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Fed Pract
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gaming
gambling
compulsive behaviors
ammunition
assault rifle
black jack
Boko Haram
bondage
child abuse
cocaine
Daech
drug paraphernalia
explosion
gun
human trafficking
ISIL
ISIS
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Islamic state
mixed martial arts
MMA
molestation
national rifle association
NRA
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pedophilia
poker
porn
pornography
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recreational drug
sex slave rings
slot machine
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Texas hold 'em
UFC
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bunges
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butt
butt fuck
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buttfucked
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cock sucker
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A peer-reviewed clinical journal serving healthcare professionals working with the Department of Veterans Affairs, the Department of Defense, and the Public Health Service.

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Anticoagulation Stewardship Efforts Via Indication Reviews at a Veterans Affairs Health Care System

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Anticoagulation Stewardship Efforts Via Indication Reviews at a Veterans Affairs Health Care System

Due to the underlying mechanism of atrial fibrillation (Afib), clots can form within the left atrial appendage. Clots that become dislodged may lead to ischemic stroke and possibly death. The 2023 guidelines for atrial fibrillation from the American College of Cardiology and American Heart Association recommend anticoagulation therapy for patients with an Afib diagnosis and a CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75 years, diabetes, stroke/vascular disease, age 65 to 74 years, and female sex) score pertinent for ≥ 1 non–sex-related factor (score ≥ 2 for women; ≥ 1 for men) to prevent stroke-related complications. The CHA2DS2-VASc score is a 9-point scoring tool based on comorbidities and conditions that increase risk of stroke in patients with Afib. Each value correlates to an annualized stroke risk percentage that increases as the score increases.

In clinical practice, patients meeting these thresholds are indicated for anticoagulation and are considered for indefinite use unless ≥ 1 of the following conditions are present: bleeding risk outweighs the stroke prevention benefit, Afib is episodic (< 48 hours) or a nonpharmacologic intervention, such as a left atrial appendage occlusion (LAAO) device is present.1

In patients with a diagnosed venous thromboembolism (VTE), such as deep vein thrombosis or pulmonary embolism, anticoagulation is used to treat the current thrombosis and prevent embolization that can ultimately lead to death. The 2021 guideline for VTE from the American College of Chest Physicians identifies certain risk factors that increase risk for VTE and categorizes them as transient or persistent. Transient risk factors include hospitalization > 3 days, major trauma, surgery, cast immobilization, hormone therapy, pregnancy, or prolonged travel > 8 hours. Persistent risk factors include malignancy, thrombophilia, and certain medications.

The guideline recommends therapy durations based on event frequency, the presence and classification of provoking risk factors, and bleeding risk. As the risk of recurrent thrombosis and other potential complications is greatest in the first 3 to 6 months after a diagnosed event, at least 3 months anticoagulation therapy is recommended following VTE diagnosis. At the 3-month mark, all regimens are suggested to be re-evaluated and considered for extended treatment duration if the event was unprovoked, recurrent, secondary to a persistent risk factor, or low bleed risk.2Anticoagulation is an important guideline-recommended pharmacologic intervention for various disease states, although its use is not without risks. The Institute for Safe Medication Practices has classified oral anticoagulants as high-alert medications. This designation was made because anticoagulant medications have the potential to cause harm when used or omitted in error and lead to life-threatening bleed or thrombotic complications.3Anticoagulation stewardship ensures that anticoagulation therapy is appropriately initiated, maintained, and discontinued when indicated. Because of the potential for harm, anticoagulation stewardship is an important part of Afib and VTE management. Pharmacists can help verify and evaluate anticoagulation therapies. Research suggests that pharmacist-led anticoagulation stewardship efforts may play a role in ensuring safer patient outcomes.4The purpose of this quality improvement (QI) study was to implement pharmacist-led anticoagulation stewardship practices at Veterans Affairs Phoenix Health Care System (VAPHCS) to identify veterans with Afib not currently on anticoagulation, as well as to identify veterans with a history of VTE events who have completed a sufficient treatment duration.

Methods

Anticoagulation stewardship efforts were implemented in 2 cohorts of patients: those with Afib who may be indicated to initiate anticoagulation, and those with a history of VTE events who may be indicated to consider anticoagulation discontinuation. Patient records were reviewed using a standardized note template, and recommendations to either initiate or discontinue anticoagulation therapy were documented. The VAPHCS Research Service reviewed this study and determined that it was not research and was exempt from institutional review board review.

Atrial Fibrillation Cohort

A population health dashboard created by the Stroke Prevention in Atrial Fibrillation/Flutter Targeting the uNTreated: a focus on health care disparities (SPAFF-TNT-D) national VA study team was used to identify veterans at VAPHCS with a diagnosis of Afib without an active VA prescription for an anticoagulant. The dashboard filtered and produced data points from the medical record that correlated to the components of the CHA2DS2-VASc score. All veterans identified by the dashboard with scores of 7 or 8 were included. No patients had a score of 9. Comprehensive chart reviews of available VA and non–VA-provided care records were conducted by the investigators, and a standardized note template designed by the SPAFF-TNT-D team (eAppendix 1) was used to document findings within the electronic health record (EHR). If anticoagulation was deemed to be indicated, the assigned primary care practitioner (PCP) as listed in the EHR was alerted to the note by the investigators for further evaluation and consideration of prescribing anticoagulation.

Venous Thromboembolism Cohort

VAPHCS pharmacy informatics pulled data that included veterans with documented VTE and an active VA anticoagulant prescription between November 2022 and November 2023. Veterans were reviewed in chronological order based on when the anticoagulant prescription was written. All veterans were included until an equal number of charts were reviewed in both the Afib and VTE cohorts. Comprehensive chart review of available VA- and non–VA-provided care records was conducted by the investigators, and a standardized note template as designed by the investigators (eAppendix 2) was used to document findings within the EHR. If the duration of anticoagulation therapy was deemed sufficient, the assigned anticoagulation clinical pharmacist practitioner (CPP) was alerted to the note by the investigators for further evaluation and consideration of discontinuing anticoagulation.

EHR reviews were conducted in October and November 2023 and lasted about 10 to 20 minutes per patient. To evaluate completeness and accuracy of the documented findings within the EHR, both investigators reviewed and cosigned the completed note template and verified the correct PCP was alerted to the recommendation for appropriate continuity of care. Results were reviewed in March 2024.

Outcomes

Atrial fibrillation cohort. The primary outcome was the number of veterans with Afib who were recommended to start anticoagulation therapy. Additional outcomes evaluated included the number of interventions completed, action taken by PCPs in response to the provided recommendation, and reasons provided by the investigators for not recommending initiation of anticoagulation therapy in specific veteran cases.

Venous thromboembolism cohort. The primary outcome was the number of veterans with a history of VTE events recommended to discontinue anticoagulation therapy. Additional outcomes included number of interventions completed, action taken by the anticoagulation CPP in response to the provided recommendation, and reasons provided by the investigators for not recommending discontinuation of anticoagulation therapy in specific veteran cases.

Analysis

Sample size was determined by the inclusion criteria and was not designed to attain statistical power. Data embedded in the Afib cohort standardized note template, also known as health factors, were later used for data analysis. Recommendations in the VTE cohort were manually tracked and recorded by the investigators. Results for this study were analyzed using descriptive statistics.

Results

A total of 114 veterans were reviewed and included in this study: 57 in each cohort. Seven recommendations were made regarding anticoagulation initiation for patients with Afib and 7 were made for anticoagulation discontinuation for patients with VTE (Table 1).

FDP04211410_T1

In the Afib cohort, 1 veteran was successfully initiated on anticoagulation therapy and 1 veteran was deemed appropriate for initiation of anticoagulation but was not reachable. Of the 5 recommendations with no action taken, 4 PCPs acknowledged the alert with no further documentation, and 1 PCP deferred the decision to cardiology with no further documentation. In the VTE cohort, 3 veterans successfully discontinued anticoagulation therapy and 2 veterans were further evaluated by the anticoagulation CPP and deemed appropriate to continue therapy based on potential for malignancy. Of the 2 recommendations with no action taken, 1 anticoagulation CPP acknowledged the alert with no further documentation and 1 anticoagulation CPP suggested further evaluation by PCP with no further documentation.

In the Afib cohort, a nonpharmacologic approach was defined as documentation of a LAAO device. An inaccurate diagnosis was defined as an Afib diagnosis being used in a previous visit, although there was no further confirmation of diagnosis via chart review. Veterans classified as already being on anticoagulation had documentation of non–VA-written anticoagulant prescriptions or receiving a supply of anticoagulants from a facility such as a nursing home. Anticoagulation was defined as unfavorable if a documented risk/benefit conversation was found via EHR review. Anticoagulation was defined as not indicated if the Afib was documented as transient, episodic, or historical (Table 2).

FDP04211410_T2

In the VTE cohort, no recommendations for discontinuation were made for veterans indicated to continue anticoagulation due to a concurrent Afib diagnosis. Chronic or recurrent events were defined as documentation of multiple VTE events and associated dates in the EHR. Persistent risk factors included malignancy or medications contributing to hypercoagulable states. Thrombophilia was defined as having documentation of a diagnosis in the EHR. An unprovoked event was defined as VTE without any documented transient risk factors (eg, hospitalization, trauma, surgery, cast immobilization, hormone therapy, pregnancy, or prolonged travel). Anticoagulation had already been discontinued in 1 veteran after the data were collected but before chart review occurred (Table 3).

FDP04211410_T3

Discussion

Pharmacy-led indication reviews resulted in appropriate recommendations for anticoagulation use in veterans with Afib and a history of VTE events. Overall, 12.3% of chart reviews in each cohort resulted in a recommendation being made, which was similar to the rate found by Koolian et al.5 In that study, 10% of recommendations were related to initiation or interruption of anticoagulation. This recommendation category consisted of several subcategories, including “suggesting therapeutic anticoagulation when none is currently ordered” and “suggesting anticoagulation cessation if no longer indicated,” but specific numerical prevalence was not provided.5

Online dashboard use allowed for greater population health management and identification of veterans with Afib who were not on active anticoagulation, providing opportunities to prevent stroke-related complications. Wang et al completed a similarly designed study that included a population health tool to identify patients with Afib who were not on anticoagulation and implemented pharmacist-led chart review and facilitation of recommendations to the responsible clinician. This study reviewed 1727 patients and recommended initiation of anticoagulation therapy for 75 (4.3%).6 The current study had a higher percentage of patients with recommendations for changes despite its smaller size.

Evaluating the duration of therapy for anticoagulation in veterans with a history of VTE events provided an opportunity to reduce unnecessary exposure to anticoagulation and minimize bleeding risks. Using a chart review process and standardized note template enabled the documentation of pertinent information that could be readily reviewed by the PCP. This process is a step toward ensuring VAPHCS PCPs provide guideline-recommended care and actively prevent stroke and bleeding complications. Adoption of this process into the current VAPHCS Anticoagulation Clinic workflow for review of veterans with either Afib or VTE could lead to more EHRs being reviewed and recommendations made, ultimately improving patient outcomes. 

Therapeutic interventions based on the recommendations were completed for 1 of 7 veterans (14%) and 3 of 7 veterans (43%) in the Afib and VTE cohorts, respectively. The prevalence of completed interventions in this anticoagulation stewardship study was higher than those in Wang et al, who found only 9% of their recommendations resulted in PCPs considering action related to anticoagulation, and only 4% were successfully initiated.6

In the Afib cohort, veterans identified by the dashboard with a CHA2DS2-VASc of 7 or 8 were prioritized for review. Reviewing these veterans ensured that patients with the highest stroke risk were sufficiently evaluated and started on anticoagulation as needed to reduce stroke-related complications. In contrast, because these veterans had higher CHA2DS2-VASc scores, they may have already been evaluated for anticoagulation in the past and had a documented rationale for not being placed on anticoagulation (LAAO device placement was the most common rationale). Focusing on veterans with a lower CHA2DS2-VASc score such as 1 for men or 2 for women could potentially include more opportunities for recommendations. Although stroke risk may be lower in this population compared with those with higher CHA2DS2-VASc scores, guideline-recommended anticoagulation use may be missed for these patients. 

In the VTE cohort, veterans with an anticoagulant prescription written 12 months before data collection were prioritized for review. Reviewing these veterans ensured that anticoagulation therapy met guideline recommendations of at least 3 months, with potential for extended duration upon further evaluation by a provider at that time. Based on collected results, most veterans were already reevaluated and had documented reasons why anticoagulation was still indicated; concurrent Afib was most common followed by chronic or recurrent VTE. Reviewing veterans with more recent prescriptions just over the recommended 3-month duration could potentially include more opportunities for recommendations to be made. It is more likely that by 3 months another PCP had not already weighed in on the duration of therapy, and the anticoagulation CPP could ensure a thorough review is conducted with guideline-based recommendations.

Most published literature on anticoagulation stewardship efforts is focused on inpatient management and policy changes, or concentrate on attributes of therapy such as appropriate dosing and drug interactions. This study highlighted that gaps in care related to anticoagulation use and discontinuation are present in the VAPHCS population and can be appropriately addressed via pharmacist-led indication reviews. Future studies designed to focus on initiating anticoagulation where appropriate, and discontinuing where a sufficient treatment period has been completed, are warranted to minimize this gap in care and allow health systems to work toward process changes to ensure safe and optimized care is provided for the patients they serve.

Limitations

In the Afib cohort, 5 of 7 recommendations (71%) had no further action taken by the PCP, which may represent a barrier to care. In contrast, 2 of 7 recommendations (29%) had no further action in the VTE cohort. It is possible that the difference can be attributed to the anticoagulation CPP receiving VTE alerts and PCPs receiving Afib alerts. The anticoagulation CPP was familiar with this QI study and may have better understood the purpose of the chart review and the need to provide a timely response. PCPs may have been less likely to take action because they were unfamiliar with the anticoagulation stewardship initiative and standardized note template or overwhelmed by too many EHR alerts.

The lack of PCP response to a virtual alert or message also was observed by Wang et al, whereas Koolian et al reported higher intervention completion rates, with verbal recommendations being made to the responsible clinicians. To further ensure these pertinent recommendations for anticoagulation initiation in veterans with Afib are properly reviewed and evaluated, future research could include intentional follow-up with the PCP regarding the alert, PCP-specific education about the anticoagulation stewardship initiative and the role of the standardized note template, and collaboration with PCPs to identify alternative ways to relay recommendations in a way that would ensure the completion of appropriate and timely review.

Conclusions

This study identified gaps in care related to anticoagulation needs in the VAPHCS veteran population. Utilizing a standardized indication review process allows pharmacists to evaluate anticoagulant use for both appropriate indication and duration of therapy. Providing recommendations via chart review notes and alerting respective PCPs and CPPs results in veterans receiving safe and optimized care regarding their anticoagulation needs.

References
  1. Joglar JA, Chung MK, Armbruster AL, et al. 2023 ACC/AHA/ACCP/HRS guideline for the diagnosis and management of atrial fibrillation: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2024;149:e1-e156. doi:10.1161/CIR.0000000000001193
  2. Stevens SM, Woller SC, Kreuziger LB, et al. Antithrombotic therapy for VTE disease: second update of the CHEST guideline and expert panel report. Chest. 2021;160:e545-e608. doi:10.1016/j.chest.2021.07.055
  3. Institute for Safe Medication Practices (ISMP). List of high-alert medications in community/ambulatory care settings. ISMP. September 30, 2021. Accessed September 11, 2025. https://home.ecri.org/blogs/ismp-resources/high-alert-medications-in-community-ambulatory-care-settings
  4. Burnett AE, Barnes GD. A call to action for anticoagulation stewardship. Res Pract Thromb Haemost. 2022;6:e12757. doi:10.1002/rth2.12757
  5. Koolian M, Wiseman D, Mantzanis H, et al. Anticoagulation stewardship: descriptive analysis of a novel approach to appropriate anticoagulant prescription. Res Pract Thromb Haemost. 2022;6:e12758. doi:10.1002/rth2.12758
  6. Wang SV, Rogers JR, Jin Y, et al. Stepped-wedge randomised trial to evaluate population health intervention designed to increase appropriate anticoagulation in patients with atrial fibrillation. BMJ Qual Saf. 2019;28:835-842. doi:10.1136/bmjqs-2019-009367
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Alexandra Brown, PharmDa; Annie Tam, PharmDa

Correspondence: Alexandra Brown (Alexandra.brown2@va.gov)

Author affiliations aVeterans Affairs Phoenix Health Care System, Arizona

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Fed Pract. 2025;42(11). Published online November 15. doi:10.12788/fp.0648

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Alexandra Brown, PharmDa; Annie Tam, PharmDa

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Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Fed Pract. 2025;42(11). Published online November 15. doi:10.12788/fp.0648

Author and Disclosure Information

Alexandra Brown, PharmDa; Annie Tam, PharmDa

Correspondence: Alexandra Brown (Alexandra.brown2@va.gov)

Author affiliations aVeterans Affairs Phoenix Health Care System, Arizona

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Fed Pract. 2025;42(11). Published online November 15. doi:10.12788/fp.0648

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Due to the underlying mechanism of atrial fibrillation (Afib), clots can form within the left atrial appendage. Clots that become dislodged may lead to ischemic stroke and possibly death. The 2023 guidelines for atrial fibrillation from the American College of Cardiology and American Heart Association recommend anticoagulation therapy for patients with an Afib diagnosis and a CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75 years, diabetes, stroke/vascular disease, age 65 to 74 years, and female sex) score pertinent for ≥ 1 non–sex-related factor (score ≥ 2 for women; ≥ 1 for men) to prevent stroke-related complications. The CHA2DS2-VASc score is a 9-point scoring tool based on comorbidities and conditions that increase risk of stroke in patients with Afib. Each value correlates to an annualized stroke risk percentage that increases as the score increases.

In clinical practice, patients meeting these thresholds are indicated for anticoagulation and are considered for indefinite use unless ≥ 1 of the following conditions are present: bleeding risk outweighs the stroke prevention benefit, Afib is episodic (< 48 hours) or a nonpharmacologic intervention, such as a left atrial appendage occlusion (LAAO) device is present.1

In patients with a diagnosed venous thromboembolism (VTE), such as deep vein thrombosis or pulmonary embolism, anticoagulation is used to treat the current thrombosis and prevent embolization that can ultimately lead to death. The 2021 guideline for VTE from the American College of Chest Physicians identifies certain risk factors that increase risk for VTE and categorizes them as transient or persistent. Transient risk factors include hospitalization > 3 days, major trauma, surgery, cast immobilization, hormone therapy, pregnancy, or prolonged travel > 8 hours. Persistent risk factors include malignancy, thrombophilia, and certain medications.

The guideline recommends therapy durations based on event frequency, the presence and classification of provoking risk factors, and bleeding risk. As the risk of recurrent thrombosis and other potential complications is greatest in the first 3 to 6 months after a diagnosed event, at least 3 months anticoagulation therapy is recommended following VTE diagnosis. At the 3-month mark, all regimens are suggested to be re-evaluated and considered for extended treatment duration if the event was unprovoked, recurrent, secondary to a persistent risk factor, or low bleed risk.2Anticoagulation is an important guideline-recommended pharmacologic intervention for various disease states, although its use is not without risks. The Institute for Safe Medication Practices has classified oral anticoagulants as high-alert medications. This designation was made because anticoagulant medications have the potential to cause harm when used or omitted in error and lead to life-threatening bleed or thrombotic complications.3Anticoagulation stewardship ensures that anticoagulation therapy is appropriately initiated, maintained, and discontinued when indicated. Because of the potential for harm, anticoagulation stewardship is an important part of Afib and VTE management. Pharmacists can help verify and evaluate anticoagulation therapies. Research suggests that pharmacist-led anticoagulation stewardship efforts may play a role in ensuring safer patient outcomes.4The purpose of this quality improvement (QI) study was to implement pharmacist-led anticoagulation stewardship practices at Veterans Affairs Phoenix Health Care System (VAPHCS) to identify veterans with Afib not currently on anticoagulation, as well as to identify veterans with a history of VTE events who have completed a sufficient treatment duration.

Methods

Anticoagulation stewardship efforts were implemented in 2 cohorts of patients: those with Afib who may be indicated to initiate anticoagulation, and those with a history of VTE events who may be indicated to consider anticoagulation discontinuation. Patient records were reviewed using a standardized note template, and recommendations to either initiate or discontinue anticoagulation therapy were documented. The VAPHCS Research Service reviewed this study and determined that it was not research and was exempt from institutional review board review.

Atrial Fibrillation Cohort

A population health dashboard created by the Stroke Prevention in Atrial Fibrillation/Flutter Targeting the uNTreated: a focus on health care disparities (SPAFF-TNT-D) national VA study team was used to identify veterans at VAPHCS with a diagnosis of Afib without an active VA prescription for an anticoagulant. The dashboard filtered and produced data points from the medical record that correlated to the components of the CHA2DS2-VASc score. All veterans identified by the dashboard with scores of 7 or 8 were included. No patients had a score of 9. Comprehensive chart reviews of available VA and non–VA-provided care records were conducted by the investigators, and a standardized note template designed by the SPAFF-TNT-D team (eAppendix 1) was used to document findings within the electronic health record (EHR). If anticoagulation was deemed to be indicated, the assigned primary care practitioner (PCP) as listed in the EHR was alerted to the note by the investigators for further evaluation and consideration of prescribing anticoagulation.

Venous Thromboembolism Cohort

VAPHCS pharmacy informatics pulled data that included veterans with documented VTE and an active VA anticoagulant prescription between November 2022 and November 2023. Veterans were reviewed in chronological order based on when the anticoagulant prescription was written. All veterans were included until an equal number of charts were reviewed in both the Afib and VTE cohorts. Comprehensive chart review of available VA- and non–VA-provided care records was conducted by the investigators, and a standardized note template as designed by the investigators (eAppendix 2) was used to document findings within the EHR. If the duration of anticoagulation therapy was deemed sufficient, the assigned anticoagulation clinical pharmacist practitioner (CPP) was alerted to the note by the investigators for further evaluation and consideration of discontinuing anticoagulation.

EHR reviews were conducted in October and November 2023 and lasted about 10 to 20 minutes per patient. To evaluate completeness and accuracy of the documented findings within the EHR, both investigators reviewed and cosigned the completed note template and verified the correct PCP was alerted to the recommendation for appropriate continuity of care. Results were reviewed in March 2024.

Outcomes

Atrial fibrillation cohort. The primary outcome was the number of veterans with Afib who were recommended to start anticoagulation therapy. Additional outcomes evaluated included the number of interventions completed, action taken by PCPs in response to the provided recommendation, and reasons provided by the investigators for not recommending initiation of anticoagulation therapy in specific veteran cases.

Venous thromboembolism cohort. The primary outcome was the number of veterans with a history of VTE events recommended to discontinue anticoagulation therapy. Additional outcomes included number of interventions completed, action taken by the anticoagulation CPP in response to the provided recommendation, and reasons provided by the investigators for not recommending discontinuation of anticoagulation therapy in specific veteran cases.

Analysis

Sample size was determined by the inclusion criteria and was not designed to attain statistical power. Data embedded in the Afib cohort standardized note template, also known as health factors, were later used for data analysis. Recommendations in the VTE cohort were manually tracked and recorded by the investigators. Results for this study were analyzed using descriptive statistics.

Results

A total of 114 veterans were reviewed and included in this study: 57 in each cohort. Seven recommendations were made regarding anticoagulation initiation for patients with Afib and 7 were made for anticoagulation discontinuation for patients with VTE (Table 1).

FDP04211410_T1

In the Afib cohort, 1 veteran was successfully initiated on anticoagulation therapy and 1 veteran was deemed appropriate for initiation of anticoagulation but was not reachable. Of the 5 recommendations with no action taken, 4 PCPs acknowledged the alert with no further documentation, and 1 PCP deferred the decision to cardiology with no further documentation. In the VTE cohort, 3 veterans successfully discontinued anticoagulation therapy and 2 veterans were further evaluated by the anticoagulation CPP and deemed appropriate to continue therapy based on potential for malignancy. Of the 2 recommendations with no action taken, 1 anticoagulation CPP acknowledged the alert with no further documentation and 1 anticoagulation CPP suggested further evaluation by PCP with no further documentation.

In the Afib cohort, a nonpharmacologic approach was defined as documentation of a LAAO device. An inaccurate diagnosis was defined as an Afib diagnosis being used in a previous visit, although there was no further confirmation of diagnosis via chart review. Veterans classified as already being on anticoagulation had documentation of non–VA-written anticoagulant prescriptions or receiving a supply of anticoagulants from a facility such as a nursing home. Anticoagulation was defined as unfavorable if a documented risk/benefit conversation was found via EHR review. Anticoagulation was defined as not indicated if the Afib was documented as transient, episodic, or historical (Table 2).

FDP04211410_T2

In the VTE cohort, no recommendations for discontinuation were made for veterans indicated to continue anticoagulation due to a concurrent Afib diagnosis. Chronic or recurrent events were defined as documentation of multiple VTE events and associated dates in the EHR. Persistent risk factors included malignancy or medications contributing to hypercoagulable states. Thrombophilia was defined as having documentation of a diagnosis in the EHR. An unprovoked event was defined as VTE without any documented transient risk factors (eg, hospitalization, trauma, surgery, cast immobilization, hormone therapy, pregnancy, or prolonged travel). Anticoagulation had already been discontinued in 1 veteran after the data were collected but before chart review occurred (Table 3).

FDP04211410_T3

Discussion

Pharmacy-led indication reviews resulted in appropriate recommendations for anticoagulation use in veterans with Afib and a history of VTE events. Overall, 12.3% of chart reviews in each cohort resulted in a recommendation being made, which was similar to the rate found by Koolian et al.5 In that study, 10% of recommendations were related to initiation or interruption of anticoagulation. This recommendation category consisted of several subcategories, including “suggesting therapeutic anticoagulation when none is currently ordered” and “suggesting anticoagulation cessation if no longer indicated,” but specific numerical prevalence was not provided.5

Online dashboard use allowed for greater population health management and identification of veterans with Afib who were not on active anticoagulation, providing opportunities to prevent stroke-related complications. Wang et al completed a similarly designed study that included a population health tool to identify patients with Afib who were not on anticoagulation and implemented pharmacist-led chart review and facilitation of recommendations to the responsible clinician. This study reviewed 1727 patients and recommended initiation of anticoagulation therapy for 75 (4.3%).6 The current study had a higher percentage of patients with recommendations for changes despite its smaller size.

Evaluating the duration of therapy for anticoagulation in veterans with a history of VTE events provided an opportunity to reduce unnecessary exposure to anticoagulation and minimize bleeding risks. Using a chart review process and standardized note template enabled the documentation of pertinent information that could be readily reviewed by the PCP. This process is a step toward ensuring VAPHCS PCPs provide guideline-recommended care and actively prevent stroke and bleeding complications. Adoption of this process into the current VAPHCS Anticoagulation Clinic workflow for review of veterans with either Afib or VTE could lead to more EHRs being reviewed and recommendations made, ultimately improving patient outcomes. 

Therapeutic interventions based on the recommendations were completed for 1 of 7 veterans (14%) and 3 of 7 veterans (43%) in the Afib and VTE cohorts, respectively. The prevalence of completed interventions in this anticoagulation stewardship study was higher than those in Wang et al, who found only 9% of their recommendations resulted in PCPs considering action related to anticoagulation, and only 4% were successfully initiated.6

In the Afib cohort, veterans identified by the dashboard with a CHA2DS2-VASc of 7 or 8 were prioritized for review. Reviewing these veterans ensured that patients with the highest stroke risk were sufficiently evaluated and started on anticoagulation as needed to reduce stroke-related complications. In contrast, because these veterans had higher CHA2DS2-VASc scores, they may have already been evaluated for anticoagulation in the past and had a documented rationale for not being placed on anticoagulation (LAAO device placement was the most common rationale). Focusing on veterans with a lower CHA2DS2-VASc score such as 1 for men or 2 for women could potentially include more opportunities for recommendations. Although stroke risk may be lower in this population compared with those with higher CHA2DS2-VASc scores, guideline-recommended anticoagulation use may be missed for these patients. 

In the VTE cohort, veterans with an anticoagulant prescription written 12 months before data collection were prioritized for review. Reviewing these veterans ensured that anticoagulation therapy met guideline recommendations of at least 3 months, with potential for extended duration upon further evaluation by a provider at that time. Based on collected results, most veterans were already reevaluated and had documented reasons why anticoagulation was still indicated; concurrent Afib was most common followed by chronic or recurrent VTE. Reviewing veterans with more recent prescriptions just over the recommended 3-month duration could potentially include more opportunities for recommendations to be made. It is more likely that by 3 months another PCP had not already weighed in on the duration of therapy, and the anticoagulation CPP could ensure a thorough review is conducted with guideline-based recommendations.

Most published literature on anticoagulation stewardship efforts is focused on inpatient management and policy changes, or concentrate on attributes of therapy such as appropriate dosing and drug interactions. This study highlighted that gaps in care related to anticoagulation use and discontinuation are present in the VAPHCS population and can be appropriately addressed via pharmacist-led indication reviews. Future studies designed to focus on initiating anticoagulation where appropriate, and discontinuing where a sufficient treatment period has been completed, are warranted to minimize this gap in care and allow health systems to work toward process changes to ensure safe and optimized care is provided for the patients they serve.

Limitations

In the Afib cohort, 5 of 7 recommendations (71%) had no further action taken by the PCP, which may represent a barrier to care. In contrast, 2 of 7 recommendations (29%) had no further action in the VTE cohort. It is possible that the difference can be attributed to the anticoagulation CPP receiving VTE alerts and PCPs receiving Afib alerts. The anticoagulation CPP was familiar with this QI study and may have better understood the purpose of the chart review and the need to provide a timely response. PCPs may have been less likely to take action because they were unfamiliar with the anticoagulation stewardship initiative and standardized note template or overwhelmed by too many EHR alerts.

The lack of PCP response to a virtual alert or message also was observed by Wang et al, whereas Koolian et al reported higher intervention completion rates, with verbal recommendations being made to the responsible clinicians. To further ensure these pertinent recommendations for anticoagulation initiation in veterans with Afib are properly reviewed and evaluated, future research could include intentional follow-up with the PCP regarding the alert, PCP-specific education about the anticoagulation stewardship initiative and the role of the standardized note template, and collaboration with PCPs to identify alternative ways to relay recommendations in a way that would ensure the completion of appropriate and timely review.

Conclusions

This study identified gaps in care related to anticoagulation needs in the VAPHCS veteran population. Utilizing a standardized indication review process allows pharmacists to evaluate anticoagulant use for both appropriate indication and duration of therapy. Providing recommendations via chart review notes and alerting respective PCPs and CPPs results in veterans receiving safe and optimized care regarding their anticoagulation needs.

Due to the underlying mechanism of atrial fibrillation (Afib), clots can form within the left atrial appendage. Clots that become dislodged may lead to ischemic stroke and possibly death. The 2023 guidelines for atrial fibrillation from the American College of Cardiology and American Heart Association recommend anticoagulation therapy for patients with an Afib diagnosis and a CHA2DS2-VASc (congestive heart failure, hypertension, age ≥ 75 years, diabetes, stroke/vascular disease, age 65 to 74 years, and female sex) score pertinent for ≥ 1 non–sex-related factor (score ≥ 2 for women; ≥ 1 for men) to prevent stroke-related complications. The CHA2DS2-VASc score is a 9-point scoring tool based on comorbidities and conditions that increase risk of stroke in patients with Afib. Each value correlates to an annualized stroke risk percentage that increases as the score increases.

In clinical practice, patients meeting these thresholds are indicated for anticoagulation and are considered for indefinite use unless ≥ 1 of the following conditions are present: bleeding risk outweighs the stroke prevention benefit, Afib is episodic (< 48 hours) or a nonpharmacologic intervention, such as a left atrial appendage occlusion (LAAO) device is present.1

In patients with a diagnosed venous thromboembolism (VTE), such as deep vein thrombosis or pulmonary embolism, anticoagulation is used to treat the current thrombosis and prevent embolization that can ultimately lead to death. The 2021 guideline for VTE from the American College of Chest Physicians identifies certain risk factors that increase risk for VTE and categorizes them as transient or persistent. Transient risk factors include hospitalization > 3 days, major trauma, surgery, cast immobilization, hormone therapy, pregnancy, or prolonged travel > 8 hours. Persistent risk factors include malignancy, thrombophilia, and certain medications.

The guideline recommends therapy durations based on event frequency, the presence and classification of provoking risk factors, and bleeding risk. As the risk of recurrent thrombosis and other potential complications is greatest in the first 3 to 6 months after a diagnosed event, at least 3 months anticoagulation therapy is recommended following VTE diagnosis. At the 3-month mark, all regimens are suggested to be re-evaluated and considered for extended treatment duration if the event was unprovoked, recurrent, secondary to a persistent risk factor, or low bleed risk.2Anticoagulation is an important guideline-recommended pharmacologic intervention for various disease states, although its use is not without risks. The Institute for Safe Medication Practices has classified oral anticoagulants as high-alert medications. This designation was made because anticoagulant medications have the potential to cause harm when used or omitted in error and lead to life-threatening bleed or thrombotic complications.3Anticoagulation stewardship ensures that anticoagulation therapy is appropriately initiated, maintained, and discontinued when indicated. Because of the potential for harm, anticoagulation stewardship is an important part of Afib and VTE management. Pharmacists can help verify and evaluate anticoagulation therapies. Research suggests that pharmacist-led anticoagulation stewardship efforts may play a role in ensuring safer patient outcomes.4The purpose of this quality improvement (QI) study was to implement pharmacist-led anticoagulation stewardship practices at Veterans Affairs Phoenix Health Care System (VAPHCS) to identify veterans with Afib not currently on anticoagulation, as well as to identify veterans with a history of VTE events who have completed a sufficient treatment duration.

Methods

Anticoagulation stewardship efforts were implemented in 2 cohorts of patients: those with Afib who may be indicated to initiate anticoagulation, and those with a history of VTE events who may be indicated to consider anticoagulation discontinuation. Patient records were reviewed using a standardized note template, and recommendations to either initiate or discontinue anticoagulation therapy were documented. The VAPHCS Research Service reviewed this study and determined that it was not research and was exempt from institutional review board review.

Atrial Fibrillation Cohort

A population health dashboard created by the Stroke Prevention in Atrial Fibrillation/Flutter Targeting the uNTreated: a focus on health care disparities (SPAFF-TNT-D) national VA study team was used to identify veterans at VAPHCS with a diagnosis of Afib without an active VA prescription for an anticoagulant. The dashboard filtered and produced data points from the medical record that correlated to the components of the CHA2DS2-VASc score. All veterans identified by the dashboard with scores of 7 or 8 were included. No patients had a score of 9. Comprehensive chart reviews of available VA and non–VA-provided care records were conducted by the investigators, and a standardized note template designed by the SPAFF-TNT-D team (eAppendix 1) was used to document findings within the electronic health record (EHR). If anticoagulation was deemed to be indicated, the assigned primary care practitioner (PCP) as listed in the EHR was alerted to the note by the investigators for further evaluation and consideration of prescribing anticoagulation.

Venous Thromboembolism Cohort

VAPHCS pharmacy informatics pulled data that included veterans with documented VTE and an active VA anticoagulant prescription between November 2022 and November 2023. Veterans were reviewed in chronological order based on when the anticoagulant prescription was written. All veterans were included until an equal number of charts were reviewed in both the Afib and VTE cohorts. Comprehensive chart review of available VA- and non–VA-provided care records was conducted by the investigators, and a standardized note template as designed by the investigators (eAppendix 2) was used to document findings within the EHR. If the duration of anticoagulation therapy was deemed sufficient, the assigned anticoagulation clinical pharmacist practitioner (CPP) was alerted to the note by the investigators for further evaluation and consideration of discontinuing anticoagulation.

EHR reviews were conducted in October and November 2023 and lasted about 10 to 20 minutes per patient. To evaluate completeness and accuracy of the documented findings within the EHR, both investigators reviewed and cosigned the completed note template and verified the correct PCP was alerted to the recommendation for appropriate continuity of care. Results were reviewed in March 2024.

Outcomes

Atrial fibrillation cohort. The primary outcome was the number of veterans with Afib who were recommended to start anticoagulation therapy. Additional outcomes evaluated included the number of interventions completed, action taken by PCPs in response to the provided recommendation, and reasons provided by the investigators for not recommending initiation of anticoagulation therapy in specific veteran cases.

Venous thromboembolism cohort. The primary outcome was the number of veterans with a history of VTE events recommended to discontinue anticoagulation therapy. Additional outcomes included number of interventions completed, action taken by the anticoagulation CPP in response to the provided recommendation, and reasons provided by the investigators for not recommending discontinuation of anticoagulation therapy in specific veteran cases.

Analysis

Sample size was determined by the inclusion criteria and was not designed to attain statistical power. Data embedded in the Afib cohort standardized note template, also known as health factors, were later used for data analysis. Recommendations in the VTE cohort were manually tracked and recorded by the investigators. Results for this study were analyzed using descriptive statistics.

Results

A total of 114 veterans were reviewed and included in this study: 57 in each cohort. Seven recommendations were made regarding anticoagulation initiation for patients with Afib and 7 were made for anticoagulation discontinuation for patients with VTE (Table 1).

FDP04211410_T1

In the Afib cohort, 1 veteran was successfully initiated on anticoagulation therapy and 1 veteran was deemed appropriate for initiation of anticoagulation but was not reachable. Of the 5 recommendations with no action taken, 4 PCPs acknowledged the alert with no further documentation, and 1 PCP deferred the decision to cardiology with no further documentation. In the VTE cohort, 3 veterans successfully discontinued anticoagulation therapy and 2 veterans were further evaluated by the anticoagulation CPP and deemed appropriate to continue therapy based on potential for malignancy. Of the 2 recommendations with no action taken, 1 anticoagulation CPP acknowledged the alert with no further documentation and 1 anticoagulation CPP suggested further evaluation by PCP with no further documentation.

In the Afib cohort, a nonpharmacologic approach was defined as documentation of a LAAO device. An inaccurate diagnosis was defined as an Afib diagnosis being used in a previous visit, although there was no further confirmation of diagnosis via chart review. Veterans classified as already being on anticoagulation had documentation of non–VA-written anticoagulant prescriptions or receiving a supply of anticoagulants from a facility such as a nursing home. Anticoagulation was defined as unfavorable if a documented risk/benefit conversation was found via EHR review. Anticoagulation was defined as not indicated if the Afib was documented as transient, episodic, or historical (Table 2).

FDP04211410_T2

In the VTE cohort, no recommendations for discontinuation were made for veterans indicated to continue anticoagulation due to a concurrent Afib diagnosis. Chronic or recurrent events were defined as documentation of multiple VTE events and associated dates in the EHR. Persistent risk factors included malignancy or medications contributing to hypercoagulable states. Thrombophilia was defined as having documentation of a diagnosis in the EHR. An unprovoked event was defined as VTE without any documented transient risk factors (eg, hospitalization, trauma, surgery, cast immobilization, hormone therapy, pregnancy, or prolonged travel). Anticoagulation had already been discontinued in 1 veteran after the data were collected but before chart review occurred (Table 3).

FDP04211410_T3

Discussion

Pharmacy-led indication reviews resulted in appropriate recommendations for anticoagulation use in veterans with Afib and a history of VTE events. Overall, 12.3% of chart reviews in each cohort resulted in a recommendation being made, which was similar to the rate found by Koolian et al.5 In that study, 10% of recommendations were related to initiation or interruption of anticoagulation. This recommendation category consisted of several subcategories, including “suggesting therapeutic anticoagulation when none is currently ordered” and “suggesting anticoagulation cessation if no longer indicated,” but specific numerical prevalence was not provided.5

Online dashboard use allowed for greater population health management and identification of veterans with Afib who were not on active anticoagulation, providing opportunities to prevent stroke-related complications. Wang et al completed a similarly designed study that included a population health tool to identify patients with Afib who were not on anticoagulation and implemented pharmacist-led chart review and facilitation of recommendations to the responsible clinician. This study reviewed 1727 patients and recommended initiation of anticoagulation therapy for 75 (4.3%).6 The current study had a higher percentage of patients with recommendations for changes despite its smaller size.

Evaluating the duration of therapy for anticoagulation in veterans with a history of VTE events provided an opportunity to reduce unnecessary exposure to anticoagulation and minimize bleeding risks. Using a chart review process and standardized note template enabled the documentation of pertinent information that could be readily reviewed by the PCP. This process is a step toward ensuring VAPHCS PCPs provide guideline-recommended care and actively prevent stroke and bleeding complications. Adoption of this process into the current VAPHCS Anticoagulation Clinic workflow for review of veterans with either Afib or VTE could lead to more EHRs being reviewed and recommendations made, ultimately improving patient outcomes. 

Therapeutic interventions based on the recommendations were completed for 1 of 7 veterans (14%) and 3 of 7 veterans (43%) in the Afib and VTE cohorts, respectively. The prevalence of completed interventions in this anticoagulation stewardship study was higher than those in Wang et al, who found only 9% of their recommendations resulted in PCPs considering action related to anticoagulation, and only 4% were successfully initiated.6

In the Afib cohort, veterans identified by the dashboard with a CHA2DS2-VASc of 7 or 8 were prioritized for review. Reviewing these veterans ensured that patients with the highest stroke risk were sufficiently evaluated and started on anticoagulation as needed to reduce stroke-related complications. In contrast, because these veterans had higher CHA2DS2-VASc scores, they may have already been evaluated for anticoagulation in the past and had a documented rationale for not being placed on anticoagulation (LAAO device placement was the most common rationale). Focusing on veterans with a lower CHA2DS2-VASc score such as 1 for men or 2 for women could potentially include more opportunities for recommendations. Although stroke risk may be lower in this population compared with those with higher CHA2DS2-VASc scores, guideline-recommended anticoagulation use may be missed for these patients. 

In the VTE cohort, veterans with an anticoagulant prescription written 12 months before data collection were prioritized for review. Reviewing these veterans ensured that anticoagulation therapy met guideline recommendations of at least 3 months, with potential for extended duration upon further evaluation by a provider at that time. Based on collected results, most veterans were already reevaluated and had documented reasons why anticoagulation was still indicated; concurrent Afib was most common followed by chronic or recurrent VTE. Reviewing veterans with more recent prescriptions just over the recommended 3-month duration could potentially include more opportunities for recommendations to be made. It is more likely that by 3 months another PCP had not already weighed in on the duration of therapy, and the anticoagulation CPP could ensure a thorough review is conducted with guideline-based recommendations.

Most published literature on anticoagulation stewardship efforts is focused on inpatient management and policy changes, or concentrate on attributes of therapy such as appropriate dosing and drug interactions. This study highlighted that gaps in care related to anticoagulation use and discontinuation are present in the VAPHCS population and can be appropriately addressed via pharmacist-led indication reviews. Future studies designed to focus on initiating anticoagulation where appropriate, and discontinuing where a sufficient treatment period has been completed, are warranted to minimize this gap in care and allow health systems to work toward process changes to ensure safe and optimized care is provided for the patients they serve.

Limitations

In the Afib cohort, 5 of 7 recommendations (71%) had no further action taken by the PCP, which may represent a barrier to care. In contrast, 2 of 7 recommendations (29%) had no further action in the VTE cohort. It is possible that the difference can be attributed to the anticoagulation CPP receiving VTE alerts and PCPs receiving Afib alerts. The anticoagulation CPP was familiar with this QI study and may have better understood the purpose of the chart review and the need to provide a timely response. PCPs may have been less likely to take action because they were unfamiliar with the anticoagulation stewardship initiative and standardized note template or overwhelmed by too many EHR alerts.

The lack of PCP response to a virtual alert or message also was observed by Wang et al, whereas Koolian et al reported higher intervention completion rates, with verbal recommendations being made to the responsible clinicians. To further ensure these pertinent recommendations for anticoagulation initiation in veterans with Afib are properly reviewed and evaluated, future research could include intentional follow-up with the PCP regarding the alert, PCP-specific education about the anticoagulation stewardship initiative and the role of the standardized note template, and collaboration with PCPs to identify alternative ways to relay recommendations in a way that would ensure the completion of appropriate and timely review.

Conclusions

This study identified gaps in care related to anticoagulation needs in the VAPHCS veteran population. Utilizing a standardized indication review process allows pharmacists to evaluate anticoagulant use for both appropriate indication and duration of therapy. Providing recommendations via chart review notes and alerting respective PCPs and CPPs results in veterans receiving safe and optimized care regarding their anticoagulation needs.

References
  1. Joglar JA, Chung MK, Armbruster AL, et al. 2023 ACC/AHA/ACCP/HRS guideline for the diagnosis and management of atrial fibrillation: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2024;149:e1-e156. doi:10.1161/CIR.0000000000001193
  2. Stevens SM, Woller SC, Kreuziger LB, et al. Antithrombotic therapy for VTE disease: second update of the CHEST guideline and expert panel report. Chest. 2021;160:e545-e608. doi:10.1016/j.chest.2021.07.055
  3. Institute for Safe Medication Practices (ISMP). List of high-alert medications in community/ambulatory care settings. ISMP. September 30, 2021. Accessed September 11, 2025. https://home.ecri.org/blogs/ismp-resources/high-alert-medications-in-community-ambulatory-care-settings
  4. Burnett AE, Barnes GD. A call to action for anticoagulation stewardship. Res Pract Thromb Haemost. 2022;6:e12757. doi:10.1002/rth2.12757
  5. Koolian M, Wiseman D, Mantzanis H, et al. Anticoagulation stewardship: descriptive analysis of a novel approach to appropriate anticoagulant prescription. Res Pract Thromb Haemost. 2022;6:e12758. doi:10.1002/rth2.12758
  6. Wang SV, Rogers JR, Jin Y, et al. Stepped-wedge randomised trial to evaluate population health intervention designed to increase appropriate anticoagulation in patients with atrial fibrillation. BMJ Qual Saf. 2019;28:835-842. doi:10.1136/bmjqs-2019-009367
References
  1. Joglar JA, Chung MK, Armbruster AL, et al. 2023 ACC/AHA/ACCP/HRS guideline for the diagnosis and management of atrial fibrillation: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2024;149:e1-e156. doi:10.1161/CIR.0000000000001193
  2. Stevens SM, Woller SC, Kreuziger LB, et al. Antithrombotic therapy for VTE disease: second update of the CHEST guideline and expert panel report. Chest. 2021;160:e545-e608. doi:10.1016/j.chest.2021.07.055
  3. Institute for Safe Medication Practices (ISMP). List of high-alert medications in community/ambulatory care settings. ISMP. September 30, 2021. Accessed September 11, 2025. https://home.ecri.org/blogs/ismp-resources/high-alert-medications-in-community-ambulatory-care-settings
  4. Burnett AE, Barnes GD. A call to action for anticoagulation stewardship. Res Pract Thromb Haemost. 2022;6:e12757. doi:10.1002/rth2.12757
  5. Koolian M, Wiseman D, Mantzanis H, et al. Anticoagulation stewardship: descriptive analysis of a novel approach to appropriate anticoagulant prescription. Res Pract Thromb Haemost. 2022;6:e12758. doi:10.1002/rth2.12758
  6. Wang SV, Rogers JR, Jin Y, et al. Stepped-wedge randomised trial to evaluate population health intervention designed to increase appropriate anticoagulation in patients with atrial fibrillation. BMJ Qual Saf. 2019;28:835-842. doi:10.1136/bmjqs-2019-009367
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Process Improvement for Engaging With Trauma-Focused Evidence-Based Psychotherapy for PTSD

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Process Improvement for Engaging With Trauma-Focused Evidence-Based Psychotherapy for PTSD

Trauma-focused evidence-based psychotherapies (TF-EBPs), including cognitive processing therapy (CPT) and prolonged exposure therapy (PE), are recommended treatments for posttraumatic stress disorder (PTSD) in clinical practice guidelines.1-3 To increase initiation of these treatments, the US Department of Veterans Affairs (VA) used a large-scale dissemination and implementation effort to improve access to TF-EBP.4,5 These efforts achieved modest success, increasing prevalence of TF-EBP from a handful of veterans in 2004 to an annual prevalence of 14.6% for CPT and 4.3% for PE in 2014.6

Throughout these efforts, qualitative studies have been used to better understand veterans’ perspectives on receiving TF-EBP care.7-18 Barriers to initiation of and engagement in TF-EBP and PTSD care have been identified from these qualitative studies. One identified barrier was lack of knowledge—particularly lack of knowledge about what is meant by a PTSD diagnosis and available treatments.7-10 Stigma (ie, automatic negative associations) toward mental health problems or seeking mental health care also has been identified as a barrier to initiation.7,10-14 Perceptions of poor alignment between treatment and veteran goals, including lack of buy-in for the rationale, served as barriers to initiation and engagement.8,15-18

Using prior qualitative work, numerous initiatives have been developed to reduce stigma, facilitate conversations about how treatment aligns with goals, and fill knowledge gaps, particularly through online resources and shared decision-making.19,20 To better inform the state of veterans’ experiences with TF-EBP, a qualitative investigation was conducted involving veterans who recently initiated TF-EBP. Themes directly related to transitions to TF-EBP were identified; however, all veterans interviewed also described their experiences with TFEBP engagement and mental health care. Consistent with recommendations for qualitative methods, this study extends prior work on transitions to TF-EBP by describing themes with a distinct focus on the experience of engaging with TF-EBP and mental health care.21,22

Methods

The experiences of veterans who were transitioning into TF-EBPs were collected in semistructured interviews and analyzed. The semistructured interview guide was developed and refined in consultation with both qualitative methods experts and PTSD treatment experts to ensure that 6 content domains were appropriately queried: PTSD treatment options, cultural sensitivity of treatment, PTSD treatment selection, transition criteria, beliefs about stabilization treatment, and treatment needs/preferences.

Participants were identified using the VA Corporate Data Warehouse and included post-9/11 veterans who had recently initiated CPT or PE for the first time between September 1, 2021, and September 1, 2022. More details of participant selection are available in Holder et al.21 From a population of 10,814 patients, stratified random sampling generated a recruitment pool of 200 veterans for further outreach. The strata were defined such that this recruitment pool had similar proportions of demographic characteristics (ie, gender, race, ethnicity) to the population of eligible veterans, equivalent distributions of time to CPT or PE initiation (ie, 33.3% < 1 year, 33.3% 1-3 years, and 33.3% > 3 years), and adequate variability in TF-EBP type (ie, 66.7% CPT, 33.3% PE). A manual chart review in the recruitment pool excluded 12 veterans who did not initiate CPT or PE, 1 veteran with evidence of current active psychosis and/or cognitive impairment that would likely preclude comprehension of study materials, and 1 who was deceased.

Eligible veterans from the recruitment pool were contacted in groups of 25. First, a recruitment letter with study information and instructions to opt-out of further contact was mailed or emailed to veterans. After 2 weeks, veterans who had not responded were contacted by phone up to 3 times. Veterans interested in participating were scheduled for a 1-time visit that included verbal consent and the qualitative interview. Metrics were established a priori to ensure an adequately diverse and inclusive sample. Specifically, a minimum number of racial and/or ethnic minority veterans (33%) and women veterans (20%) were sought. Equal distribution across the 3 categories of time from first mental health visit to CPT/PE initiation also was targeted. Throughout enrollment, recruitment efforts were adapted to meet these metrics in the emerging sample. While the goal was to generate a diverse and inclusive sample using these methods, the sample was not intended to be representative of the population.

Of the 186 eligible participants, 21 declined participation and 26 could not be reached. The targeted sample was reached after exhausting contact for 47 veterans and contacting 80 veterans for a final response rate of 40% among fully contacted veterans and 27% among veterans with any contact. The final sample included 30 veterans who received CPT or PE in VA facilities (Table).

1025FDED-ePTSD-T1

After veterans provided verbal consent for study participation, sociodemographic information was verbally reported, and a 30- to 60-minute semistructured qualitative phone interview was recorded and transcribed. Veterans received $40 for participation. All procedures were approved by the University of California San Francisco Institutional Review Board.

Qualitative Data Analysis

Rapid analysis procedures were used to analyze qualitative data. This approach is suitable for focused, moderately structured qualitative analyses in health services research and facilitates rapid dissemination to stakeholders.23 The qualitative analysts were 2 clinical psychologists with expertise in PTSD treatment (NH primary and RR secondary). Consistent with rapid analysis procedures, analysts prepared a templated summary (including relevant quotations) of each interview, organized by the prespecified content domains. Interviews were summarized independently, compared to ensure consistency, and discrepancies were resolved through review of the interview source materials. Individual summary templates were combined into a master analytic matrix to facilitate the identification of patterns and delineation of themes. Analysts routinely met to identify, discuss, and refine preliminary themes, revisiting source materials to reach consensus as needed.

Results

Fifteen themes were identified and organized into 2 distinct focus areas: themes directly related to the transition to TF-EBP (8 themes) and themes related to veterans’ experiences with TF-EBP and general mental health care with potential process-improvement implications (7 themes).21 Seven themes were identified related to experiences with TF-EBP engagement and VA mental health care. The 7 themes related to TF-EBP engagement and VA mental health care themes are summarized with exemplary quotations.

Veterans want a better understanding of psychotherapy and engaging with VA mental health. Veterans reported that they generally had a poor or “nebulous” understanding about the experience of psychotherapy. For example, veterans exhibited confusion about whether certain experiences were equivalent to participating in psychotherapy. They were sometimes unable to distinguish between interactions such as assessment, disability evaluations, peer support, and psychotherapy. One veteran described a conversation with a TFEBP therapist about prior treatment:

She [asked], have you ever been, or gone through a therapy to begin with? And I, I said, well I just chatted with somebody. And she said that’s not, that’s not therapy. So, I was like, oh, it’s not? That’s not what people do?

Veterans were surprised the VA offered a diverse range of psychotherapy interventions, rather than simply therapy. They did not realize there were different types of psychotherapy. As a result, veterans were not aware that some VA mental practitioners have specialty training and certification to provide treatment matched to specific diagnoses or needs. They thought that all clinicians could provide the same care. One veteran described their understanding:

I just figured all mental health people are mental health people. I didn’t have a better understanding of the system and all the different levels and how it plays out and specialties and things like that. Which, I guess, I should have because you have a primary care doctor, but then you have specialists in all these other different sectors that specialize in one particular area. I guess that should’ve been common sense, but it wasn’t.

Stigma was a barrier to seeking and engaging in mental health care. Veterans discovered they had to overcome stigma associated with seeking and engaging in mental health treatment. Military culture was often discussed as promoting stigma regarding mental health treatment. Specifically, veterans described that seeking treatment meant “either, I’m weak or I’m gonna be seen as weak.” In active-duty settings, the strategy for dealing with mental health symptoms was to “leave those feelings, you push ‘em aside,” an approach highly inconsistent with TF-EBP. In some cases, incorrect information about the VA and PTSD was presented as part of discharge from the military, leading to long-term skepticism of the VA and PTSD treatment. One veteran described his experience as part of a class on the VA compensation and pension assessment process for service-connected disabilities during his military discharge:

[A fellow discharging soldier asked] what about like PTSD, gettin’ rated for PTSD. I hear they take our weapons and stuff like we can’t own firearms and all that stuff. And [the instructor] was like, well, yes that’s a thing. He didn’t explain it like if you get compensated for PTSD you don’t lose your rights to carry a firearm or to have, to be able to go hunting.

Importantly, veterans often described how other identities (eg, race, ethnicity, gender, region of origin) interacted with military culture to enhance stigma. Hearing messaging from multiple sources reinforced beliefs that mental health treatment is inappropriate or is associated with weakness:

As a first-generation Italian, I was always taught keep your feelings to yourself. Never talk outside your family. Never bring up problems to other people and stuff like that. Same with the military. And then the old stigma working in [emergency medical services] and public safety, you’re weak if you get help.

The fundamentals of therapy, including rapport and flexibility, were important. Veterans valued nonspecific therapy factors, genuine empathy, building trust, being honest about treatment, personality, and rapport. These characteristics were almost universally described as particularly important:

I liked the fact that she made it personable and she cared. It wasn’t just like, here, we’re gonna start this. She explained it in the ways I could understand, not in medical terms, so to speak, but that’s what I liked about her. She really cared about what she did and helping me.

Flexibility was viewed as an asset, particularly when clinicians acknowledged veteran autonomy. A consistent example was when veterans were able to titrate trauma disclosure. One veteran described this flexible treatment experience: “She was right there in the room, she said, you know, at any time, you know, we could stop, we could debrief.”

Experiences of clinician flexibility and personalization of therapy were contrasted with experiences of overly rigid therapy. Overemphasis on protocols created barriers, often because treatment did not feel personalized. One veteran described how a clinician’s task-oriented approach interfered with their ability to engage in TF-EBP:

They listened, but it just didn’t seem like they were listening, because they really wanted to stay on task… So, I felt like if the person was more concerned, or more sympathetic to the things that was also going on in my life at that present time, I think I would’ve felt more comfortable talking about what was the PTSD part, too.

Veterans valued shared decision-making prior to TF-EBP initiation. Veterans typically described being involved in a shared decision-making process prior to initiating TF-EBP. During these sessions, clinicians discussed treatment options and provided veterans with a variety of materials describing treatments (eg, pamphlets, websites, videos, statistics). Most veterans appreciated being able to reflect on and discuss treatment options with their clinicians. Being given time in and out of session to review was viewed as valuable and increased confidence in treatment choice. One veteran described their experience:

I was given the information, you know, they gave me handouts, PDFs, whatever was available, and let me read over it. I didn’t have to choose anything right then and there, you know, they let me sleep on it. And I got back to them after some thought.

However, some veterans felt overwhelmed by being presented with too much information and did not believe they knew enough to make a final treatment decision. One veteran described being asked to contribute to the treatment decision:

I definitely asked [the clinician] to weigh in on maybe what he thought was best, because—I mean, I don’t know… I’m not necessarily sure I know what I think is best. I think we’re just lucky I’m here, so if you can give me a solid and help me out here by telling me just based on what I’ve said to you and the things that I’ve gone through, what do you think?

Veterans who perceived that their treatment preferences were respected had a positive outlook on TF-EBP. As part of the shared-decision making process, veterans typically described being given choices among PTSD treatments. One way that preferences were respected was through clinicians tailoring treatment descriptions to a veteran’s unique symptoms, experiences, and values. In these cases, clinicians observed specific concerns and clearly linked treatment principles to those concerns. For example, one veteran described their clinician’s recommendation for PE: “The hardest thing for me is to do the normal things like grocery store or getting on a train or anything like that. And so, he suggested that [PE] would be a good idea.”

In other cases, veterans wanted the highest quality of treatment rather than a match between treatment principles and the veteran’s presentation, goals, or strengths. These veterans wanted the best treatment available for PTSD and valued research support, recommendations from clinical practice guidelines, or clinician confidence in the effectiveness of the treatment. One veteran described this perspective:

I just wanted to be able to really tackle it in the best way possible and in the most like aggressive way possible. And it seemed like PE really was going to, they said that it’s a difficult type of therapy, but I really just wanted to kind of do the best that I could to eradicate some of the issues that I was having.

When veterans perceived a lack of respect for their preferences, they were hesitant about TF-EBP. For some veterans, a generic pitch for a TF-EBP was detrimental in the absence of the personal connection between the treatment and their own symptoms, goals, or strengths. These veterans did not question whether the treatment was effective in general but did question whether the treatment was best for them. One veteran described the contrast between their clinician’s perspective and their own.

I felt like they felt very comfortable, very confident in [CPT] being the program, because it was comfortable for them. Because they did it several times. And maybe they had a lot of success with other individuals... but they were very comfortable with that one, as a provider, more than: Is this the best fit for [me]?

Some veterans perceived little concern for their preferences and a lack of choice in available treatments, which tended to perpetuate negative perceptions of TFEBP. These veterans described their lack of choices with frustration. Alternatives to TFEBP were described by these veterans as so undesirable that they did not believe they had a real choice:

[CPT] was the only decision they had. There was nothing else for PTSD. They didn’t offer anything else. So, I mean it wasn’t a decision. It was either … take treatment or don’t take treatment at all… Actually, I need to correct myself. So, there were 2 options, group therapy or CPT. I forgot about that. I’m not a big group guy so I chose the CPT.

Another veteran was offered a choice between therapeutic approaches, but all were delivered via telehealth (consistent with the transition to virtual services during the COVID-19 pandemic). For this veteran, not only was the distinction between approaches unclear, but the choice between approaches was unimportant compared to the mode of delivery.

This happened during COVID-19 and VA stopped seeing anybody physically, face-to-face. So my only option for therapy was [telehealth]… There was like 3 of them, and I tried to figure out, you know, from the layperson’s perspective, like: I don’t know which one to go with.

Veterans wanted to be asked about their cultural identity. Veterans valued when clinicians asked questions about cultural identity as part of their mental health treatment and listened to their cultural context. Cultural identity factors extended beyond factors such as race, ethnicity, gender, and sexual orientation to religion, military culture, and regionality. Veterans often described situations where they wished clinicians would ask the question or initiate conversations about culture. A veteran highlighted the importance of their faith but noted that it was a taboo topic. Their clinician did not say “we don’t go there,” but they “never dove into it either.” Another veteran expressed a desire for their clinician to ask questions about experiences in the National Guard and as an African American veteran:

If a provider was to say like: Oh, you know, it’s a stressful situation being a part of the military, being in the National Guard. You know, just asking questions about that. I think that would really go a long way… Being African American was difficult as well. And more so because of my region, I think… I felt like it would probably be an uncomfortable subject to speak on… I mean, it wasn’t anything that my providers necessarily did, it was more so just because it wasn’t brought up.

One common area of concern for veterans was a match between veteran and therapist demographics. When asked about how their cultural identity influenced treatment, several veterans described the relevance of therapist match. Much like questions about their own cultural identity, veterans valued being asked about identity preferences in clinicians (eg, gender or race matching), rather than having to bring up the preference themselves. One veteran described relief at this question being asked directly: “I was relieved when she had asked [whether I wanted a male or female clinician] primarily because I was going to ask that or bring that up somehow. But her asking that before me was a weight off my shoulders.”

Discussing cultural identity through treatment strengthened veterans’ engagement in therapy. Many veterans appreciated when analogies used in therapy were relevant to their cultural experiences and when clinicians understood their culture (eg, military culture, race, ethnicity, religious beliefs, sexual orientation). One veteran described how their clinician understood military culture and made connections between military culture and the rationale for TF-EBP, which strengthened the veteran’s buy-in for the treatment and alliance with the clinician:

At the beginning when she was explaining PTSD, and I remember she said that your brain needed to think this way when you were in the military because it was a way of protecting and surviving, so your brain was doing that in order for you to survive in whatever areas you were because there was danger. So, your brain had you thinking that way. But now, you’re not in those situations anymore. You’re not in danger. You’re not in the military, but your brain is still thinking you are, and that’s what PTSD generally does to you.

Specific elements of TF-EBP also provided opportunities to discuss and integrate important aspects of identity. This is accomplished in PE by assigning relevant in vivo exercises. In CPT, “connecting the dots” on how prior experiences influenced trauma-related stuck points achieved this element. One veteran described their experience with a clinician who was comfortable discussing the veteran’s sexual orientation and recognized the impacts of prior trauma on intimacy:

They’re very different, and there’s a lot of things that can be accepted in gay relationships that are not in straight ones. With all that said, I think [the PE therapist] did a fantastic job being not—like never once did she laugh or make an uncomfortable comment or say she didn’t wanna talk about something when like part of the reason I wanted to get into therapy is that my partner and I weren’t having sex unless I used alcohol.

Discussion

As part of a larger national qualitative investigation of the experiences of veterans who recently initiated TF-EBP, veterans discussed their experiences with therapy and mental health care that have important implications for continued process improvement.21 Three key areas for continued process improvement were identified: (1) providing information about the diverse range of mental health care services at the VA and the implications of this continuum of care; (2) consideration of veteran preferences in treatment decision-making, including the importance of perceived choice; and (3) incorporating cultural assessment and cultural responsiveness into case conceptualization and treatment.

One area of process improvement identified was increasing knowledge about different types of psychotherapy and the continuum of care available at the VA. Veterans in this study confused or conflated participating in psychotherapy with talking about mental health symptoms with a clinician (eg, assessment, disability evaluation). They were sometimes surprised that psychotherapy is an umbrella term referring to a variety of different modalities. The downstream impact of these misunderstandings was a perception of VA mental health care as nebulous. Veterans were surprised that all mental health practitioners were unable to provide the same care. Confusion may have been compounded by highly variable referral processes across VA.24 To address this, clinicians have developed local educational resources and handouts for both veterans and referring clinicians from nonmental health and general mental health specialties.25 Given the variability in referral processes both between and within VA medical centers, national dissemination of these educational materials may be more difficult compared to materials for TF-EBPs.24 The VA started to use behavioral health interdisciplinary program (BHIP) teams, which are designed to be clinical homes for veterans connected with a central clinician who can explain and coordinate their mental health care as well as bring more consistency to the referral process.26 The ongoing transition toward the BHIP model of mental health care at VA may provide the opportunity to consolidate and integrate knowledge about the VA approach to mental health care, potentially filling knowledge gaps.

A second area of process improvement focused on the shared decision-making process. Consistent with mental health initiatives, veterans generally believed they had received sufficient information about TF-EBP and engaged in shared decision-making with clinicians.20,27 Veterans were given educational materials to review and had the opportunity to discuss these materials with clinicians. However, veterans described variability in the success of shared decision-making. Although veterans valued receiving accurate, comprehensible information to support treatment decisions, some preferred to defer to clinicians’ expertise regarding which treatment to pursue. While these veterans valued information, they also valued the expertise of clinicians in explaining why specific treatments would be beneficial. A key contributor to veterans satisfaction was assessing how veterans wanted to engage in the decision-making process and respecting those preferences.28 Veterans approached shared decision-making differently, from making decisions independently after receiving information to relying solely on clinician recommendation. The process was most successful when clinicians articulated how their recommended treatment aligned with a veteran’s preferences, including recommendations based on specific values (eg, personalized match vs being the best). Another important consideration is ensuring veterans know they can receive a variety of different types of mental health services available in different modalities (eg, virtual vs in-person; group vs individual). When veterans did not perceive choice in treatment aspects important to them (typically despite having choices), they were less satisfied with their TF-EBP experience.

A final area of process improvement identified involves how therapists address important aspects of culture. Veterans often described mental health stigma coming from intersecting cultural identities and expressed appreciation when therapists helped them recognize the impact of these beliefs on treatment. Some veterans did not discuss important aspects of their identity with clinicians, including race/ethnicity, religion, and military culture. Veterans did not report negative interactions with clinicians or experiences suggesting it was inappropriate to discuss identity; however, they were reluctant to independently raise these identity factors. Strategies such as the ADDRESSING framework, a mnemonic acronym that describes a series of potentially relevant characteristics, can help clinicians comprehensively consider different aspects that may be relevant to veterans, modeling that discussion of relevant these characteristics is welcome in TF-EBP.29 Veterans reported that making culturally relevant connections enhanced the TF-EBP experience, most commonly with military culture. These data support that TF-EBP delivery with attention to culture should be an integrated part of treatment, supporting engagement and therapeutic alliance.30 The VA National Center for PTSD consultation program is a resource to support clinicians in assessing and incorporating relevant aspects of cultural identity.31 For example, the National Center for PTSD provides a guide for using case conceptualization to address patient reactions to race-based violence during PTSD treatment.32 Both manualized design and therapist certification training can reinforce that assessing and attending to case conceptualization (including identity factors) is an integral component of TF-EBP.33,34

Limitations

While the current study has numerous strengths (eg, national veteran sampling, robust qualitative methods), results should be considered within the context of study limitations. First, veteran participants all received TF-EBP, and the perspectives of veterans who never initiate TF-EBP may differ. Despite the strong sampling approach, the study design is not intended to be generalizable to all veterans receiving TF-EBP for PTSD. Qualitative analysis yielded 15 themes, described in this study and prior research, consistent with recommendations.21,22 This approach allows rich description of distinct focus areas that would not be possible in a single manuscript. Nonetheless, all veterans interviewed described their experiences in TF-EBP and general mental health care, the focus of the semistructured interview guide was on the experience of transitioning from other treatment to TF-EBP.

Conclusion

This study describes themes related to general mental health and TF-EBP process improvement as part of a larger study on transitions in PTSD care.21,22 Veterans valued the fundamentals of therapy, including rapport and flexibility. Treatment-specific rapport (eg, pointing out treatment progress and effort in completing treatment components) and flexibility within the context of fidelity (ie, personalizing treatment while maintaining core treatment elements) may be most effective at engaging veterans in recommended PTSD treatments.18,34 In addition to successes, themes suggest multiple opportunities for process improvement. Ongoing VA initiatives and priorities (ie, BHIP, shared decision-making, consultation services) aim to improve processes consistent with veteran recommendations. Future research is needed to evaluate the success of these and other programs to optimize access to and engagement in recommended PTSD treatments.

References
  1. US Department of Veterans Affairs; US Department of Defense. VA/DoD clinical practice guideline for the management of posttraumatic stress disorder and acute stress disorder. 2023. Updated August 20, 2025. Accessed October 17, 2025. https://www.healthquality.va.gov/guidelines/MH/ptsd/
  2. International Society for Traumatic Stress Studies. ISTSS PTSD prevention and treatment guidelines: methodology and recommendations. Accessed August 13, 2025. http://www.istss.org/getattachment/Treating-Trauma/New-ISTSS-Prevention-and-TreatmentGuidelines/ISTSS_PreventionTreatmentGuidelines_FNL-March-19-2019.pdf.aspx
  3. American Psychological Association. Clinical practice guideline for the treatment of posttraumatic stress disorder in adults. Accessed August 13, 2025. https://www.apa.org/ptsd-guideline/ptsd.pdf
  4. Karlin BE, Cross G. From the laboratory to the therapy room: National dissemination and implementation of evidence- based psychotherapies in the U.S. Department of Veterans Affairs Health Care System. Am Psychol. 2014;69:19-33. doi:10.1037/a0033888
  5. Rosen CS, Matthieu MM, Wiltsey Stirman S, et al. A review of studies on the system-wide implementation of evidencebased psychotherapies for posttraumatic stress disorder in the Veterans Health Administration. Adm Policy Ment Health. 2016;43:957-977. doi:10.1007/s10488-016-0755-0
  6. Maguen S, Holder N, Madden E, et al. Evidence-based psychotherapy trends among posttraumatic stress disorder patients in a national healthcare system, 2001-2014. Depress Anxiety. 2020;37:356-364. doi:10.1002/da.22983
  7. Cheney AM, Koenig CJ, Miller CJ, et al. Veteran-centered barriers to VA mental healthcare services use. BMC Health Serv Res. 2018;18:591. doi:10.1186/s12913-018-3346-9
  8. Hundt NE, Mott JM, Miles SR, et al. Veterans’ perspectives on initiating evidence-based psychotherapy for posttraumatic stress disorder. Psychol Trauma. 2015;7:539-546. doi:10.1037/tra0000035
  9. Hundt NE, Helm A, Smith TL, et al. Failure to engage: a qualitative study of veterans who decline evidence-based psychotherapies for PTSD. Psychol Serv. 2018;15:536- 542. doi:10.1037/ser0000212
  10. Sayer NA, Friedemann-Sanchez G, Spoont M, et al. A qualitative study of determinants of PTSD treatment initiation in veterans. Psychiatry. 2009;72:238-255. doi:10.1521/psyc.2009.72.3.238
  11. Mittal D, Drummond KL, Blevins D, et al. Stigma associated with PTSD: perceptions of treatment seeking combat veterans. Psychiatr Rehabil J. 2013;36:86-92. doi:10.1037/h0094976
  12. Possemato K, Wray LO, Johnson E, et al. Facilitators and barriers to seeking mental health care among primary care veterans with posttraumatic stress disorder. J Trauma Stress. 2018;31:742-752. doi:10.1002/jts.22327
  13. Silvestrini M, Chen JA. “It’s a sign of weakness”: Masculinity and help-seeking behaviors among male veterans accessing posttraumatic stress disorder care. Psychol Trauma. 2023;15:665-671. doi:10.1037/tra0001382
  14. Stecker T, Shiner B, Watts BV, et al. Treatment-seeking barriers for veterans of the Iraq and Afghanistan conflicts who screen positive for PTSD. Psychiatr Serv. 2013;64:280-283. doi:10.1176/appi.ps.001372012
  15. Etingen B, Grubbs KM, Harik JM. Drivers of preference for evidence-based PTSD treatment: a qualitative assessment. Mil Med. 2020;185:303-310. doi:10.1093/milmed/usz220
  16. Hundt NE, Ecker AH, Thompson K, et al. “It didn’t fit for me:” A qualitative examination of dropout from prolonged exposure and cognitive processing therapy in veterans. Psychol Serv. 2020;17:414-421. doi:10.1037/ser0000316
  17. Kehle-Forbes SM, Gerould H, Polusny MA, et al. “It leaves me very skeptical” messaging in marketing prolonged exposure and cognitive processing therapy to veterans with PTSD. Psychol Trauma. 2022;14:849-852. doi:10.1037/tra0000550
  18. Kehle-Forbes SM, Ackland PE, Spoont MR, et al. Divergent experiences of U.S. veterans who did and did not complete trauma-focused therapies for PTSD: a national qualitative study of treatment dropout. Behav Res Ther. 2022;154:104123. doi:10.1016/j.brat.2022.104123
  19. Hessinger JD, London MJ, Baer SM. Evaluation of a shared decision-making intervention on the utilization of evidence-based psychotherapy in a VA outpatient PTSD clinic. Psychol Serv. 2018;15:437-441. doi:10.1037/ser0000141
  20. Hamblen JL, Grubbs KM, Cole B, et al. “Will it work for me?” Developing patient-friendly graphical displays of posttraumatic stress disorder treatment effectiveness. J Trauma Stress. 2022;35:999-1010. doi:10.1002/jts.22808
  21. Holder N, Ranney RM, Delgado AK, et al. Transitioning into trauma-focused evidence-based psychotherapy for posttraumatic stress disorder from other treatments: a qualitative investigation. Cogn Behav Ther. 2025;54:391-407. doi:10.1080/16506073.2024.2408386
  22. Levitt HM, Bamberg M, Creswell JW, et al. Journal article reporting standards for qualitative primary, qualitative meta-analytic, and mixed methods research in psychology: The APA Publications and Communications Board task force report. Am Psychol. 2018;73:26-46. doi:10.1037/amp0000151
  23. Palinkas LA, Mendon SJ, Hamilton AB. Innovations in mixed methods evaluations. Annu Rev Public Health. 2019;40:423- 442. doi:10.1146/annurev-publhealth-040218-044215
  24. Ranney RM, Cordova MJ, Maguen S. A review of the referral process for evidence-based psychotherapies for PTSD among veterans. Prof Psychol Res Pr. 2022;53:276-285. doi:10.1037/pro0000463
  25. Holder N, Ranney RM, Delgado AK, et al. Transitions to trauma-focused evidence-based psychotherapy for posttraumatic stress disorder from other treatment: a qualitative investigation of clinician’s perspectives. Cogn Behav Ther. 2025;1-19. doi:10.1080/16506073.2025.2481475
  26. Barry CN, Abraham KM, Weaver KR, et al. Innovating team-based outpatient mental health care in the Veterans Health Administration: staff-perceived benefits and challenges to pilot implementation of the Behavioral Health Interdisciplinary Program (BHIP). Psychol Serv. 2016;13:148-155. doi:10.1037/ser0000072
  27. Harik JM, Hundt NE, Bernardy NC, et al. Desired involvement in treatment decisions among adults with PTSD symptoms. J Trauma Stress. 2016;29:221-228. doi:10.1002/jts.22102
  28. Larsen SE, Hooyer K, Kehle-Forbes SM, et al. Patient experiences in making PTSD treatment decisions. Psychol Serv. 2024;21:529-537. doi:10.1037/ser0000817
  29. Hays PA. Four steps toward intersectionality in psychotherapy using the ADDRESSING framework. Prof Psychol Res Pr. 2024;55:454-462. doi:10.1037/pro0000577
  30. Galovski TE, Nixon RDV, Kaysen D. Flexible Applications of Cognitive Processing Therapy: Evidence-Based Treatment Methods. Academic Press; 2020.
  31. Larsen SE, McKee T, Fielstein E, et al. The development of a posttraumatic stress disorder (PTSD) consultation program to support system-wide implementation of high-quality PTSD care for veterans. Psychol Serv. 2025;22:342-348. doi:10.1037/ser0000867
  32. Galovski T, Kaysen D, McClendon J, et al. Provider guide to addressing patient reactions to race-based violence during PTSD treatment. PTSD.va.gov. Accessed August 3, 2025. www.ptsd.va.gov/professional/treat/specific/patient_reactions_race_violence.asp
  33. Galovski TE, Nixon RDV, Kehle-Forbes S. Walking the line between fidelity and flexibility: a conceptual review of personalized approaches to manualized treatments for posttraumatic stress disorder. J Trauma Stress. 2024;37:768-774. doi:10.1002/jts.23073
  34. Galovski TE, McSweeney LB, Nixon RDV, et al. Personalizing cognitive processing therapy with a case formulation approach to intentionally target impairment in psychosocial functioning associated with PTSD. Contemp Clin Trials Commun. 2024;42:101385. doi:10.1016/j.conctc.2024.101385
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Author affiliations
aSan Francisco Veterans Affairs Health Care System, California
bUniversity of California San Francisco School of Medicine
cCenter for Data to Discovery and Delivery Innovation, San Francisco, California
dSierra Pacific Mental Illness Research, Education, and Clinical Center, Palo Alto, California
eUniversity of California San Francisco School of Nursing
fDepartment of Veterans Affairs, Washington DC
gWhite River Junction Veterans Affairs Health Care System, Vermont
hNational Center for Posttraumatic Stress Disorder, White River Junction, Vermont
iGeisel School of Medicine at Dartmouth, Hanover, New Hampshire

Correspondence: Nicholas Holder (nicholas.davis.holder@ gmail.com)

Fed Pract. 2025; November 7. Published online ahead of print. doi:10.12788/fp.0627

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aSan Francisco Veterans Affairs Health Care System, California
bUniversity of California San Francisco School of Medicine
cCenter for Data to Discovery and Delivery Innovation, San Francisco, California
dSierra Pacific Mental Illness Research, Education, and Clinical Center, Palo Alto, California
eUniversity of California San Francisco School of Nursing
fDepartment of Veterans Affairs, Washington DC
gWhite River Junction Veterans Affairs Health Care System, Vermont
hNational Center for Posttraumatic Stress Disorder, White River Junction, Vermont
iGeisel School of Medicine at Dartmouth, Hanover, New Hampshire

Correspondence: Nicholas Holder (nicholas.davis.holder@ gmail.com)

Fed Pract. 2025; November 7. Published online ahead of print. doi:10.12788/fp.0627

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Nicholas Holder, PhDa,b,c; Rachel M. Ranney, PhDa,b,c,d; Natalie Purcell, PhD, MPAc,e,f; Gayle Y. Iwamasa, PhD, HSPPg; Alejandra K. Delgado, BAa,b; Adam Batten, MS, PSTATa; Thomas C. Neylan, MDa,b,d; Brian Shiner, MD, MPHg,h,i; Shira Maguen, PhDa,b,c,d

Author affiliations
aSan Francisco Veterans Affairs Health Care System, California
bUniversity of California San Francisco School of Medicine
cCenter for Data to Discovery and Delivery Innovation, San Francisco, California
dSierra Pacific Mental Illness Research, Education, and Clinical Center, Palo Alto, California
eUniversity of California San Francisco School of Nursing
fDepartment of Veterans Affairs, Washington DC
gWhite River Junction Veterans Affairs Health Care System, Vermont
hNational Center for Posttraumatic Stress Disorder, White River Junction, Vermont
iGeisel School of Medicine at Dartmouth, Hanover, New Hampshire

Correspondence: Nicholas Holder (nicholas.davis.holder@ gmail.com)

Fed Pract. 2025; November 7. Published online ahead of print. doi:10.12788/fp.0627

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Trauma-focused evidence-based psychotherapies (TF-EBPs), including cognitive processing therapy (CPT) and prolonged exposure therapy (PE), are recommended treatments for posttraumatic stress disorder (PTSD) in clinical practice guidelines.1-3 To increase initiation of these treatments, the US Department of Veterans Affairs (VA) used a large-scale dissemination and implementation effort to improve access to TF-EBP.4,5 These efforts achieved modest success, increasing prevalence of TF-EBP from a handful of veterans in 2004 to an annual prevalence of 14.6% for CPT and 4.3% for PE in 2014.6

Throughout these efforts, qualitative studies have been used to better understand veterans’ perspectives on receiving TF-EBP care.7-18 Barriers to initiation of and engagement in TF-EBP and PTSD care have been identified from these qualitative studies. One identified barrier was lack of knowledge—particularly lack of knowledge about what is meant by a PTSD diagnosis and available treatments.7-10 Stigma (ie, automatic negative associations) toward mental health problems or seeking mental health care also has been identified as a barrier to initiation.7,10-14 Perceptions of poor alignment between treatment and veteran goals, including lack of buy-in for the rationale, served as barriers to initiation and engagement.8,15-18

Using prior qualitative work, numerous initiatives have been developed to reduce stigma, facilitate conversations about how treatment aligns with goals, and fill knowledge gaps, particularly through online resources and shared decision-making.19,20 To better inform the state of veterans’ experiences with TF-EBP, a qualitative investigation was conducted involving veterans who recently initiated TF-EBP. Themes directly related to transitions to TF-EBP were identified; however, all veterans interviewed also described their experiences with TFEBP engagement and mental health care. Consistent with recommendations for qualitative methods, this study extends prior work on transitions to TF-EBP by describing themes with a distinct focus on the experience of engaging with TF-EBP and mental health care.21,22

Methods

The experiences of veterans who were transitioning into TF-EBPs were collected in semistructured interviews and analyzed. The semistructured interview guide was developed and refined in consultation with both qualitative methods experts and PTSD treatment experts to ensure that 6 content domains were appropriately queried: PTSD treatment options, cultural sensitivity of treatment, PTSD treatment selection, transition criteria, beliefs about stabilization treatment, and treatment needs/preferences.

Participants were identified using the VA Corporate Data Warehouse and included post-9/11 veterans who had recently initiated CPT or PE for the first time between September 1, 2021, and September 1, 2022. More details of participant selection are available in Holder et al.21 From a population of 10,814 patients, stratified random sampling generated a recruitment pool of 200 veterans for further outreach. The strata were defined such that this recruitment pool had similar proportions of demographic characteristics (ie, gender, race, ethnicity) to the population of eligible veterans, equivalent distributions of time to CPT or PE initiation (ie, 33.3% < 1 year, 33.3% 1-3 years, and 33.3% > 3 years), and adequate variability in TF-EBP type (ie, 66.7% CPT, 33.3% PE). A manual chart review in the recruitment pool excluded 12 veterans who did not initiate CPT or PE, 1 veteran with evidence of current active psychosis and/or cognitive impairment that would likely preclude comprehension of study materials, and 1 who was deceased.

Eligible veterans from the recruitment pool were contacted in groups of 25. First, a recruitment letter with study information and instructions to opt-out of further contact was mailed or emailed to veterans. After 2 weeks, veterans who had not responded were contacted by phone up to 3 times. Veterans interested in participating were scheduled for a 1-time visit that included verbal consent and the qualitative interview. Metrics were established a priori to ensure an adequately diverse and inclusive sample. Specifically, a minimum number of racial and/or ethnic minority veterans (33%) and women veterans (20%) were sought. Equal distribution across the 3 categories of time from first mental health visit to CPT/PE initiation also was targeted. Throughout enrollment, recruitment efforts were adapted to meet these metrics in the emerging sample. While the goal was to generate a diverse and inclusive sample using these methods, the sample was not intended to be representative of the population.

Of the 186 eligible participants, 21 declined participation and 26 could not be reached. The targeted sample was reached after exhausting contact for 47 veterans and contacting 80 veterans for a final response rate of 40% among fully contacted veterans and 27% among veterans with any contact. The final sample included 30 veterans who received CPT or PE in VA facilities (Table).

1025FDED-ePTSD-T1

After veterans provided verbal consent for study participation, sociodemographic information was verbally reported, and a 30- to 60-minute semistructured qualitative phone interview was recorded and transcribed. Veterans received $40 for participation. All procedures were approved by the University of California San Francisco Institutional Review Board.

Qualitative Data Analysis

Rapid analysis procedures were used to analyze qualitative data. This approach is suitable for focused, moderately structured qualitative analyses in health services research and facilitates rapid dissemination to stakeholders.23 The qualitative analysts were 2 clinical psychologists with expertise in PTSD treatment (NH primary and RR secondary). Consistent with rapid analysis procedures, analysts prepared a templated summary (including relevant quotations) of each interview, organized by the prespecified content domains. Interviews were summarized independently, compared to ensure consistency, and discrepancies were resolved through review of the interview source materials. Individual summary templates were combined into a master analytic matrix to facilitate the identification of patterns and delineation of themes. Analysts routinely met to identify, discuss, and refine preliminary themes, revisiting source materials to reach consensus as needed.

Results

Fifteen themes were identified and organized into 2 distinct focus areas: themes directly related to the transition to TF-EBP (8 themes) and themes related to veterans’ experiences with TF-EBP and general mental health care with potential process-improvement implications (7 themes).21 Seven themes were identified related to experiences with TF-EBP engagement and VA mental health care. The 7 themes related to TF-EBP engagement and VA mental health care themes are summarized with exemplary quotations.

Veterans want a better understanding of psychotherapy and engaging with VA mental health. Veterans reported that they generally had a poor or “nebulous” understanding about the experience of psychotherapy. For example, veterans exhibited confusion about whether certain experiences were equivalent to participating in psychotherapy. They were sometimes unable to distinguish between interactions such as assessment, disability evaluations, peer support, and psychotherapy. One veteran described a conversation with a TFEBP therapist about prior treatment:

She [asked], have you ever been, or gone through a therapy to begin with? And I, I said, well I just chatted with somebody. And she said that’s not, that’s not therapy. So, I was like, oh, it’s not? That’s not what people do?

Veterans were surprised the VA offered a diverse range of psychotherapy interventions, rather than simply therapy. They did not realize there were different types of psychotherapy. As a result, veterans were not aware that some VA mental practitioners have specialty training and certification to provide treatment matched to specific diagnoses or needs. They thought that all clinicians could provide the same care. One veteran described their understanding:

I just figured all mental health people are mental health people. I didn’t have a better understanding of the system and all the different levels and how it plays out and specialties and things like that. Which, I guess, I should have because you have a primary care doctor, but then you have specialists in all these other different sectors that specialize in one particular area. I guess that should’ve been common sense, but it wasn’t.

Stigma was a barrier to seeking and engaging in mental health care. Veterans discovered they had to overcome stigma associated with seeking and engaging in mental health treatment. Military culture was often discussed as promoting stigma regarding mental health treatment. Specifically, veterans described that seeking treatment meant “either, I’m weak or I’m gonna be seen as weak.” In active-duty settings, the strategy for dealing with mental health symptoms was to “leave those feelings, you push ‘em aside,” an approach highly inconsistent with TF-EBP. In some cases, incorrect information about the VA and PTSD was presented as part of discharge from the military, leading to long-term skepticism of the VA and PTSD treatment. One veteran described his experience as part of a class on the VA compensation and pension assessment process for service-connected disabilities during his military discharge:

[A fellow discharging soldier asked] what about like PTSD, gettin’ rated for PTSD. I hear they take our weapons and stuff like we can’t own firearms and all that stuff. And [the instructor] was like, well, yes that’s a thing. He didn’t explain it like if you get compensated for PTSD you don’t lose your rights to carry a firearm or to have, to be able to go hunting.

Importantly, veterans often described how other identities (eg, race, ethnicity, gender, region of origin) interacted with military culture to enhance stigma. Hearing messaging from multiple sources reinforced beliefs that mental health treatment is inappropriate or is associated with weakness:

As a first-generation Italian, I was always taught keep your feelings to yourself. Never talk outside your family. Never bring up problems to other people and stuff like that. Same with the military. And then the old stigma working in [emergency medical services] and public safety, you’re weak if you get help.

The fundamentals of therapy, including rapport and flexibility, were important. Veterans valued nonspecific therapy factors, genuine empathy, building trust, being honest about treatment, personality, and rapport. These characteristics were almost universally described as particularly important:

I liked the fact that she made it personable and she cared. It wasn’t just like, here, we’re gonna start this. She explained it in the ways I could understand, not in medical terms, so to speak, but that’s what I liked about her. She really cared about what she did and helping me.

Flexibility was viewed as an asset, particularly when clinicians acknowledged veteran autonomy. A consistent example was when veterans were able to titrate trauma disclosure. One veteran described this flexible treatment experience: “She was right there in the room, she said, you know, at any time, you know, we could stop, we could debrief.”

Experiences of clinician flexibility and personalization of therapy were contrasted with experiences of overly rigid therapy. Overemphasis on protocols created barriers, often because treatment did not feel personalized. One veteran described how a clinician’s task-oriented approach interfered with their ability to engage in TF-EBP:

They listened, but it just didn’t seem like they were listening, because they really wanted to stay on task… So, I felt like if the person was more concerned, or more sympathetic to the things that was also going on in my life at that present time, I think I would’ve felt more comfortable talking about what was the PTSD part, too.

Veterans valued shared decision-making prior to TF-EBP initiation. Veterans typically described being involved in a shared decision-making process prior to initiating TF-EBP. During these sessions, clinicians discussed treatment options and provided veterans with a variety of materials describing treatments (eg, pamphlets, websites, videos, statistics). Most veterans appreciated being able to reflect on and discuss treatment options with their clinicians. Being given time in and out of session to review was viewed as valuable and increased confidence in treatment choice. One veteran described their experience:

I was given the information, you know, they gave me handouts, PDFs, whatever was available, and let me read over it. I didn’t have to choose anything right then and there, you know, they let me sleep on it. And I got back to them after some thought.

However, some veterans felt overwhelmed by being presented with too much information and did not believe they knew enough to make a final treatment decision. One veteran described being asked to contribute to the treatment decision:

I definitely asked [the clinician] to weigh in on maybe what he thought was best, because—I mean, I don’t know… I’m not necessarily sure I know what I think is best. I think we’re just lucky I’m here, so if you can give me a solid and help me out here by telling me just based on what I’ve said to you and the things that I’ve gone through, what do you think?

Veterans who perceived that their treatment preferences were respected had a positive outlook on TF-EBP. As part of the shared-decision making process, veterans typically described being given choices among PTSD treatments. One way that preferences were respected was through clinicians tailoring treatment descriptions to a veteran’s unique symptoms, experiences, and values. In these cases, clinicians observed specific concerns and clearly linked treatment principles to those concerns. For example, one veteran described their clinician’s recommendation for PE: “The hardest thing for me is to do the normal things like grocery store or getting on a train or anything like that. And so, he suggested that [PE] would be a good idea.”

In other cases, veterans wanted the highest quality of treatment rather than a match between treatment principles and the veteran’s presentation, goals, or strengths. These veterans wanted the best treatment available for PTSD and valued research support, recommendations from clinical practice guidelines, or clinician confidence in the effectiveness of the treatment. One veteran described this perspective:

I just wanted to be able to really tackle it in the best way possible and in the most like aggressive way possible. And it seemed like PE really was going to, they said that it’s a difficult type of therapy, but I really just wanted to kind of do the best that I could to eradicate some of the issues that I was having.

When veterans perceived a lack of respect for their preferences, they were hesitant about TF-EBP. For some veterans, a generic pitch for a TF-EBP was detrimental in the absence of the personal connection between the treatment and their own symptoms, goals, or strengths. These veterans did not question whether the treatment was effective in general but did question whether the treatment was best for them. One veteran described the contrast between their clinician’s perspective and their own.

I felt like they felt very comfortable, very confident in [CPT] being the program, because it was comfortable for them. Because they did it several times. And maybe they had a lot of success with other individuals... but they were very comfortable with that one, as a provider, more than: Is this the best fit for [me]?

Some veterans perceived little concern for their preferences and a lack of choice in available treatments, which tended to perpetuate negative perceptions of TFEBP. These veterans described their lack of choices with frustration. Alternatives to TFEBP were described by these veterans as so undesirable that they did not believe they had a real choice:

[CPT] was the only decision they had. There was nothing else for PTSD. They didn’t offer anything else. So, I mean it wasn’t a decision. It was either … take treatment or don’t take treatment at all… Actually, I need to correct myself. So, there were 2 options, group therapy or CPT. I forgot about that. I’m not a big group guy so I chose the CPT.

Another veteran was offered a choice between therapeutic approaches, but all were delivered via telehealth (consistent with the transition to virtual services during the COVID-19 pandemic). For this veteran, not only was the distinction between approaches unclear, but the choice between approaches was unimportant compared to the mode of delivery.

This happened during COVID-19 and VA stopped seeing anybody physically, face-to-face. So my only option for therapy was [telehealth]… There was like 3 of them, and I tried to figure out, you know, from the layperson’s perspective, like: I don’t know which one to go with.

Veterans wanted to be asked about their cultural identity. Veterans valued when clinicians asked questions about cultural identity as part of their mental health treatment and listened to their cultural context. Cultural identity factors extended beyond factors such as race, ethnicity, gender, and sexual orientation to religion, military culture, and regionality. Veterans often described situations where they wished clinicians would ask the question or initiate conversations about culture. A veteran highlighted the importance of their faith but noted that it was a taboo topic. Their clinician did not say “we don’t go there,” but they “never dove into it either.” Another veteran expressed a desire for their clinician to ask questions about experiences in the National Guard and as an African American veteran:

If a provider was to say like: Oh, you know, it’s a stressful situation being a part of the military, being in the National Guard. You know, just asking questions about that. I think that would really go a long way… Being African American was difficult as well. And more so because of my region, I think… I felt like it would probably be an uncomfortable subject to speak on… I mean, it wasn’t anything that my providers necessarily did, it was more so just because it wasn’t brought up.

One common area of concern for veterans was a match between veteran and therapist demographics. When asked about how their cultural identity influenced treatment, several veterans described the relevance of therapist match. Much like questions about their own cultural identity, veterans valued being asked about identity preferences in clinicians (eg, gender or race matching), rather than having to bring up the preference themselves. One veteran described relief at this question being asked directly: “I was relieved when she had asked [whether I wanted a male or female clinician] primarily because I was going to ask that or bring that up somehow. But her asking that before me was a weight off my shoulders.”

Discussing cultural identity through treatment strengthened veterans’ engagement in therapy. Many veterans appreciated when analogies used in therapy were relevant to their cultural experiences and when clinicians understood their culture (eg, military culture, race, ethnicity, religious beliefs, sexual orientation). One veteran described how their clinician understood military culture and made connections between military culture and the rationale for TF-EBP, which strengthened the veteran’s buy-in for the treatment and alliance with the clinician:

At the beginning when she was explaining PTSD, and I remember she said that your brain needed to think this way when you were in the military because it was a way of protecting and surviving, so your brain was doing that in order for you to survive in whatever areas you were because there was danger. So, your brain had you thinking that way. But now, you’re not in those situations anymore. You’re not in danger. You’re not in the military, but your brain is still thinking you are, and that’s what PTSD generally does to you.

Specific elements of TF-EBP also provided opportunities to discuss and integrate important aspects of identity. This is accomplished in PE by assigning relevant in vivo exercises. In CPT, “connecting the dots” on how prior experiences influenced trauma-related stuck points achieved this element. One veteran described their experience with a clinician who was comfortable discussing the veteran’s sexual orientation and recognized the impacts of prior trauma on intimacy:

They’re very different, and there’s a lot of things that can be accepted in gay relationships that are not in straight ones. With all that said, I think [the PE therapist] did a fantastic job being not—like never once did she laugh or make an uncomfortable comment or say she didn’t wanna talk about something when like part of the reason I wanted to get into therapy is that my partner and I weren’t having sex unless I used alcohol.

Discussion

As part of a larger national qualitative investigation of the experiences of veterans who recently initiated TF-EBP, veterans discussed their experiences with therapy and mental health care that have important implications for continued process improvement.21 Three key areas for continued process improvement were identified: (1) providing information about the diverse range of mental health care services at the VA and the implications of this continuum of care; (2) consideration of veteran preferences in treatment decision-making, including the importance of perceived choice; and (3) incorporating cultural assessment and cultural responsiveness into case conceptualization and treatment.

One area of process improvement identified was increasing knowledge about different types of psychotherapy and the continuum of care available at the VA. Veterans in this study confused or conflated participating in psychotherapy with talking about mental health symptoms with a clinician (eg, assessment, disability evaluation). They were sometimes surprised that psychotherapy is an umbrella term referring to a variety of different modalities. The downstream impact of these misunderstandings was a perception of VA mental health care as nebulous. Veterans were surprised that all mental health practitioners were unable to provide the same care. Confusion may have been compounded by highly variable referral processes across VA.24 To address this, clinicians have developed local educational resources and handouts for both veterans and referring clinicians from nonmental health and general mental health specialties.25 Given the variability in referral processes both between and within VA medical centers, national dissemination of these educational materials may be more difficult compared to materials for TF-EBPs.24 The VA started to use behavioral health interdisciplinary program (BHIP) teams, which are designed to be clinical homes for veterans connected with a central clinician who can explain and coordinate their mental health care as well as bring more consistency to the referral process.26 The ongoing transition toward the BHIP model of mental health care at VA may provide the opportunity to consolidate and integrate knowledge about the VA approach to mental health care, potentially filling knowledge gaps.

A second area of process improvement focused on the shared decision-making process. Consistent with mental health initiatives, veterans generally believed they had received sufficient information about TF-EBP and engaged in shared decision-making with clinicians.20,27 Veterans were given educational materials to review and had the opportunity to discuss these materials with clinicians. However, veterans described variability in the success of shared decision-making. Although veterans valued receiving accurate, comprehensible information to support treatment decisions, some preferred to defer to clinicians’ expertise regarding which treatment to pursue. While these veterans valued information, they also valued the expertise of clinicians in explaining why specific treatments would be beneficial. A key contributor to veterans satisfaction was assessing how veterans wanted to engage in the decision-making process and respecting those preferences.28 Veterans approached shared decision-making differently, from making decisions independently after receiving information to relying solely on clinician recommendation. The process was most successful when clinicians articulated how their recommended treatment aligned with a veteran’s preferences, including recommendations based on specific values (eg, personalized match vs being the best). Another important consideration is ensuring veterans know they can receive a variety of different types of mental health services available in different modalities (eg, virtual vs in-person; group vs individual). When veterans did not perceive choice in treatment aspects important to them (typically despite having choices), they were less satisfied with their TF-EBP experience.

A final area of process improvement identified involves how therapists address important aspects of culture. Veterans often described mental health stigma coming from intersecting cultural identities and expressed appreciation when therapists helped them recognize the impact of these beliefs on treatment. Some veterans did not discuss important aspects of their identity with clinicians, including race/ethnicity, religion, and military culture. Veterans did not report negative interactions with clinicians or experiences suggesting it was inappropriate to discuss identity; however, they were reluctant to independently raise these identity factors. Strategies such as the ADDRESSING framework, a mnemonic acronym that describes a series of potentially relevant characteristics, can help clinicians comprehensively consider different aspects that may be relevant to veterans, modeling that discussion of relevant these characteristics is welcome in TF-EBP.29 Veterans reported that making culturally relevant connections enhanced the TF-EBP experience, most commonly with military culture. These data support that TF-EBP delivery with attention to culture should be an integrated part of treatment, supporting engagement and therapeutic alliance.30 The VA National Center for PTSD consultation program is a resource to support clinicians in assessing and incorporating relevant aspects of cultural identity.31 For example, the National Center for PTSD provides a guide for using case conceptualization to address patient reactions to race-based violence during PTSD treatment.32 Both manualized design and therapist certification training can reinforce that assessing and attending to case conceptualization (including identity factors) is an integral component of TF-EBP.33,34

Limitations

While the current study has numerous strengths (eg, national veteran sampling, robust qualitative methods), results should be considered within the context of study limitations. First, veteran participants all received TF-EBP, and the perspectives of veterans who never initiate TF-EBP may differ. Despite the strong sampling approach, the study design is not intended to be generalizable to all veterans receiving TF-EBP for PTSD. Qualitative analysis yielded 15 themes, described in this study and prior research, consistent with recommendations.21,22 This approach allows rich description of distinct focus areas that would not be possible in a single manuscript. Nonetheless, all veterans interviewed described their experiences in TF-EBP and general mental health care, the focus of the semistructured interview guide was on the experience of transitioning from other treatment to TF-EBP.

Conclusion

This study describes themes related to general mental health and TF-EBP process improvement as part of a larger study on transitions in PTSD care.21,22 Veterans valued the fundamentals of therapy, including rapport and flexibility. Treatment-specific rapport (eg, pointing out treatment progress and effort in completing treatment components) and flexibility within the context of fidelity (ie, personalizing treatment while maintaining core treatment elements) may be most effective at engaging veterans in recommended PTSD treatments.18,34 In addition to successes, themes suggest multiple opportunities for process improvement. Ongoing VA initiatives and priorities (ie, BHIP, shared decision-making, consultation services) aim to improve processes consistent with veteran recommendations. Future research is needed to evaluate the success of these and other programs to optimize access to and engagement in recommended PTSD treatments.

Trauma-focused evidence-based psychotherapies (TF-EBPs), including cognitive processing therapy (CPT) and prolonged exposure therapy (PE), are recommended treatments for posttraumatic stress disorder (PTSD) in clinical practice guidelines.1-3 To increase initiation of these treatments, the US Department of Veterans Affairs (VA) used a large-scale dissemination and implementation effort to improve access to TF-EBP.4,5 These efforts achieved modest success, increasing prevalence of TF-EBP from a handful of veterans in 2004 to an annual prevalence of 14.6% for CPT and 4.3% for PE in 2014.6

Throughout these efforts, qualitative studies have been used to better understand veterans’ perspectives on receiving TF-EBP care.7-18 Barriers to initiation of and engagement in TF-EBP and PTSD care have been identified from these qualitative studies. One identified barrier was lack of knowledge—particularly lack of knowledge about what is meant by a PTSD diagnosis and available treatments.7-10 Stigma (ie, automatic negative associations) toward mental health problems or seeking mental health care also has been identified as a barrier to initiation.7,10-14 Perceptions of poor alignment between treatment and veteran goals, including lack of buy-in for the rationale, served as barriers to initiation and engagement.8,15-18

Using prior qualitative work, numerous initiatives have been developed to reduce stigma, facilitate conversations about how treatment aligns with goals, and fill knowledge gaps, particularly through online resources and shared decision-making.19,20 To better inform the state of veterans’ experiences with TF-EBP, a qualitative investigation was conducted involving veterans who recently initiated TF-EBP. Themes directly related to transitions to TF-EBP were identified; however, all veterans interviewed also described their experiences with TFEBP engagement and mental health care. Consistent with recommendations for qualitative methods, this study extends prior work on transitions to TF-EBP by describing themes with a distinct focus on the experience of engaging with TF-EBP and mental health care.21,22

Methods

The experiences of veterans who were transitioning into TF-EBPs were collected in semistructured interviews and analyzed. The semistructured interview guide was developed and refined in consultation with both qualitative methods experts and PTSD treatment experts to ensure that 6 content domains were appropriately queried: PTSD treatment options, cultural sensitivity of treatment, PTSD treatment selection, transition criteria, beliefs about stabilization treatment, and treatment needs/preferences.

Participants were identified using the VA Corporate Data Warehouse and included post-9/11 veterans who had recently initiated CPT or PE for the first time between September 1, 2021, and September 1, 2022. More details of participant selection are available in Holder et al.21 From a population of 10,814 patients, stratified random sampling generated a recruitment pool of 200 veterans for further outreach. The strata were defined such that this recruitment pool had similar proportions of demographic characteristics (ie, gender, race, ethnicity) to the population of eligible veterans, equivalent distributions of time to CPT or PE initiation (ie, 33.3% < 1 year, 33.3% 1-3 years, and 33.3% > 3 years), and adequate variability in TF-EBP type (ie, 66.7% CPT, 33.3% PE). A manual chart review in the recruitment pool excluded 12 veterans who did not initiate CPT or PE, 1 veteran with evidence of current active psychosis and/or cognitive impairment that would likely preclude comprehension of study materials, and 1 who was deceased.

Eligible veterans from the recruitment pool were contacted in groups of 25. First, a recruitment letter with study information and instructions to opt-out of further contact was mailed or emailed to veterans. After 2 weeks, veterans who had not responded were contacted by phone up to 3 times. Veterans interested in participating were scheduled for a 1-time visit that included verbal consent and the qualitative interview. Metrics were established a priori to ensure an adequately diverse and inclusive sample. Specifically, a minimum number of racial and/or ethnic minority veterans (33%) and women veterans (20%) were sought. Equal distribution across the 3 categories of time from first mental health visit to CPT/PE initiation also was targeted. Throughout enrollment, recruitment efforts were adapted to meet these metrics in the emerging sample. While the goal was to generate a diverse and inclusive sample using these methods, the sample was not intended to be representative of the population.

Of the 186 eligible participants, 21 declined participation and 26 could not be reached. The targeted sample was reached after exhausting contact for 47 veterans and contacting 80 veterans for a final response rate of 40% among fully contacted veterans and 27% among veterans with any contact. The final sample included 30 veterans who received CPT or PE in VA facilities (Table).

1025FDED-ePTSD-T1

After veterans provided verbal consent for study participation, sociodemographic information was verbally reported, and a 30- to 60-minute semistructured qualitative phone interview was recorded and transcribed. Veterans received $40 for participation. All procedures were approved by the University of California San Francisco Institutional Review Board.

Qualitative Data Analysis

Rapid analysis procedures were used to analyze qualitative data. This approach is suitable for focused, moderately structured qualitative analyses in health services research and facilitates rapid dissemination to stakeholders.23 The qualitative analysts were 2 clinical psychologists with expertise in PTSD treatment (NH primary and RR secondary). Consistent with rapid analysis procedures, analysts prepared a templated summary (including relevant quotations) of each interview, organized by the prespecified content domains. Interviews were summarized independently, compared to ensure consistency, and discrepancies were resolved through review of the interview source materials. Individual summary templates were combined into a master analytic matrix to facilitate the identification of patterns and delineation of themes. Analysts routinely met to identify, discuss, and refine preliminary themes, revisiting source materials to reach consensus as needed.

Results

Fifteen themes were identified and organized into 2 distinct focus areas: themes directly related to the transition to TF-EBP (8 themes) and themes related to veterans’ experiences with TF-EBP and general mental health care with potential process-improvement implications (7 themes).21 Seven themes were identified related to experiences with TF-EBP engagement and VA mental health care. The 7 themes related to TF-EBP engagement and VA mental health care themes are summarized with exemplary quotations.

Veterans want a better understanding of psychotherapy and engaging with VA mental health. Veterans reported that they generally had a poor or “nebulous” understanding about the experience of psychotherapy. For example, veterans exhibited confusion about whether certain experiences were equivalent to participating in psychotherapy. They were sometimes unable to distinguish between interactions such as assessment, disability evaluations, peer support, and psychotherapy. One veteran described a conversation with a TFEBP therapist about prior treatment:

She [asked], have you ever been, or gone through a therapy to begin with? And I, I said, well I just chatted with somebody. And she said that’s not, that’s not therapy. So, I was like, oh, it’s not? That’s not what people do?

Veterans were surprised the VA offered a diverse range of psychotherapy interventions, rather than simply therapy. They did not realize there were different types of psychotherapy. As a result, veterans were not aware that some VA mental practitioners have specialty training and certification to provide treatment matched to specific diagnoses or needs. They thought that all clinicians could provide the same care. One veteran described their understanding:

I just figured all mental health people are mental health people. I didn’t have a better understanding of the system and all the different levels and how it plays out and specialties and things like that. Which, I guess, I should have because you have a primary care doctor, but then you have specialists in all these other different sectors that specialize in one particular area. I guess that should’ve been common sense, but it wasn’t.

Stigma was a barrier to seeking and engaging in mental health care. Veterans discovered they had to overcome stigma associated with seeking and engaging in mental health treatment. Military culture was often discussed as promoting stigma regarding mental health treatment. Specifically, veterans described that seeking treatment meant “either, I’m weak or I’m gonna be seen as weak.” In active-duty settings, the strategy for dealing with mental health symptoms was to “leave those feelings, you push ‘em aside,” an approach highly inconsistent with TF-EBP. In some cases, incorrect information about the VA and PTSD was presented as part of discharge from the military, leading to long-term skepticism of the VA and PTSD treatment. One veteran described his experience as part of a class on the VA compensation and pension assessment process for service-connected disabilities during his military discharge:

[A fellow discharging soldier asked] what about like PTSD, gettin’ rated for PTSD. I hear they take our weapons and stuff like we can’t own firearms and all that stuff. And [the instructor] was like, well, yes that’s a thing. He didn’t explain it like if you get compensated for PTSD you don’t lose your rights to carry a firearm or to have, to be able to go hunting.

Importantly, veterans often described how other identities (eg, race, ethnicity, gender, region of origin) interacted with military culture to enhance stigma. Hearing messaging from multiple sources reinforced beliefs that mental health treatment is inappropriate or is associated with weakness:

As a first-generation Italian, I was always taught keep your feelings to yourself. Never talk outside your family. Never bring up problems to other people and stuff like that. Same with the military. And then the old stigma working in [emergency medical services] and public safety, you’re weak if you get help.

The fundamentals of therapy, including rapport and flexibility, were important. Veterans valued nonspecific therapy factors, genuine empathy, building trust, being honest about treatment, personality, and rapport. These characteristics were almost universally described as particularly important:

I liked the fact that she made it personable and she cared. It wasn’t just like, here, we’re gonna start this. She explained it in the ways I could understand, not in medical terms, so to speak, but that’s what I liked about her. She really cared about what she did and helping me.

Flexibility was viewed as an asset, particularly when clinicians acknowledged veteran autonomy. A consistent example was when veterans were able to titrate trauma disclosure. One veteran described this flexible treatment experience: “She was right there in the room, she said, you know, at any time, you know, we could stop, we could debrief.”

Experiences of clinician flexibility and personalization of therapy were contrasted with experiences of overly rigid therapy. Overemphasis on protocols created barriers, often because treatment did not feel personalized. One veteran described how a clinician’s task-oriented approach interfered with their ability to engage in TF-EBP:

They listened, but it just didn’t seem like they were listening, because they really wanted to stay on task… So, I felt like if the person was more concerned, or more sympathetic to the things that was also going on in my life at that present time, I think I would’ve felt more comfortable talking about what was the PTSD part, too.

Veterans valued shared decision-making prior to TF-EBP initiation. Veterans typically described being involved in a shared decision-making process prior to initiating TF-EBP. During these sessions, clinicians discussed treatment options and provided veterans with a variety of materials describing treatments (eg, pamphlets, websites, videos, statistics). Most veterans appreciated being able to reflect on and discuss treatment options with their clinicians. Being given time in and out of session to review was viewed as valuable and increased confidence in treatment choice. One veteran described their experience:

I was given the information, you know, they gave me handouts, PDFs, whatever was available, and let me read over it. I didn’t have to choose anything right then and there, you know, they let me sleep on it. And I got back to them after some thought.

However, some veterans felt overwhelmed by being presented with too much information and did not believe they knew enough to make a final treatment decision. One veteran described being asked to contribute to the treatment decision:

I definitely asked [the clinician] to weigh in on maybe what he thought was best, because—I mean, I don’t know… I’m not necessarily sure I know what I think is best. I think we’re just lucky I’m here, so if you can give me a solid and help me out here by telling me just based on what I’ve said to you and the things that I’ve gone through, what do you think?

Veterans who perceived that their treatment preferences were respected had a positive outlook on TF-EBP. As part of the shared-decision making process, veterans typically described being given choices among PTSD treatments. One way that preferences were respected was through clinicians tailoring treatment descriptions to a veteran’s unique symptoms, experiences, and values. In these cases, clinicians observed specific concerns and clearly linked treatment principles to those concerns. For example, one veteran described their clinician’s recommendation for PE: “The hardest thing for me is to do the normal things like grocery store or getting on a train or anything like that. And so, he suggested that [PE] would be a good idea.”

In other cases, veterans wanted the highest quality of treatment rather than a match between treatment principles and the veteran’s presentation, goals, or strengths. These veterans wanted the best treatment available for PTSD and valued research support, recommendations from clinical practice guidelines, or clinician confidence in the effectiveness of the treatment. One veteran described this perspective:

I just wanted to be able to really tackle it in the best way possible and in the most like aggressive way possible. And it seemed like PE really was going to, they said that it’s a difficult type of therapy, but I really just wanted to kind of do the best that I could to eradicate some of the issues that I was having.

When veterans perceived a lack of respect for their preferences, they were hesitant about TF-EBP. For some veterans, a generic pitch for a TF-EBP was detrimental in the absence of the personal connection between the treatment and their own symptoms, goals, or strengths. These veterans did not question whether the treatment was effective in general but did question whether the treatment was best for them. One veteran described the contrast between their clinician’s perspective and their own.

I felt like they felt very comfortable, very confident in [CPT] being the program, because it was comfortable for them. Because they did it several times. And maybe they had a lot of success with other individuals... but they were very comfortable with that one, as a provider, more than: Is this the best fit for [me]?

Some veterans perceived little concern for their preferences and a lack of choice in available treatments, which tended to perpetuate negative perceptions of TFEBP. These veterans described their lack of choices with frustration. Alternatives to TFEBP were described by these veterans as so undesirable that they did not believe they had a real choice:

[CPT] was the only decision they had. There was nothing else for PTSD. They didn’t offer anything else. So, I mean it wasn’t a decision. It was either … take treatment or don’t take treatment at all… Actually, I need to correct myself. So, there were 2 options, group therapy or CPT. I forgot about that. I’m not a big group guy so I chose the CPT.

Another veteran was offered a choice between therapeutic approaches, but all were delivered via telehealth (consistent with the transition to virtual services during the COVID-19 pandemic). For this veteran, not only was the distinction between approaches unclear, but the choice between approaches was unimportant compared to the mode of delivery.

This happened during COVID-19 and VA stopped seeing anybody physically, face-to-face. So my only option for therapy was [telehealth]… There was like 3 of them, and I tried to figure out, you know, from the layperson’s perspective, like: I don’t know which one to go with.

Veterans wanted to be asked about their cultural identity. Veterans valued when clinicians asked questions about cultural identity as part of their mental health treatment and listened to their cultural context. Cultural identity factors extended beyond factors such as race, ethnicity, gender, and sexual orientation to religion, military culture, and regionality. Veterans often described situations where they wished clinicians would ask the question or initiate conversations about culture. A veteran highlighted the importance of their faith but noted that it was a taboo topic. Their clinician did not say “we don’t go there,” but they “never dove into it either.” Another veteran expressed a desire for their clinician to ask questions about experiences in the National Guard and as an African American veteran:

If a provider was to say like: Oh, you know, it’s a stressful situation being a part of the military, being in the National Guard. You know, just asking questions about that. I think that would really go a long way… Being African American was difficult as well. And more so because of my region, I think… I felt like it would probably be an uncomfortable subject to speak on… I mean, it wasn’t anything that my providers necessarily did, it was more so just because it wasn’t brought up.

One common area of concern for veterans was a match between veteran and therapist demographics. When asked about how their cultural identity influenced treatment, several veterans described the relevance of therapist match. Much like questions about their own cultural identity, veterans valued being asked about identity preferences in clinicians (eg, gender or race matching), rather than having to bring up the preference themselves. One veteran described relief at this question being asked directly: “I was relieved when she had asked [whether I wanted a male or female clinician] primarily because I was going to ask that or bring that up somehow. But her asking that before me was a weight off my shoulders.”

Discussing cultural identity through treatment strengthened veterans’ engagement in therapy. Many veterans appreciated when analogies used in therapy were relevant to their cultural experiences and when clinicians understood their culture (eg, military culture, race, ethnicity, religious beliefs, sexual orientation). One veteran described how their clinician understood military culture and made connections between military culture and the rationale for TF-EBP, which strengthened the veteran’s buy-in for the treatment and alliance with the clinician:

At the beginning when she was explaining PTSD, and I remember she said that your brain needed to think this way when you were in the military because it was a way of protecting and surviving, so your brain was doing that in order for you to survive in whatever areas you were because there was danger. So, your brain had you thinking that way. But now, you’re not in those situations anymore. You’re not in danger. You’re not in the military, but your brain is still thinking you are, and that’s what PTSD generally does to you.

Specific elements of TF-EBP also provided opportunities to discuss and integrate important aspects of identity. This is accomplished in PE by assigning relevant in vivo exercises. In CPT, “connecting the dots” on how prior experiences influenced trauma-related stuck points achieved this element. One veteran described their experience with a clinician who was comfortable discussing the veteran’s sexual orientation and recognized the impacts of prior trauma on intimacy:

They’re very different, and there’s a lot of things that can be accepted in gay relationships that are not in straight ones. With all that said, I think [the PE therapist] did a fantastic job being not—like never once did she laugh or make an uncomfortable comment or say she didn’t wanna talk about something when like part of the reason I wanted to get into therapy is that my partner and I weren’t having sex unless I used alcohol.

Discussion

As part of a larger national qualitative investigation of the experiences of veterans who recently initiated TF-EBP, veterans discussed their experiences with therapy and mental health care that have important implications for continued process improvement.21 Three key areas for continued process improvement were identified: (1) providing information about the diverse range of mental health care services at the VA and the implications of this continuum of care; (2) consideration of veteran preferences in treatment decision-making, including the importance of perceived choice; and (3) incorporating cultural assessment and cultural responsiveness into case conceptualization and treatment.

One area of process improvement identified was increasing knowledge about different types of psychotherapy and the continuum of care available at the VA. Veterans in this study confused or conflated participating in psychotherapy with talking about mental health symptoms with a clinician (eg, assessment, disability evaluation). They were sometimes surprised that psychotherapy is an umbrella term referring to a variety of different modalities. The downstream impact of these misunderstandings was a perception of VA mental health care as nebulous. Veterans were surprised that all mental health practitioners were unable to provide the same care. Confusion may have been compounded by highly variable referral processes across VA.24 To address this, clinicians have developed local educational resources and handouts for both veterans and referring clinicians from nonmental health and general mental health specialties.25 Given the variability in referral processes both between and within VA medical centers, national dissemination of these educational materials may be more difficult compared to materials for TF-EBPs.24 The VA started to use behavioral health interdisciplinary program (BHIP) teams, which are designed to be clinical homes for veterans connected with a central clinician who can explain and coordinate their mental health care as well as bring more consistency to the referral process.26 The ongoing transition toward the BHIP model of mental health care at VA may provide the opportunity to consolidate and integrate knowledge about the VA approach to mental health care, potentially filling knowledge gaps.

A second area of process improvement focused on the shared decision-making process. Consistent with mental health initiatives, veterans generally believed they had received sufficient information about TF-EBP and engaged in shared decision-making with clinicians.20,27 Veterans were given educational materials to review and had the opportunity to discuss these materials with clinicians. However, veterans described variability in the success of shared decision-making. Although veterans valued receiving accurate, comprehensible information to support treatment decisions, some preferred to defer to clinicians’ expertise regarding which treatment to pursue. While these veterans valued information, they also valued the expertise of clinicians in explaining why specific treatments would be beneficial. A key contributor to veterans satisfaction was assessing how veterans wanted to engage in the decision-making process and respecting those preferences.28 Veterans approached shared decision-making differently, from making decisions independently after receiving information to relying solely on clinician recommendation. The process was most successful when clinicians articulated how their recommended treatment aligned with a veteran’s preferences, including recommendations based on specific values (eg, personalized match vs being the best). Another important consideration is ensuring veterans know they can receive a variety of different types of mental health services available in different modalities (eg, virtual vs in-person; group vs individual). When veterans did not perceive choice in treatment aspects important to them (typically despite having choices), they were less satisfied with their TF-EBP experience.

A final area of process improvement identified involves how therapists address important aspects of culture. Veterans often described mental health stigma coming from intersecting cultural identities and expressed appreciation when therapists helped them recognize the impact of these beliefs on treatment. Some veterans did not discuss important aspects of their identity with clinicians, including race/ethnicity, religion, and military culture. Veterans did not report negative interactions with clinicians or experiences suggesting it was inappropriate to discuss identity; however, they were reluctant to independently raise these identity factors. Strategies such as the ADDRESSING framework, a mnemonic acronym that describes a series of potentially relevant characteristics, can help clinicians comprehensively consider different aspects that may be relevant to veterans, modeling that discussion of relevant these characteristics is welcome in TF-EBP.29 Veterans reported that making culturally relevant connections enhanced the TF-EBP experience, most commonly with military culture. These data support that TF-EBP delivery with attention to culture should be an integrated part of treatment, supporting engagement and therapeutic alliance.30 The VA National Center for PTSD consultation program is a resource to support clinicians in assessing and incorporating relevant aspects of cultural identity.31 For example, the National Center for PTSD provides a guide for using case conceptualization to address patient reactions to race-based violence during PTSD treatment.32 Both manualized design and therapist certification training can reinforce that assessing and attending to case conceptualization (including identity factors) is an integral component of TF-EBP.33,34

Limitations

While the current study has numerous strengths (eg, national veteran sampling, robust qualitative methods), results should be considered within the context of study limitations. First, veteran participants all received TF-EBP, and the perspectives of veterans who never initiate TF-EBP may differ. Despite the strong sampling approach, the study design is not intended to be generalizable to all veterans receiving TF-EBP for PTSD. Qualitative analysis yielded 15 themes, described in this study and prior research, consistent with recommendations.21,22 This approach allows rich description of distinct focus areas that would not be possible in a single manuscript. Nonetheless, all veterans interviewed described their experiences in TF-EBP and general mental health care, the focus of the semistructured interview guide was on the experience of transitioning from other treatment to TF-EBP.

Conclusion

This study describes themes related to general mental health and TF-EBP process improvement as part of a larger study on transitions in PTSD care.21,22 Veterans valued the fundamentals of therapy, including rapport and flexibility. Treatment-specific rapport (eg, pointing out treatment progress and effort in completing treatment components) and flexibility within the context of fidelity (ie, personalizing treatment while maintaining core treatment elements) may be most effective at engaging veterans in recommended PTSD treatments.18,34 In addition to successes, themes suggest multiple opportunities for process improvement. Ongoing VA initiatives and priorities (ie, BHIP, shared decision-making, consultation services) aim to improve processes consistent with veteran recommendations. Future research is needed to evaluate the success of these and other programs to optimize access to and engagement in recommended PTSD treatments.

References
  1. US Department of Veterans Affairs; US Department of Defense. VA/DoD clinical practice guideline for the management of posttraumatic stress disorder and acute stress disorder. 2023. Updated August 20, 2025. Accessed October 17, 2025. https://www.healthquality.va.gov/guidelines/MH/ptsd/
  2. International Society for Traumatic Stress Studies. ISTSS PTSD prevention and treatment guidelines: methodology and recommendations. Accessed August 13, 2025. http://www.istss.org/getattachment/Treating-Trauma/New-ISTSS-Prevention-and-TreatmentGuidelines/ISTSS_PreventionTreatmentGuidelines_FNL-March-19-2019.pdf.aspx
  3. American Psychological Association. Clinical practice guideline for the treatment of posttraumatic stress disorder in adults. Accessed August 13, 2025. https://www.apa.org/ptsd-guideline/ptsd.pdf
  4. Karlin BE, Cross G. From the laboratory to the therapy room: National dissemination and implementation of evidence- based psychotherapies in the U.S. Department of Veterans Affairs Health Care System. Am Psychol. 2014;69:19-33. doi:10.1037/a0033888
  5. Rosen CS, Matthieu MM, Wiltsey Stirman S, et al. A review of studies on the system-wide implementation of evidencebased psychotherapies for posttraumatic stress disorder in the Veterans Health Administration. Adm Policy Ment Health. 2016;43:957-977. doi:10.1007/s10488-016-0755-0
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References
  1. US Department of Veterans Affairs; US Department of Defense. VA/DoD clinical practice guideline for the management of posttraumatic stress disorder and acute stress disorder. 2023. Updated August 20, 2025. Accessed October 17, 2025. https://www.healthquality.va.gov/guidelines/MH/ptsd/
  2. International Society for Traumatic Stress Studies. ISTSS PTSD prevention and treatment guidelines: methodology and recommendations. Accessed August 13, 2025. http://www.istss.org/getattachment/Treating-Trauma/New-ISTSS-Prevention-and-TreatmentGuidelines/ISTSS_PreventionTreatmentGuidelines_FNL-March-19-2019.pdf.aspx
  3. American Psychological Association. Clinical practice guideline for the treatment of posttraumatic stress disorder in adults. Accessed August 13, 2025. https://www.apa.org/ptsd-guideline/ptsd.pdf
  4. Karlin BE, Cross G. From the laboratory to the therapy room: National dissemination and implementation of evidence- based psychotherapies in the U.S. Department of Veterans Affairs Health Care System. Am Psychol. 2014;69:19-33. doi:10.1037/a0033888
  5. Rosen CS, Matthieu MM, Wiltsey Stirman S, et al. A review of studies on the system-wide implementation of evidencebased psychotherapies for posttraumatic stress disorder in the Veterans Health Administration. Adm Policy Ment Health. 2016;43:957-977. doi:10.1007/s10488-016-0755-0
  6. Maguen S, Holder N, Madden E, et al. Evidence-based psychotherapy trends among posttraumatic stress disorder patients in a national healthcare system, 2001-2014. Depress Anxiety. 2020;37:356-364. doi:10.1002/da.22983
  7. Cheney AM, Koenig CJ, Miller CJ, et al. Veteran-centered barriers to VA mental healthcare services use. BMC Health Serv Res. 2018;18:591. doi:10.1186/s12913-018-3346-9
  8. Hundt NE, Mott JM, Miles SR, et al. Veterans’ perspectives on initiating evidence-based psychotherapy for posttraumatic stress disorder. Psychol Trauma. 2015;7:539-546. doi:10.1037/tra0000035
  9. Hundt NE, Helm A, Smith TL, et al. Failure to engage: a qualitative study of veterans who decline evidence-based psychotherapies for PTSD. Psychol Serv. 2018;15:536- 542. doi:10.1037/ser0000212
  10. Sayer NA, Friedemann-Sanchez G, Spoont M, et al. A qualitative study of determinants of PTSD treatment initiation in veterans. Psychiatry. 2009;72:238-255. doi:10.1521/psyc.2009.72.3.238
  11. Mittal D, Drummond KL, Blevins D, et al. Stigma associated with PTSD: perceptions of treatment seeking combat veterans. Psychiatr Rehabil J. 2013;36:86-92. doi:10.1037/h0094976
  12. Possemato K, Wray LO, Johnson E, et al. Facilitators and barriers to seeking mental health care among primary care veterans with posttraumatic stress disorder. J Trauma Stress. 2018;31:742-752. doi:10.1002/jts.22327
  13. Silvestrini M, Chen JA. “It’s a sign of weakness”: Masculinity and help-seeking behaviors among male veterans accessing posttraumatic stress disorder care. Psychol Trauma. 2023;15:665-671. doi:10.1037/tra0001382
  14. Stecker T, Shiner B, Watts BV, et al. Treatment-seeking barriers for veterans of the Iraq and Afghanistan conflicts who screen positive for PTSD. Psychiatr Serv. 2013;64:280-283. doi:10.1176/appi.ps.001372012
  15. Etingen B, Grubbs KM, Harik JM. Drivers of preference for evidence-based PTSD treatment: a qualitative assessment. Mil Med. 2020;185:303-310. doi:10.1093/milmed/usz220
  16. Hundt NE, Ecker AH, Thompson K, et al. “It didn’t fit for me:” A qualitative examination of dropout from prolonged exposure and cognitive processing therapy in veterans. Psychol Serv. 2020;17:414-421. doi:10.1037/ser0000316
  17. Kehle-Forbes SM, Gerould H, Polusny MA, et al. “It leaves me very skeptical” messaging in marketing prolonged exposure and cognitive processing therapy to veterans with PTSD. Psychol Trauma. 2022;14:849-852. doi:10.1037/tra0000550
  18. Kehle-Forbes SM, Ackland PE, Spoont MR, et al. Divergent experiences of U.S. veterans who did and did not complete trauma-focused therapies for PTSD: a national qualitative study of treatment dropout. Behav Res Ther. 2022;154:104123. doi:10.1016/j.brat.2022.104123
  19. Hessinger JD, London MJ, Baer SM. Evaluation of a shared decision-making intervention on the utilization of evidence-based psychotherapy in a VA outpatient PTSD clinic. Psychol Serv. 2018;15:437-441. doi:10.1037/ser0000141
  20. Hamblen JL, Grubbs KM, Cole B, et al. “Will it work for me?” Developing patient-friendly graphical displays of posttraumatic stress disorder treatment effectiveness. J Trauma Stress. 2022;35:999-1010. doi:10.1002/jts.22808
  21. Holder N, Ranney RM, Delgado AK, et al. Transitioning into trauma-focused evidence-based psychotherapy for posttraumatic stress disorder from other treatments: a qualitative investigation. Cogn Behav Ther. 2025;54:391-407. doi:10.1080/16506073.2024.2408386
  22. Levitt HM, Bamberg M, Creswell JW, et al. Journal article reporting standards for qualitative primary, qualitative meta-analytic, and mixed methods research in psychology: The APA Publications and Communications Board task force report. Am Psychol. 2018;73:26-46. doi:10.1037/amp0000151
  23. Palinkas LA, Mendon SJ, Hamilton AB. Innovations in mixed methods evaluations. Annu Rev Public Health. 2019;40:423- 442. doi:10.1146/annurev-publhealth-040218-044215
  24. Ranney RM, Cordova MJ, Maguen S. A review of the referral process for evidence-based psychotherapies for PTSD among veterans. Prof Psychol Res Pr. 2022;53:276-285. doi:10.1037/pro0000463
  25. Holder N, Ranney RM, Delgado AK, et al. Transitions to trauma-focused evidence-based psychotherapy for posttraumatic stress disorder from other treatment: a qualitative investigation of clinician’s perspectives. Cogn Behav Ther. 2025;1-19. doi:10.1080/16506073.2025.2481475
  26. Barry CN, Abraham KM, Weaver KR, et al. Innovating team-based outpatient mental health care in the Veterans Health Administration: staff-perceived benefits and challenges to pilot implementation of the Behavioral Health Interdisciplinary Program (BHIP). Psychol Serv. 2016;13:148-155. doi:10.1037/ser0000072
  27. Harik JM, Hundt NE, Bernardy NC, et al. Desired involvement in treatment decisions among adults with PTSD symptoms. J Trauma Stress. 2016;29:221-228. doi:10.1002/jts.22102
  28. Larsen SE, Hooyer K, Kehle-Forbes SM, et al. Patient experiences in making PTSD treatment decisions. Psychol Serv. 2024;21:529-537. doi:10.1037/ser0000817
  29. Hays PA. Four steps toward intersectionality in psychotherapy using the ADDRESSING framework. Prof Psychol Res Pr. 2024;55:454-462. doi:10.1037/pro0000577
  30. Galovski TE, Nixon RDV, Kaysen D. Flexible Applications of Cognitive Processing Therapy: Evidence-Based Treatment Methods. Academic Press; 2020.
  31. Larsen SE, McKee T, Fielstein E, et al. The development of a posttraumatic stress disorder (PTSD) consultation program to support system-wide implementation of high-quality PTSD care for veterans. Psychol Serv. 2025;22:342-348. doi:10.1037/ser0000867
  32. Galovski T, Kaysen D, McClendon J, et al. Provider guide to addressing patient reactions to race-based violence during PTSD treatment. PTSD.va.gov. Accessed August 3, 2025. www.ptsd.va.gov/professional/treat/specific/patient_reactions_race_violence.asp
  33. Galovski TE, Nixon RDV, Kehle-Forbes S. Walking the line between fidelity and flexibility: a conceptual review of personalized approaches to manualized treatments for posttraumatic stress disorder. J Trauma Stress. 2024;37:768-774. doi:10.1002/jts.23073
  34. Galovski TE, McSweeney LB, Nixon RDV, et al. Personalizing cognitive processing therapy with a case formulation approach to intentionally target impairment in psychosocial functioning associated with PTSD. Contemp Clin Trials Commun. 2024;42:101385. doi:10.1016/j.conctc.2024.101385
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Process Improvement for Engaging With Trauma-Focused Evidence-Based Psychotherapy for PTSD

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Helping Veterans Ease Into Civilian Life

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What does a successful military-to-civilian transition look like? How do we know if a veteran is sinking, treading water, or swimming? Two recent studies by the Penn State University Clearinghouse for Military Family Readiness sought to answer to those questions and more while determining how and when is the right time to step in to help a veteran in need.

The research analyzed The Veterans Metrics Initiative data (TVMI). This longitudinal study surveyed 9566 men and women who left active duty in 2016 over 3 years, answering questions about deployment histories, adverse childhood experiences (ACEs) and exposure to combat. They also reported whether they had symptoms related to anxiety and depression. 

The TVMI study found that ACEs predicted poor outcomes early on and when combined with warfare experience dramatically increased the likelihood of mental health issues, including posttraumatic stress disorder (PTSD), anxiety, and depression; moral injury impacted adjustment to civilian life (the degree varied by gender); and, many veterans have a “growth outlook” as a result of a trauma or crisis they experienced.

The TVMI study found that almost all veterans use transition resources in the first 2 years after military separation. Beyond that, however, those in high-risk categories (eg, PTSD and cumulative trauma experiences) need continued support. This may come in the form of a universal screener and linking it to a navigation infrastructure (eg, AmericaServes), “thereby identifying risk factors early and providing targeted supports, interventions, and components.”

Veterans often face a series of simultaneous challenges as they return to civilian life. Among them include getting used to family and friends again, finding jobs, losing their military identity, structure, and perhaps leaving military friends behind. In addition, veterans are likely dealing with physical and mental health challenges, which can significantly influence how well they readjust to civilian life and lead to inconsistency experiences for each individual.

A 2019 survey from the Pew Research Center found about 40% of veterans who suffered from PTSD said they frequently had difficulty dealing with the lack of structure in civilian life, compared with 5% of those who do not have PTSD. Another survey cited a large majority (78%) of pre-9/11 veterans said their readjustment was very or somewhat easy. However, 26% said adjusting to civilian life was difficult.

In 2011, 4 variables were identified that predicted easy civilian life re-entry: being an officer; having a consistently clear understanding of the missions while in the service; being a college graduate; and, for post-9/11 veterans, attending religious services frequently. Six variables were associated with a diminished probability of an easy transition: having had a traumatic experience; being seriously injured; serving in the post-9/11 era; serving in a combat zone; serving with someone who was killed or injured; and, for post-9/11 veterans, being married while in the service.

The probabilities of an easy re-entry dropped from 82% for those who did not experience a traumatic event to 56% for those who did—the largest change noted in the 2011 study.

The second Penn State study evaluated a model framework with a lifespan development perspective. The study surveyed veterans on their self-reported satisfaction or symptoms in 7 domains of well-being: employment, education, financial, legal problems, social, physical health, and mental health. Within 3 months of separation , 41% of respondents fell into the “problematic” category for the mental health domain. However, by 30 to 33 months postseparation, this proportion dropped to 34%. During the same period, the proportion of veterans in the at risk category increased from 28% at Wave 1 to 37% at Wave 6. About 30% of veterans fell into the successful category for symptoms across the 3 examined waves. Almost 60% were in the successful category across the 3 time points.

Both Penn State studies emphasize the importance of viewing veterans as individuals on their own timelines.

“These findings underscore that the transition to civilian life is not a single moment, but a process influenced by experiences across the life span,” said Mary M. Mitchell, research professor at the Clearinghouse and lead author on the predictors study. “By following veterans over 3 years, we were able to see how patterns emerge that would be invisible in a one-time survey.”

Current conceptualization “assumes that there are commonalities across veterans when evaluating the success of the transition to civilian life,” according to the authors of the framework study. “However, each veteran likely has his or her view of what a successful transition constitutes, and he or she may weigh domains differently when considering his or her own transition.”

The research highlights the need to find ways to encourage veterans to seek help—and not just in the first year, which is often the most stressful. The Pew Research Center survey identified a “significant break from the past,” in that nearly 70% of post-9/11 veterans said their superiors made them feel comfortable about seeking help with emotional issues resulting from their military service. 

However, ≤ 8% veterans in the TVMI study used any health programs, even when they screened positive for mental health problems. Veterans who did use counseling services, however, improved their depression symptoms. Engaging veterans at various time points could help keep mental health problems from worsening during—and beyond—the transition.

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What does a successful military-to-civilian transition look like? How do we know if a veteran is sinking, treading water, or swimming? Two recent studies by the Penn State University Clearinghouse for Military Family Readiness sought to answer to those questions and more while determining how and when is the right time to step in to help a veteran in need.

The research analyzed The Veterans Metrics Initiative data (TVMI). This longitudinal study surveyed 9566 men and women who left active duty in 2016 over 3 years, answering questions about deployment histories, adverse childhood experiences (ACEs) and exposure to combat. They also reported whether they had symptoms related to anxiety and depression. 

The TVMI study found that ACEs predicted poor outcomes early on and when combined with warfare experience dramatically increased the likelihood of mental health issues, including posttraumatic stress disorder (PTSD), anxiety, and depression; moral injury impacted adjustment to civilian life (the degree varied by gender); and, many veterans have a “growth outlook” as a result of a trauma or crisis they experienced.

The TVMI study found that almost all veterans use transition resources in the first 2 years after military separation. Beyond that, however, those in high-risk categories (eg, PTSD and cumulative trauma experiences) need continued support. This may come in the form of a universal screener and linking it to a navigation infrastructure (eg, AmericaServes), “thereby identifying risk factors early and providing targeted supports, interventions, and components.”

Veterans often face a series of simultaneous challenges as they return to civilian life. Among them include getting used to family and friends again, finding jobs, losing their military identity, structure, and perhaps leaving military friends behind. In addition, veterans are likely dealing with physical and mental health challenges, which can significantly influence how well they readjust to civilian life and lead to inconsistency experiences for each individual.

A 2019 survey from the Pew Research Center found about 40% of veterans who suffered from PTSD said they frequently had difficulty dealing with the lack of structure in civilian life, compared with 5% of those who do not have PTSD. Another survey cited a large majority (78%) of pre-9/11 veterans said their readjustment was very or somewhat easy. However, 26% said adjusting to civilian life was difficult.

In 2011, 4 variables were identified that predicted easy civilian life re-entry: being an officer; having a consistently clear understanding of the missions while in the service; being a college graduate; and, for post-9/11 veterans, attending religious services frequently. Six variables were associated with a diminished probability of an easy transition: having had a traumatic experience; being seriously injured; serving in the post-9/11 era; serving in a combat zone; serving with someone who was killed or injured; and, for post-9/11 veterans, being married while in the service.

The probabilities of an easy re-entry dropped from 82% for those who did not experience a traumatic event to 56% for those who did—the largest change noted in the 2011 study.

The second Penn State study evaluated a model framework with a lifespan development perspective. The study surveyed veterans on their self-reported satisfaction or symptoms in 7 domains of well-being: employment, education, financial, legal problems, social, physical health, and mental health. Within 3 months of separation , 41% of respondents fell into the “problematic” category for the mental health domain. However, by 30 to 33 months postseparation, this proportion dropped to 34%. During the same period, the proportion of veterans in the at risk category increased from 28% at Wave 1 to 37% at Wave 6. About 30% of veterans fell into the successful category for symptoms across the 3 examined waves. Almost 60% were in the successful category across the 3 time points.

Both Penn State studies emphasize the importance of viewing veterans as individuals on their own timelines.

“These findings underscore that the transition to civilian life is not a single moment, but a process influenced by experiences across the life span,” said Mary M. Mitchell, research professor at the Clearinghouse and lead author on the predictors study. “By following veterans over 3 years, we were able to see how patterns emerge that would be invisible in a one-time survey.”

Current conceptualization “assumes that there are commonalities across veterans when evaluating the success of the transition to civilian life,” according to the authors of the framework study. “However, each veteran likely has his or her view of what a successful transition constitutes, and he or she may weigh domains differently when considering his or her own transition.”

The research highlights the need to find ways to encourage veterans to seek help—and not just in the first year, which is often the most stressful. The Pew Research Center survey identified a “significant break from the past,” in that nearly 70% of post-9/11 veterans said their superiors made them feel comfortable about seeking help with emotional issues resulting from their military service. 

However, ≤ 8% veterans in the TVMI study used any health programs, even when they screened positive for mental health problems. Veterans who did use counseling services, however, improved their depression symptoms. Engaging veterans at various time points could help keep mental health problems from worsening during—and beyond—the transition.

What does a successful military-to-civilian transition look like? How do we know if a veteran is sinking, treading water, or swimming? Two recent studies by the Penn State University Clearinghouse for Military Family Readiness sought to answer to those questions and more while determining how and when is the right time to step in to help a veteran in need.

The research analyzed The Veterans Metrics Initiative data (TVMI). This longitudinal study surveyed 9566 men and women who left active duty in 2016 over 3 years, answering questions about deployment histories, adverse childhood experiences (ACEs) and exposure to combat. They also reported whether they had symptoms related to anxiety and depression. 

The TVMI study found that ACEs predicted poor outcomes early on and when combined with warfare experience dramatically increased the likelihood of mental health issues, including posttraumatic stress disorder (PTSD), anxiety, and depression; moral injury impacted adjustment to civilian life (the degree varied by gender); and, many veterans have a “growth outlook” as a result of a trauma or crisis they experienced.

The TVMI study found that almost all veterans use transition resources in the first 2 years after military separation. Beyond that, however, those in high-risk categories (eg, PTSD and cumulative trauma experiences) need continued support. This may come in the form of a universal screener and linking it to a navigation infrastructure (eg, AmericaServes), “thereby identifying risk factors early and providing targeted supports, interventions, and components.”

Veterans often face a series of simultaneous challenges as they return to civilian life. Among them include getting used to family and friends again, finding jobs, losing their military identity, structure, and perhaps leaving military friends behind. In addition, veterans are likely dealing with physical and mental health challenges, which can significantly influence how well they readjust to civilian life and lead to inconsistency experiences for each individual.

A 2019 survey from the Pew Research Center found about 40% of veterans who suffered from PTSD said they frequently had difficulty dealing with the lack of structure in civilian life, compared with 5% of those who do not have PTSD. Another survey cited a large majority (78%) of pre-9/11 veterans said their readjustment was very or somewhat easy. However, 26% said adjusting to civilian life was difficult.

In 2011, 4 variables were identified that predicted easy civilian life re-entry: being an officer; having a consistently clear understanding of the missions while in the service; being a college graduate; and, for post-9/11 veterans, attending religious services frequently. Six variables were associated with a diminished probability of an easy transition: having had a traumatic experience; being seriously injured; serving in the post-9/11 era; serving in a combat zone; serving with someone who was killed or injured; and, for post-9/11 veterans, being married while in the service.

The probabilities of an easy re-entry dropped from 82% for those who did not experience a traumatic event to 56% for those who did—the largest change noted in the 2011 study.

The second Penn State study evaluated a model framework with a lifespan development perspective. The study surveyed veterans on their self-reported satisfaction or symptoms in 7 domains of well-being: employment, education, financial, legal problems, social, physical health, and mental health. Within 3 months of separation , 41% of respondents fell into the “problematic” category for the mental health domain. However, by 30 to 33 months postseparation, this proportion dropped to 34%. During the same period, the proportion of veterans in the at risk category increased from 28% at Wave 1 to 37% at Wave 6. About 30% of veterans fell into the successful category for symptoms across the 3 examined waves. Almost 60% were in the successful category across the 3 time points.

Both Penn State studies emphasize the importance of viewing veterans as individuals on their own timelines.

“These findings underscore that the transition to civilian life is not a single moment, but a process influenced by experiences across the life span,” said Mary M. Mitchell, research professor at the Clearinghouse and lead author on the predictors study. “By following veterans over 3 years, we were able to see how patterns emerge that would be invisible in a one-time survey.”

Current conceptualization “assumes that there are commonalities across veterans when evaluating the success of the transition to civilian life,” according to the authors of the framework study. “However, each veteran likely has his or her view of what a successful transition constitutes, and he or she may weigh domains differently when considering his or her own transition.”

The research highlights the need to find ways to encourage veterans to seek help—and not just in the first year, which is often the most stressful. The Pew Research Center survey identified a “significant break from the past,” in that nearly 70% of post-9/11 veterans said their superiors made them feel comfortable about seeking help with emotional issues resulting from their military service. 

However, ≤ 8% veterans in the TVMI study used any health programs, even when they screened positive for mental health problems. Veterans who did use counseling services, however, improved their depression symptoms. Engaging veterans at various time points could help keep mental health problems from worsening during—and beyond—the transition.

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'Energy Insecurity' Tied to Anxiety, Depression Risk

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'Energy Insecurity' Tied to Anxiety, Depression Risk

TOPLINE:

Energy insecurity, the inability to meet household energy needs, was associated with more than twice the odds of having depression and anxiety symptoms than energy security in US adults, a new cross-sectional study showed.

METHODOLOGY:

  • Using data from the US Census Bureau's online Household Pulse Survey, administered between 2022 and 2024, researchers conducted a cross-sectional study with a weighted population of > 187 million US adults (51% women; 64% White, 16% Hispanic, 10% Black, and 5% Asian). About a quarter of the population was in each of 4 age groups: 18-34 years, 35-49 years, 50-64 years, and ≥ 65 years.
  • Three indicators of energy insecurity—inability to pay energy bills, maintaining unsafe/unhealthy home temperatures, and forgoing expenses on basic necessities to pay energy bills—were assessed individually and as a composite measure.
  • Mental health was assessed using modified versions of the 2-item Patient Health Questionnaire for depression and the 2-item Generalized Anxiety Disorder scale for anxiety.
  • The analysis was adjusted for other social determinants of health, including unemployment, housing instability, and food insecurity. Covariates included a wide range of factors, such as age, educational level, sex, and annual household income.

TAKEAWAY:

  • In all, > 43% of the population reported having ≥ 1 form of energy security; around 22% reported being unable to pay energy bills, 22% maintained unsafe home temperatures, and nearly 34% forewent spending on basic necessities to pay energy bills.
  • Individuals who gave up spending on basic necessities to pay energy bills had higher odds of anxiety (adjusted odds ratio [aOR], 1.79) and depression (aOR, 1.74) than those who did not.
  • Adults with energy insecurity on the composite measure had higher odds for anxiety (aOR, 2.29) and depression (aOR, 2.31) than those with energy security.
  • Food insecurity was also associated with poorer mental health, with higher odds for symptoms of depression (aOR, 2.05) and anxiety (aOR, 2.07).

IN PRACTICE:

"Despite its high prevalence, energy insecurity remains underrecognized in public health and policy intervention strategies," the investigators wrote.

"These findings suggest that energy insecurity is a widespread and important factor associated with mental health symptoms and may warrant consideration in efforts to reduce adverse mental health outcomes," they added.

SOURCE:

This study was led by Michelle Graf, PhD, Carter School of Public Policy, Georgia Institute of Technology, Atlanta. It was published online on October 27 in JAMA Network Open.

LIMITATIONS:

The cross-sectional nature of the data limited causal interference and increased the possibility of reverse causality. The questionnaire captured subjective interpretations of unsafe and unhealthy indoor temperatures, which may have varied among respondents. Additionally, the recall periods for energy insecurity and mental health outcomes were different.

DISCLOSURES:

The investigators reported no relevant conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

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TOPLINE:

Energy insecurity, the inability to meet household energy needs, was associated with more than twice the odds of having depression and anxiety symptoms than energy security in US adults, a new cross-sectional study showed.

METHODOLOGY:

  • Using data from the US Census Bureau's online Household Pulse Survey, administered between 2022 and 2024, researchers conducted a cross-sectional study with a weighted population of > 187 million US adults (51% women; 64% White, 16% Hispanic, 10% Black, and 5% Asian). About a quarter of the population was in each of 4 age groups: 18-34 years, 35-49 years, 50-64 years, and ≥ 65 years.
  • Three indicators of energy insecurity—inability to pay energy bills, maintaining unsafe/unhealthy home temperatures, and forgoing expenses on basic necessities to pay energy bills—were assessed individually and as a composite measure.
  • Mental health was assessed using modified versions of the 2-item Patient Health Questionnaire for depression and the 2-item Generalized Anxiety Disorder scale for anxiety.
  • The analysis was adjusted for other social determinants of health, including unemployment, housing instability, and food insecurity. Covariates included a wide range of factors, such as age, educational level, sex, and annual household income.

TAKEAWAY:

  • In all, > 43% of the population reported having ≥ 1 form of energy security; around 22% reported being unable to pay energy bills, 22% maintained unsafe home temperatures, and nearly 34% forewent spending on basic necessities to pay energy bills.
  • Individuals who gave up spending on basic necessities to pay energy bills had higher odds of anxiety (adjusted odds ratio [aOR], 1.79) and depression (aOR, 1.74) than those who did not.
  • Adults with energy insecurity on the composite measure had higher odds for anxiety (aOR, 2.29) and depression (aOR, 2.31) than those with energy security.
  • Food insecurity was also associated with poorer mental health, with higher odds for symptoms of depression (aOR, 2.05) and anxiety (aOR, 2.07).

IN PRACTICE:

"Despite its high prevalence, energy insecurity remains underrecognized in public health and policy intervention strategies," the investigators wrote.

"These findings suggest that energy insecurity is a widespread and important factor associated with mental health symptoms and may warrant consideration in efforts to reduce adverse mental health outcomes," they added.

SOURCE:

This study was led by Michelle Graf, PhD, Carter School of Public Policy, Georgia Institute of Technology, Atlanta. It was published online on October 27 in JAMA Network Open.

LIMITATIONS:

The cross-sectional nature of the data limited causal interference and increased the possibility of reverse causality. The questionnaire captured subjective interpretations of unsafe and unhealthy indoor temperatures, which may have varied among respondents. Additionally, the recall periods for energy insecurity and mental health outcomes were different.

DISCLOSURES:

The investigators reported no relevant conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

TOPLINE:

Energy insecurity, the inability to meet household energy needs, was associated with more than twice the odds of having depression and anxiety symptoms than energy security in US adults, a new cross-sectional study showed.

METHODOLOGY:

  • Using data from the US Census Bureau's online Household Pulse Survey, administered between 2022 and 2024, researchers conducted a cross-sectional study with a weighted population of > 187 million US adults (51% women; 64% White, 16% Hispanic, 10% Black, and 5% Asian). About a quarter of the population was in each of 4 age groups: 18-34 years, 35-49 years, 50-64 years, and ≥ 65 years.
  • Three indicators of energy insecurity—inability to pay energy bills, maintaining unsafe/unhealthy home temperatures, and forgoing expenses on basic necessities to pay energy bills—were assessed individually and as a composite measure.
  • Mental health was assessed using modified versions of the 2-item Patient Health Questionnaire for depression and the 2-item Generalized Anxiety Disorder scale for anxiety.
  • The analysis was adjusted for other social determinants of health, including unemployment, housing instability, and food insecurity. Covariates included a wide range of factors, such as age, educational level, sex, and annual household income.

TAKEAWAY:

  • In all, > 43% of the population reported having ≥ 1 form of energy security; around 22% reported being unable to pay energy bills, 22% maintained unsafe home temperatures, and nearly 34% forewent spending on basic necessities to pay energy bills.
  • Individuals who gave up spending on basic necessities to pay energy bills had higher odds of anxiety (adjusted odds ratio [aOR], 1.79) and depression (aOR, 1.74) than those who did not.
  • Adults with energy insecurity on the composite measure had higher odds for anxiety (aOR, 2.29) and depression (aOR, 2.31) than those with energy security.
  • Food insecurity was also associated with poorer mental health, with higher odds for symptoms of depression (aOR, 2.05) and anxiety (aOR, 2.07).

IN PRACTICE:

"Despite its high prevalence, energy insecurity remains underrecognized in public health and policy intervention strategies," the investigators wrote.

"These findings suggest that energy insecurity is a widespread and important factor associated with mental health symptoms and may warrant consideration in efforts to reduce adverse mental health outcomes," they added.

SOURCE:

This study was led by Michelle Graf, PhD, Carter School of Public Policy, Georgia Institute of Technology, Atlanta. It was published online on October 27 in JAMA Network Open.

LIMITATIONS:

The cross-sectional nature of the data limited causal interference and increased the possibility of reverse causality. The questionnaire captured subjective interpretations of unsafe and unhealthy indoor temperatures, which may have varied among respondents. Additionally, the recall periods for energy insecurity and mental health outcomes were different.

DISCLOSURES:

The investigators reported no relevant conflicts of interest.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

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'Energy Insecurity' Tied to Anxiety, Depression Risk

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'Energy Insecurity' Tied to Anxiety, Depression Risk

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Preoperative Diabetes Management for Patients Undergoing Elective Surgeries at a Veterans Affairs Medical Center

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Preoperative Diabetes Management for Patients Undergoing Elective Surgeries at a Veterans Affairs Medical Center

More than 38 million people in the United States (12%) have diabetes mellitus (DM), though 1 in 5 are unaware they have DM.1 The prevalence among veterans is even more substantial, impacting nearly 25% of those who received care from the US Department of Veterans Affairs (VA).2 DM can lead to increased health care costs in addition to various complications (eg, cardiovascular, renal), especially if left uncontrolled.1,3 similar impact is found in the perioperative period (defined as at or around the time of an operation), as multiple studies have found that uncontrolled preoperative DM can result in worsened surgical outcomes, including longer hospital stays, more infectious complications, and higher perioperative mortality.4-6

In contrast, adequate glycemic control assessed with blood glucose levels has been shown to decrease the incidence of postoperative infections.7 Optimizing glycemic control during hospital stays, especially postsurgery, has become the standard of care, with most health systems establishing specific protocols. In current literature, most studies examining DM management in the perioperative period are focused on postoperative care, with little attention to the preoperative period.4,6,7

One study found that patients with poor presurgery glycemic control assessed by hemoglobin A1c (HbA1c) levels were more likely to remain hyperglycemic during and after surgery. 8 Blood glucose levels < 200 mg/dL can lead to an increased risk of infection and impaired wound healing, meaning a well-controlled HbA1c before a procedure serves as a potential factor for success.9 The 2025 American Diabetes Association (ADA) Standards of Care (SOC) recommendation is to target HbA1c < 8% whenever possible, and some health systems require lower levels (eg, < 7% or 7.5%).10 With that goal in mind and knowing that preoperative hyperglycemia has been shown to be a contributing factor in the delay or cancellation of surgical cases, an argument can be made that attention to preoperative DM management also should be a focus for health care systems performing surgeries.8,9,11

Attention to glucose control during preoperative care offers an opportunity to screen for DM in patients who may not have been screened otherwise and to standardize perioperative DM management. Since DM disproportionately impacts veterans, this is a pertinent issue to the VA. Veterans can be more susceptible to complications if DM is left uncontrolled prior to surgery. To determine readiness for surgery and control of comorbid conditions such as DM before a planned surgery, facilities often perform a preoperative clinic assessment, often in a multidisciplinary clinic.

At Veteran Health Indiana (VHI), a presurgery clinic visit involving the primary surgery service (physician, nurse practitioner, and/or a physician assistant) is conducted 1 to 2 months prior to the planned procedure to determine whether a patient is ready for surgery. During this visit, patients receive a packet with instructions for various tasks and medications, such as applying topical antibiotic prophylaxis on the anticipated surgical site. This is documented in the form of a note in the VHI Computerized Patient Record System (CPRS). The medication instructions are provided according to the preferences of the surgical team. These may be templated notes that contain general directions on the timing and dosing of specific medications, in addition to instructions for holding or reducing doses when appropriate. The instructions can be tailored by the team conducting the preoperative visit (eg, “Take 20 units of insulin glargine the day before surgery” vs “Take half of your long-acting insulin the night before surgery”). Specific to DM, VHI has a nurse-driven day of surgery glucose assessment where point-of-care blood glucose is collected during preoperative holding for most patients.

There is limited research assessing the level of preoperative glycemic control and the incidence of complications in a veteran population. The objective of this study was to gain a baseline understanding of what, if any, standardization exists for preoperative instructions for DM medications and to assess the level of preoperative glycemic control and postoperative complications in patients with DM undergoing major elective surgical procedures.

Methods

This retrospective, single-center chart review was conducted at VHI. The Indiana University and VHI institutional review boards determined that this quality improvement project was exempt from review.

The primary outcome was the number of patients with surgical procedures delayed or canceled due to hyperglycemia or hypoglycemia. Hyperglycemia was defined as blood glucose > 180 mg/dL and hypoglycemia was defined as < 70 mg/dL, slight variations from the current ADA SOC preoperative specific recommendation of a blood glucose reading of 100 to 180 mg/dL within 4 hours of surgery.10 The standard outpatient hypoglycemia definition of blood glucose < 70 mg/dL was chosen because the current goal (< 100 mg/dL) was not the standard in previous ADA SOCs that were in place during the study period. Specifically, the 2018 ADA SOC did not provide preoperative recommendations and the 2019-2021 ADA SOC recommended 80 to 180 mg/dL.10,12-18 For patients who had multiple preoperative blood glucose measurements, the first recorded glucose on the day of the procedure was used.

The secondary outcomes of this study were focused on the preoperative process/care at VHI and postoperative glycemic control. The preoperative process included examining whether medication instructions were given and their quality. Additionally, the number of interventions for hyperglycemia and hypoglycemia were required immediately prior to surgery and the average preoperative HbA1c (measured within 3 months prior to surgery) were collected and analyzed. For postoperative glycemic control, average blood glucose measurements and number of hypoglycemic (< 70 mg/dL) and hyperglycemic (> 180 mg/dL) events were measured in addition to the frequency of changes made at discharge to patients’ DM medication regimens.

The safety outcome of this study assessed commonly observed postoperative complications and was examined up to 30 days postsurgery. These included acute kidney injury (defined using Kidney Disease: Improving Global Outcomes 2012, the standard during the study period), nonfatal myocardial infarction, nonfatal stroke, and surgical site infections, which were identified from the discharge summary written by the primary surgery service.19 All-cause mortality also was collected.

Patients were included if they were admitted for major elective surgeries and had a diagnosis of either type 1 or type 2 DM on their problem list, determined by International Classification of Diseases, Tenth Revision codes. Major elective surgery was defined as a procedure that would likely result in a hospital admission of > 24 hours. Of note, patients may have been included in this study more than once if they had > 1 procedure at least 30 days apart and met inclusion criteria within the time frame. Patients were excluded if they were taking no DM medications or chronic steroids (at any dose), residing in a long-term care facility, being managed by a non-VA clinician prior to surgery, or missing a preoperative blood glucose measurement.

All data were collected from the CPRS. A list of surgical cases involving patients with DM who were scheduled to undergo major elective surgeries from January 1, 2018, to December 31, 2021, at VHI was generated. The list was randomized to a smaller number (N = 394) for data collection due to the time and resource constraints for a pharmacy residency project. All data were deidentified and stored in a secured VA server to protect patient confidentiality. Descriptive statistics were used for all results.

Results

Initially, 2362 surgeries were identified. A randomized sample of 394 charts were reviewed and 131 cases met inclusion criteria. Each case involved a unique patient (Figure). The most common reasons for exclusion were 143 patients with diet-controlled DM and 78 nonelective surgeries. The mean (SD) age of patients was 68 (8) years, and the most were male (98.5%) and White (76.3%) (Table 1). 

1125FED-DM-Preop-F1
FIGURE. Patient Selection
1125FED-DM-Preop-T1

At baseline, 45 of 131 patients (34.4%) had coronary artery disease and 29 (22.1%) each had autonomic neuropathy and chronic kidney disease. Most surgeries were conducted by orthopedic (32.1%) and peripheral vascular (21.4%) specialties. The mean (SD) length of surgery was 4.6 (2.6) hours and of hospital length of stay was 4 (4) days. No patients stayed longer than the 30-day safety outcome follow-up period. All patients had type 2 DM and took a mean 2 DM medications. The 63 patients taking insulin had a mean (SD) total daily dose of 99 (77) U (Table 2). A preoperative HbA1c was collected in 116 patients within 3 months of surgery, with a mean HbA1c of 7.0% (range, 5.3-10.7).

1125FED-DM-Preop-T2

No patients had surgeries delayed or canceled because of uncontrolled DM on the day of surgery. The mean preoperative blood glucose level was 146 mg/dL (range, 73-365) (Table 3). No patients had a preoperative blood glucose level of < 70 mg/dL and 19 (14.5%) had a blood glucose level > 180 mg/dL. Among patients with hyperglycemia immediately prior to surgery, 6 (31.6%) had documentation of insulin being provided.

1125FED-DM-Preop-T3

For this sample of patients, the preoperative clinic visit was conducted a mean 22 days prior to the planned surgery date. Among the 131 included patients, 122 (93.1%) had documentation of receiving instructions for DM medications. Among patients who had documented receipt of instructions, only 30 (24.6%) had instructions specifically tailored to their regimen rather than a generic templated form. The mean (SD) preoperative blood glucose was similar for those who received specific perioperative DM instructions at 146 (50) mg/dL when compared with those who did not at 147 (45) mg/dL. The mean (SD) preoperative blood glucose reading for those who had no documentation of receipt of perioperative instructions was 126 (54) mg/dL compared with 147 (46) mg/dL for those who did.

The mean number of postoperative blood glucose events per day was negligible for hypoglycemia and more frequent for hyperglycemia with a mean of 2 events per day. The mean postoperative blood glucose range was 121 to 247 mg/dL with most readings < 180 mg/dL. Upon discharge, most patients continued their home DM regimen with 5 patients (3.8%) having changes made to their regimen upon discharge.

Very few postoperative complications were identified from chart review. The most frequently observed postoperative complications were acute kidney injury, surgical site infections, and nonfatal stroke. There were no documented nonfatal myocardial infarctions. Two patients (1.5%) died within 30 days of the surgery; neither death was deemed to have been related to poor perioperative glycemic control.

Discussion

To our knowledge, this retrospective chart review was the first study to assess preoperative DM management and postoperative complications in a veteran population. VHI is a large, tertiary, level 1a, academic medical center that serves approximately 62,000 veterans annually and performs about 5000 to 6000 surgeries annually, a total that is increasing following the COVID-19 pandemic.20 This study found that the current process of a presurgery clinic visit and day of surgery glucose assessment has prevented surgical delays or cancellations.

Most patients included in this study were well controlled at baseline in accordance with the 2025 ADA SOC HbA1c recommendation of a preoperative HbA1c of < 8%, which may have contributed to no surgical delays or cancellations.10 However, not all patients had HbA1c collected within 3 months of surgery or even had one collected at all. Despite the ADA SOC providing no explicit recommendation for universal HbA1c screening prior to elective procedures, its importance cannot be understated given the body of evidence demonstrating poor outcomes with uncontrolled preoperative DM.8,10 The glycemic control at baseline may have contributed to the very few postsurgical complications observed in this study.

Although the current process at VHI prevented surgical delays and cancellations in this sample, there are still identified areas for improvement. One area is the instructions the patients received. Patients with DM are often prescribed ≥ 1 medication or a combination of insulins, noninsulin injectables, and oral DM medications, and this study population was no different. Because these medications may influence the anesthesia and perioperative periods, the ADA has specific guidance for altering administration schedules in the days leading up to surgery.10

Inappropriate administration of DM medications could lead to perioperative hypoglycemia or hyperglycemia, possibly causing surgical delays, case cancellations, and/or postoperative complications.21 Although these data reveal the specificity and documented receipt that the preoperative DM instructions did not impact the first recorded preoperative blood glucose, future studies should examine patient confidence in how to properly administer their DM medications prior to surgery. It is vital that patients receive clear instructions in accordance with the ADA SOC on whether to continue, hold, or adjust the dose of their medications to prevent fluctuations in blood glucose levels in the perioperative period, ensure safety with anesthesia, and prevent postoperative complications such as acute kidney injury. Of note, compliance with guideline recommendations for medication instructions was not examined because the data collection time frame expanded over multiple years and the recommendations have evolved each year as new data emerge.

Preoperative DM Management

The first key takeaway from this study is to ensure patients are ready for surgery with a formal assessment (typically in the form of a clinic visit) prior to the surgery. One private sector health system published their approach to this by administering an automatic preoperative HbA1c screening for those with a DM diagnosis and all patients with a random plasma glucose ≥ 200 mg/dL.22 Additionally, if the patient's HbA1c level was not at goal prior to surgery (≥ 8% for those with known DM and ≥ 6.5% with no known DM), patients were referred to endocrinology for further management. Increasing attention to the preoperative visit and extending HbA1c testing to all patients regardless of DM status also provides an opportunity to identify individuals living with undiagnosed DM.1

Even though there was no difference in the mean preoperative blood glucose level based on receipt or specificity of preoperative DM instructions, a second takeaway from this study is the importance of ensuring patients receive clear instructions on their DM medication schedule in the perioperative period. A practical first step may be updating the templates used by the primary surgery teams and providing education to the clinicians in the clinic on how to personalize the visits. Because the current preoperative DM process at VHI is managed by the primary surgical team in a clinic visit, there is an opportunity to shift this responsibility to other health care professionals, such as pharmacists—a change shown to reduce unintended omission of home medications following surgery during hospitalization and reduce costs.23,24

Limitations

This study relied on data included in the patient chart. These data include medication interventions made immediately prior to surgery, which can sometimes be inaccurately charted or difficult to find as they are not documented in the typical medication administration record. Also, the safety outcomes were collected from a discharge summary written by different clinicians, which may lead to information bias. Special attention was taken to ensure these data points were collected as accurately as possible, but it is possible some data may be inaccurate from unintentional human error. Additionally, the safety outcome was limited to a 30-day follow-up, but encompassed the entire length of postoperative stay for all included patients. Finally, given this study was retrospective with no comparison group and the intent was to improve processes at VHI, only hypotheses and potential interventions can be generated from this study. Future prospective studies with larger sample sizes and comparator groups are needed to draw further conclusions.

Conclusions

This study found that the current presurgery process at VHI appears to be successful in preventing surgical delays or cancellations due to hyperglycemia or hypoglycemia. Optimizing DM management can improve surgical outcomes by decreasing rates of postoperative complications, and this study added additional evidence in support of that in a unique population: veterans. Insight on the awareness of preoperative blood glucose management should be gleaned from this study, and based on this sample and site, the preadmission screening process and instructions provided to patients can serve as 2 starting points for optimizing elective surgery.

References
  1. Centers for Disease Control and Prevention. Diabetes basics. May 15, 2024. Accessed September 24, 2025. https://www.cdc.gov/diabetes/about/index.html
  2. Liu Y, Sayam S, Shao X, et al. Prevalence of and trends in diabetes among veterans, United States, 2005-2014. Prev Chronic Dis. 2017;14:E135. doi:10.5888/pcd14.170230
  3. Farmaki P, Damaskos C, Garmpis N, et al . Complications of the Type 2 Diabetes Mellitus. Curr Cardiol Rev. 2020;16(4):249-251. doi:10.2174/1573403X1604201229115531
  4. Frisch A, Chandra P, Smiley D, et al. Prevalence and clinical outcome of hyperglycemia in the perioperative period in noncardiac surgery. Diabetes Care. 2010;33:1783-1788. doi:10.2337/dc10-0304
  5. Noordzij PG, Boersma E, Schreiner F, et al. Increased preoperative glucose levels are associated with perioperative mortality in patients undergoing noncardiac, nonvascular surgery. Eur J Endocrinol. 2007;156:137 -142. doi:10.1530/eje.1.02321
  6. Pomposelli JJ, Baxter JK 3rd, Babineau TJ, et al. Early postoperative glucose control predicts nosocomial infection rate in diabetic patients. JPEN J Parenter Enteral Nutr. 1998;22:77-81. doi:10.1177/01486071980220027
  7. Umpierrez GE, Smiley D, Jacobs S, et al. Randomized study of basal-bolus insulin therapy in the inpatient management of patients with type 2 diabetes undergoing general surgery (RABBIT 2 surgery). Diabetes Care. 2011;34:256-261. doi:10.2337/dc10-1407
  8. Pasquel FJ, Gomez-Huelgas R, Anzola I, et al. Predictive value of admission hemoglobin A1c on inpatient glycemic control and response to insulin therapy in medicine and surgery patients with type 2 diabetes. Diabetes Care. 2015;38:e202-e203. doi:10.2337/dc15-1835
  9. Alexiewicz JM, Kumar D, Smogorzewski M, et al. Polymorphonuclear leukocytes in non-insulin-dependent diabetes mellitus: abnormalities in metabolism and function. Ann Intern Med. 1995;123:919-924. doi:10.7326/0003-4819-123-12-199512150-00004
  10. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Medical Care in Diabetes—2025. Diabetes Care. 2025;48(1 suppl 1):S321-S334. doi:10.2337/dc25-S016
  11. Kumar R, Gandhi R. Reasons for cancellation of operation on the day of intended surgery in a multidisciplinary 500 bedded hospital. J Anaesthesiol Clin Pharmacol. 2012;28:66-69. doi:10.4103/0970-9185.92442
  12. American Diabetes Association. 14. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2018. Diabetes Care. 2018;41(1 suppl 1):S144- S151. doi:10.2337/dc18-S014
  13. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2019. Diabetes Care. 2019;42(suppl 1):S173- S181. doi:10.2337/dc19-S015
  14. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2020. Diabetes Care. 2020;43(suppl 1):S193- S202. doi:10.2337/dc20-S015
  15. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2021. Diabetes Care. 2021;44(suppl 1):S211- S220. doi:10.2337/dc21-S015
  16. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Medical Care in Diabetes—2022. Diabetes Care. 2022;45(suppl 1):S244-S253. doi:10.2337/dc22-S016
  17. ElSayed NA, Aleppo G, Aroda VR, et al. 16. Diabetes care in the hospital: Standards of Care in Diabetes—2023. Diabetes Care. 2023;46(suppl 1):S267-S278. doi:10.2337/dc23-S016
  18. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Care in Diabetes—2024. Diabetes Care. 2024;47(suppl 1):S295-S306. doi:10.2337/dc24-S016
  19. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int Suppl. 2012;2:1-138. Accessed September 24, 2025. https:// www.kisupplements.org/issue/S2157-1716(12)X7200-9
  20. US Department of Veterans Affairs. VA Indiana Healthcare: about us. Accessed September 24, 2025. https:// www.va.gov/indiana-health-care/about-us/
  21. Koh WX, Phelan R, Hopman WM, et al. Cancellation of elective surgery: rates, reasons and effect on patient satisfaction. Can J Surg. 2021;64:E155-E161. doi:10.1503/cjs.008119
  22. Pai S-L, Haehn DA, Pitruzzello NE, et al. Reducing infection rates with enhanced preoperative diabetes mellitus diagnosis and optimization processes. South Med J. 2023;116:215-219. doi:10.14423/SMJ.0000000000001507
  23. Forrester TG, Sullivan S, Snoswell CL, et al. Integrating a pharmacist into the perioperative setting. Aust Health Rev. 2020;44:563-568. doi:10.1071/AH19126
  24. Hale AR, Coombes ID, Stokes J, et al. Perioperative medication management: expanding the role of the preadmission clinic pharmacist in a single centre, randomised controlled trial of collaborative prescribing. BMJ Open. 2013;3:e003027. doi:10.1136/bmjopen-2013-003027
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Author affiliations: aUniversity of Nebraska Medical Center College of Pharmacy, Omaha

bVeteran Health Indiana, Indianapolis

cPurdue University College of Pharmacy, West Lafayette, Indiana

dHospital of the University of Pennsylvania, Philadelphia

Author disclosures: The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Chelsea Huppert (chuppert@unmc.edu)

Fed Pract. 2025;42(suppl 6). Published online November 7. doi:10.12788/fp.0645

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Chelsea A. Huppert, PharmDa; Emily A. Moore, PharmD, BCACPb; Deanna S. Kania, PharmD, BCPS, BCACPb,c; Kayla Cann, PharmDd; Christopher A. Knefelkamp, PharmD, BCPSb

Author affiliations: aUniversity of Nebraska Medical Center College of Pharmacy, Omaha

bVeteran Health Indiana, Indianapolis

cPurdue University College of Pharmacy, West Lafayette, Indiana

dHospital of the University of Pennsylvania, Philadelphia

Author disclosures: The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Chelsea Huppert (chuppert@unmc.edu)

Fed Pract. 2025;42(suppl 6). Published online November 7. doi:10.12788/fp.0645

Author and Disclosure Information

Chelsea A. Huppert, PharmDa; Emily A. Moore, PharmD, BCACPb; Deanna S. Kania, PharmD, BCPS, BCACPb,c; Kayla Cann, PharmDd; Christopher A. Knefelkamp, PharmD, BCPSb

Author affiliations: aUniversity of Nebraska Medical Center College of Pharmacy, Omaha

bVeteran Health Indiana, Indianapolis

cPurdue University College of Pharmacy, West Lafayette, Indiana

dHospital of the University of Pennsylvania, Philadelphia

Author disclosures: The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Chelsea Huppert (chuppert@unmc.edu)

Fed Pract. 2025;42(suppl 6). Published online November 7. doi:10.12788/fp.0645

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More than 38 million people in the United States (12%) have diabetes mellitus (DM), though 1 in 5 are unaware they have DM.1 The prevalence among veterans is even more substantial, impacting nearly 25% of those who received care from the US Department of Veterans Affairs (VA).2 DM can lead to increased health care costs in addition to various complications (eg, cardiovascular, renal), especially if left uncontrolled.1,3 similar impact is found in the perioperative period (defined as at or around the time of an operation), as multiple studies have found that uncontrolled preoperative DM can result in worsened surgical outcomes, including longer hospital stays, more infectious complications, and higher perioperative mortality.4-6

In contrast, adequate glycemic control assessed with blood glucose levels has been shown to decrease the incidence of postoperative infections.7 Optimizing glycemic control during hospital stays, especially postsurgery, has become the standard of care, with most health systems establishing specific protocols. In current literature, most studies examining DM management in the perioperative period are focused on postoperative care, with little attention to the preoperative period.4,6,7

One study found that patients with poor presurgery glycemic control assessed by hemoglobin A1c (HbA1c) levels were more likely to remain hyperglycemic during and after surgery. 8 Blood glucose levels < 200 mg/dL can lead to an increased risk of infection and impaired wound healing, meaning a well-controlled HbA1c before a procedure serves as a potential factor for success.9 The 2025 American Diabetes Association (ADA) Standards of Care (SOC) recommendation is to target HbA1c < 8% whenever possible, and some health systems require lower levels (eg, < 7% or 7.5%).10 With that goal in mind and knowing that preoperative hyperglycemia has been shown to be a contributing factor in the delay or cancellation of surgical cases, an argument can be made that attention to preoperative DM management also should be a focus for health care systems performing surgeries.8,9,11

Attention to glucose control during preoperative care offers an opportunity to screen for DM in patients who may not have been screened otherwise and to standardize perioperative DM management. Since DM disproportionately impacts veterans, this is a pertinent issue to the VA. Veterans can be more susceptible to complications if DM is left uncontrolled prior to surgery. To determine readiness for surgery and control of comorbid conditions such as DM before a planned surgery, facilities often perform a preoperative clinic assessment, often in a multidisciplinary clinic.

At Veteran Health Indiana (VHI), a presurgery clinic visit involving the primary surgery service (physician, nurse practitioner, and/or a physician assistant) is conducted 1 to 2 months prior to the planned procedure to determine whether a patient is ready for surgery. During this visit, patients receive a packet with instructions for various tasks and medications, such as applying topical antibiotic prophylaxis on the anticipated surgical site. This is documented in the form of a note in the VHI Computerized Patient Record System (CPRS). The medication instructions are provided according to the preferences of the surgical team. These may be templated notes that contain general directions on the timing and dosing of specific medications, in addition to instructions for holding or reducing doses when appropriate. The instructions can be tailored by the team conducting the preoperative visit (eg, “Take 20 units of insulin glargine the day before surgery” vs “Take half of your long-acting insulin the night before surgery”). Specific to DM, VHI has a nurse-driven day of surgery glucose assessment where point-of-care blood glucose is collected during preoperative holding for most patients.

There is limited research assessing the level of preoperative glycemic control and the incidence of complications in a veteran population. The objective of this study was to gain a baseline understanding of what, if any, standardization exists for preoperative instructions for DM medications and to assess the level of preoperative glycemic control and postoperative complications in patients with DM undergoing major elective surgical procedures.

Methods

This retrospective, single-center chart review was conducted at VHI. The Indiana University and VHI institutional review boards determined that this quality improvement project was exempt from review.

The primary outcome was the number of patients with surgical procedures delayed or canceled due to hyperglycemia or hypoglycemia. Hyperglycemia was defined as blood glucose > 180 mg/dL and hypoglycemia was defined as < 70 mg/dL, slight variations from the current ADA SOC preoperative specific recommendation of a blood glucose reading of 100 to 180 mg/dL within 4 hours of surgery.10 The standard outpatient hypoglycemia definition of blood glucose < 70 mg/dL was chosen because the current goal (< 100 mg/dL) was not the standard in previous ADA SOCs that were in place during the study period. Specifically, the 2018 ADA SOC did not provide preoperative recommendations and the 2019-2021 ADA SOC recommended 80 to 180 mg/dL.10,12-18 For patients who had multiple preoperative blood glucose measurements, the first recorded glucose on the day of the procedure was used.

The secondary outcomes of this study were focused on the preoperative process/care at VHI and postoperative glycemic control. The preoperative process included examining whether medication instructions were given and their quality. Additionally, the number of interventions for hyperglycemia and hypoglycemia were required immediately prior to surgery and the average preoperative HbA1c (measured within 3 months prior to surgery) were collected and analyzed. For postoperative glycemic control, average blood glucose measurements and number of hypoglycemic (< 70 mg/dL) and hyperglycemic (> 180 mg/dL) events were measured in addition to the frequency of changes made at discharge to patients’ DM medication regimens.

The safety outcome of this study assessed commonly observed postoperative complications and was examined up to 30 days postsurgery. These included acute kidney injury (defined using Kidney Disease: Improving Global Outcomes 2012, the standard during the study period), nonfatal myocardial infarction, nonfatal stroke, and surgical site infections, which were identified from the discharge summary written by the primary surgery service.19 All-cause mortality also was collected.

Patients were included if they were admitted for major elective surgeries and had a diagnosis of either type 1 or type 2 DM on their problem list, determined by International Classification of Diseases, Tenth Revision codes. Major elective surgery was defined as a procedure that would likely result in a hospital admission of > 24 hours. Of note, patients may have been included in this study more than once if they had > 1 procedure at least 30 days apart and met inclusion criteria within the time frame. Patients were excluded if they were taking no DM medications or chronic steroids (at any dose), residing in a long-term care facility, being managed by a non-VA clinician prior to surgery, or missing a preoperative blood glucose measurement.

All data were collected from the CPRS. A list of surgical cases involving patients with DM who were scheduled to undergo major elective surgeries from January 1, 2018, to December 31, 2021, at VHI was generated. The list was randomized to a smaller number (N = 394) for data collection due to the time and resource constraints for a pharmacy residency project. All data were deidentified and stored in a secured VA server to protect patient confidentiality. Descriptive statistics were used for all results.

Results

Initially, 2362 surgeries were identified. A randomized sample of 394 charts were reviewed and 131 cases met inclusion criteria. Each case involved a unique patient (Figure). The most common reasons for exclusion were 143 patients with diet-controlled DM and 78 nonelective surgeries. The mean (SD) age of patients was 68 (8) years, and the most were male (98.5%) and White (76.3%) (Table 1). 

1125FED-DM-Preop-F1
FIGURE. Patient Selection
1125FED-DM-Preop-T1

At baseline, 45 of 131 patients (34.4%) had coronary artery disease and 29 (22.1%) each had autonomic neuropathy and chronic kidney disease. Most surgeries were conducted by orthopedic (32.1%) and peripheral vascular (21.4%) specialties. The mean (SD) length of surgery was 4.6 (2.6) hours and of hospital length of stay was 4 (4) days. No patients stayed longer than the 30-day safety outcome follow-up period. All patients had type 2 DM and took a mean 2 DM medications. The 63 patients taking insulin had a mean (SD) total daily dose of 99 (77) U (Table 2). A preoperative HbA1c was collected in 116 patients within 3 months of surgery, with a mean HbA1c of 7.0% (range, 5.3-10.7).

1125FED-DM-Preop-T2

No patients had surgeries delayed or canceled because of uncontrolled DM on the day of surgery. The mean preoperative blood glucose level was 146 mg/dL (range, 73-365) (Table 3). No patients had a preoperative blood glucose level of < 70 mg/dL and 19 (14.5%) had a blood glucose level > 180 mg/dL. Among patients with hyperglycemia immediately prior to surgery, 6 (31.6%) had documentation of insulin being provided.

1125FED-DM-Preop-T3

For this sample of patients, the preoperative clinic visit was conducted a mean 22 days prior to the planned surgery date. Among the 131 included patients, 122 (93.1%) had documentation of receiving instructions for DM medications. Among patients who had documented receipt of instructions, only 30 (24.6%) had instructions specifically tailored to their regimen rather than a generic templated form. The mean (SD) preoperative blood glucose was similar for those who received specific perioperative DM instructions at 146 (50) mg/dL when compared with those who did not at 147 (45) mg/dL. The mean (SD) preoperative blood glucose reading for those who had no documentation of receipt of perioperative instructions was 126 (54) mg/dL compared with 147 (46) mg/dL for those who did.

The mean number of postoperative blood glucose events per day was negligible for hypoglycemia and more frequent for hyperglycemia with a mean of 2 events per day. The mean postoperative blood glucose range was 121 to 247 mg/dL with most readings < 180 mg/dL. Upon discharge, most patients continued their home DM regimen with 5 patients (3.8%) having changes made to their regimen upon discharge.

Very few postoperative complications were identified from chart review. The most frequently observed postoperative complications were acute kidney injury, surgical site infections, and nonfatal stroke. There were no documented nonfatal myocardial infarctions. Two patients (1.5%) died within 30 days of the surgery; neither death was deemed to have been related to poor perioperative glycemic control.

Discussion

To our knowledge, this retrospective chart review was the first study to assess preoperative DM management and postoperative complications in a veteran population. VHI is a large, tertiary, level 1a, academic medical center that serves approximately 62,000 veterans annually and performs about 5000 to 6000 surgeries annually, a total that is increasing following the COVID-19 pandemic.20 This study found that the current process of a presurgery clinic visit and day of surgery glucose assessment has prevented surgical delays or cancellations.

Most patients included in this study were well controlled at baseline in accordance with the 2025 ADA SOC HbA1c recommendation of a preoperative HbA1c of < 8%, which may have contributed to no surgical delays or cancellations.10 However, not all patients had HbA1c collected within 3 months of surgery or even had one collected at all. Despite the ADA SOC providing no explicit recommendation for universal HbA1c screening prior to elective procedures, its importance cannot be understated given the body of evidence demonstrating poor outcomes with uncontrolled preoperative DM.8,10 The glycemic control at baseline may have contributed to the very few postsurgical complications observed in this study.

Although the current process at VHI prevented surgical delays and cancellations in this sample, there are still identified areas for improvement. One area is the instructions the patients received. Patients with DM are often prescribed ≥ 1 medication or a combination of insulins, noninsulin injectables, and oral DM medications, and this study population was no different. Because these medications may influence the anesthesia and perioperative periods, the ADA has specific guidance for altering administration schedules in the days leading up to surgery.10

Inappropriate administration of DM medications could lead to perioperative hypoglycemia or hyperglycemia, possibly causing surgical delays, case cancellations, and/or postoperative complications.21 Although these data reveal the specificity and documented receipt that the preoperative DM instructions did not impact the first recorded preoperative blood glucose, future studies should examine patient confidence in how to properly administer their DM medications prior to surgery. It is vital that patients receive clear instructions in accordance with the ADA SOC on whether to continue, hold, or adjust the dose of their medications to prevent fluctuations in blood glucose levels in the perioperative period, ensure safety with anesthesia, and prevent postoperative complications such as acute kidney injury. Of note, compliance with guideline recommendations for medication instructions was not examined because the data collection time frame expanded over multiple years and the recommendations have evolved each year as new data emerge.

Preoperative DM Management

The first key takeaway from this study is to ensure patients are ready for surgery with a formal assessment (typically in the form of a clinic visit) prior to the surgery. One private sector health system published their approach to this by administering an automatic preoperative HbA1c screening for those with a DM diagnosis and all patients with a random plasma glucose ≥ 200 mg/dL.22 Additionally, if the patient's HbA1c level was not at goal prior to surgery (≥ 8% for those with known DM and ≥ 6.5% with no known DM), patients were referred to endocrinology for further management. Increasing attention to the preoperative visit and extending HbA1c testing to all patients regardless of DM status also provides an opportunity to identify individuals living with undiagnosed DM.1

Even though there was no difference in the mean preoperative blood glucose level based on receipt or specificity of preoperative DM instructions, a second takeaway from this study is the importance of ensuring patients receive clear instructions on their DM medication schedule in the perioperative period. A practical first step may be updating the templates used by the primary surgery teams and providing education to the clinicians in the clinic on how to personalize the visits. Because the current preoperative DM process at VHI is managed by the primary surgical team in a clinic visit, there is an opportunity to shift this responsibility to other health care professionals, such as pharmacists—a change shown to reduce unintended omission of home medications following surgery during hospitalization and reduce costs.23,24

Limitations

This study relied on data included in the patient chart. These data include medication interventions made immediately prior to surgery, which can sometimes be inaccurately charted or difficult to find as they are not documented in the typical medication administration record. Also, the safety outcomes were collected from a discharge summary written by different clinicians, which may lead to information bias. Special attention was taken to ensure these data points were collected as accurately as possible, but it is possible some data may be inaccurate from unintentional human error. Additionally, the safety outcome was limited to a 30-day follow-up, but encompassed the entire length of postoperative stay for all included patients. Finally, given this study was retrospective with no comparison group and the intent was to improve processes at VHI, only hypotheses and potential interventions can be generated from this study. Future prospective studies with larger sample sizes and comparator groups are needed to draw further conclusions.

Conclusions

This study found that the current presurgery process at VHI appears to be successful in preventing surgical delays or cancellations due to hyperglycemia or hypoglycemia. Optimizing DM management can improve surgical outcomes by decreasing rates of postoperative complications, and this study added additional evidence in support of that in a unique population: veterans. Insight on the awareness of preoperative blood glucose management should be gleaned from this study, and based on this sample and site, the preadmission screening process and instructions provided to patients can serve as 2 starting points for optimizing elective surgery.

More than 38 million people in the United States (12%) have diabetes mellitus (DM), though 1 in 5 are unaware they have DM.1 The prevalence among veterans is even more substantial, impacting nearly 25% of those who received care from the US Department of Veterans Affairs (VA).2 DM can lead to increased health care costs in addition to various complications (eg, cardiovascular, renal), especially if left uncontrolled.1,3 similar impact is found in the perioperative period (defined as at or around the time of an operation), as multiple studies have found that uncontrolled preoperative DM can result in worsened surgical outcomes, including longer hospital stays, more infectious complications, and higher perioperative mortality.4-6

In contrast, adequate glycemic control assessed with blood glucose levels has been shown to decrease the incidence of postoperative infections.7 Optimizing glycemic control during hospital stays, especially postsurgery, has become the standard of care, with most health systems establishing specific protocols. In current literature, most studies examining DM management in the perioperative period are focused on postoperative care, with little attention to the preoperative period.4,6,7

One study found that patients with poor presurgery glycemic control assessed by hemoglobin A1c (HbA1c) levels were more likely to remain hyperglycemic during and after surgery. 8 Blood glucose levels < 200 mg/dL can lead to an increased risk of infection and impaired wound healing, meaning a well-controlled HbA1c before a procedure serves as a potential factor for success.9 The 2025 American Diabetes Association (ADA) Standards of Care (SOC) recommendation is to target HbA1c < 8% whenever possible, and some health systems require lower levels (eg, < 7% or 7.5%).10 With that goal in mind and knowing that preoperative hyperglycemia has been shown to be a contributing factor in the delay or cancellation of surgical cases, an argument can be made that attention to preoperative DM management also should be a focus for health care systems performing surgeries.8,9,11

Attention to glucose control during preoperative care offers an opportunity to screen for DM in patients who may not have been screened otherwise and to standardize perioperative DM management. Since DM disproportionately impacts veterans, this is a pertinent issue to the VA. Veterans can be more susceptible to complications if DM is left uncontrolled prior to surgery. To determine readiness for surgery and control of comorbid conditions such as DM before a planned surgery, facilities often perform a preoperative clinic assessment, often in a multidisciplinary clinic.

At Veteran Health Indiana (VHI), a presurgery clinic visit involving the primary surgery service (physician, nurse practitioner, and/or a physician assistant) is conducted 1 to 2 months prior to the planned procedure to determine whether a patient is ready for surgery. During this visit, patients receive a packet with instructions for various tasks and medications, such as applying topical antibiotic prophylaxis on the anticipated surgical site. This is documented in the form of a note in the VHI Computerized Patient Record System (CPRS). The medication instructions are provided according to the preferences of the surgical team. These may be templated notes that contain general directions on the timing and dosing of specific medications, in addition to instructions for holding or reducing doses when appropriate. The instructions can be tailored by the team conducting the preoperative visit (eg, “Take 20 units of insulin glargine the day before surgery” vs “Take half of your long-acting insulin the night before surgery”). Specific to DM, VHI has a nurse-driven day of surgery glucose assessment where point-of-care blood glucose is collected during preoperative holding for most patients.

There is limited research assessing the level of preoperative glycemic control and the incidence of complications in a veteran population. The objective of this study was to gain a baseline understanding of what, if any, standardization exists for preoperative instructions for DM medications and to assess the level of preoperative glycemic control and postoperative complications in patients with DM undergoing major elective surgical procedures.

Methods

This retrospective, single-center chart review was conducted at VHI. The Indiana University and VHI institutional review boards determined that this quality improvement project was exempt from review.

The primary outcome was the number of patients with surgical procedures delayed or canceled due to hyperglycemia or hypoglycemia. Hyperglycemia was defined as blood glucose > 180 mg/dL and hypoglycemia was defined as < 70 mg/dL, slight variations from the current ADA SOC preoperative specific recommendation of a blood glucose reading of 100 to 180 mg/dL within 4 hours of surgery.10 The standard outpatient hypoglycemia definition of blood glucose < 70 mg/dL was chosen because the current goal (< 100 mg/dL) was not the standard in previous ADA SOCs that were in place during the study period. Specifically, the 2018 ADA SOC did not provide preoperative recommendations and the 2019-2021 ADA SOC recommended 80 to 180 mg/dL.10,12-18 For patients who had multiple preoperative blood glucose measurements, the first recorded glucose on the day of the procedure was used.

The secondary outcomes of this study were focused on the preoperative process/care at VHI and postoperative glycemic control. The preoperative process included examining whether medication instructions were given and their quality. Additionally, the number of interventions for hyperglycemia and hypoglycemia were required immediately prior to surgery and the average preoperative HbA1c (measured within 3 months prior to surgery) were collected and analyzed. For postoperative glycemic control, average blood glucose measurements and number of hypoglycemic (< 70 mg/dL) and hyperglycemic (> 180 mg/dL) events were measured in addition to the frequency of changes made at discharge to patients’ DM medication regimens.

The safety outcome of this study assessed commonly observed postoperative complications and was examined up to 30 days postsurgery. These included acute kidney injury (defined using Kidney Disease: Improving Global Outcomes 2012, the standard during the study period), nonfatal myocardial infarction, nonfatal stroke, and surgical site infections, which were identified from the discharge summary written by the primary surgery service.19 All-cause mortality also was collected.

Patients were included if they were admitted for major elective surgeries and had a diagnosis of either type 1 or type 2 DM on their problem list, determined by International Classification of Diseases, Tenth Revision codes. Major elective surgery was defined as a procedure that would likely result in a hospital admission of > 24 hours. Of note, patients may have been included in this study more than once if they had > 1 procedure at least 30 days apart and met inclusion criteria within the time frame. Patients were excluded if they were taking no DM medications or chronic steroids (at any dose), residing in a long-term care facility, being managed by a non-VA clinician prior to surgery, or missing a preoperative blood glucose measurement.

All data were collected from the CPRS. A list of surgical cases involving patients with DM who were scheduled to undergo major elective surgeries from January 1, 2018, to December 31, 2021, at VHI was generated. The list was randomized to a smaller number (N = 394) for data collection due to the time and resource constraints for a pharmacy residency project. All data were deidentified and stored in a secured VA server to protect patient confidentiality. Descriptive statistics were used for all results.

Results

Initially, 2362 surgeries were identified. A randomized sample of 394 charts were reviewed and 131 cases met inclusion criteria. Each case involved a unique patient (Figure). The most common reasons for exclusion were 143 patients with diet-controlled DM and 78 nonelective surgeries. The mean (SD) age of patients was 68 (8) years, and the most were male (98.5%) and White (76.3%) (Table 1). 

1125FED-DM-Preop-F1
FIGURE. Patient Selection
1125FED-DM-Preop-T1

At baseline, 45 of 131 patients (34.4%) had coronary artery disease and 29 (22.1%) each had autonomic neuropathy and chronic kidney disease. Most surgeries were conducted by orthopedic (32.1%) and peripheral vascular (21.4%) specialties. The mean (SD) length of surgery was 4.6 (2.6) hours and of hospital length of stay was 4 (4) days. No patients stayed longer than the 30-day safety outcome follow-up period. All patients had type 2 DM and took a mean 2 DM medications. The 63 patients taking insulin had a mean (SD) total daily dose of 99 (77) U (Table 2). A preoperative HbA1c was collected in 116 patients within 3 months of surgery, with a mean HbA1c of 7.0% (range, 5.3-10.7).

1125FED-DM-Preop-T2

No patients had surgeries delayed or canceled because of uncontrolled DM on the day of surgery. The mean preoperative blood glucose level was 146 mg/dL (range, 73-365) (Table 3). No patients had a preoperative blood glucose level of < 70 mg/dL and 19 (14.5%) had a blood glucose level > 180 mg/dL. Among patients with hyperglycemia immediately prior to surgery, 6 (31.6%) had documentation of insulin being provided.

1125FED-DM-Preop-T3

For this sample of patients, the preoperative clinic visit was conducted a mean 22 days prior to the planned surgery date. Among the 131 included patients, 122 (93.1%) had documentation of receiving instructions for DM medications. Among patients who had documented receipt of instructions, only 30 (24.6%) had instructions specifically tailored to their regimen rather than a generic templated form. The mean (SD) preoperative blood glucose was similar for those who received specific perioperative DM instructions at 146 (50) mg/dL when compared with those who did not at 147 (45) mg/dL. The mean (SD) preoperative blood glucose reading for those who had no documentation of receipt of perioperative instructions was 126 (54) mg/dL compared with 147 (46) mg/dL for those who did.

The mean number of postoperative blood glucose events per day was negligible for hypoglycemia and more frequent for hyperglycemia with a mean of 2 events per day. The mean postoperative blood glucose range was 121 to 247 mg/dL with most readings < 180 mg/dL. Upon discharge, most patients continued their home DM regimen with 5 patients (3.8%) having changes made to their regimen upon discharge.

Very few postoperative complications were identified from chart review. The most frequently observed postoperative complications were acute kidney injury, surgical site infections, and nonfatal stroke. There were no documented nonfatal myocardial infarctions. Two patients (1.5%) died within 30 days of the surgery; neither death was deemed to have been related to poor perioperative glycemic control.

Discussion

To our knowledge, this retrospective chart review was the first study to assess preoperative DM management and postoperative complications in a veteran population. VHI is a large, tertiary, level 1a, academic medical center that serves approximately 62,000 veterans annually and performs about 5000 to 6000 surgeries annually, a total that is increasing following the COVID-19 pandemic.20 This study found that the current process of a presurgery clinic visit and day of surgery glucose assessment has prevented surgical delays or cancellations.

Most patients included in this study were well controlled at baseline in accordance with the 2025 ADA SOC HbA1c recommendation of a preoperative HbA1c of < 8%, which may have contributed to no surgical delays or cancellations.10 However, not all patients had HbA1c collected within 3 months of surgery or even had one collected at all. Despite the ADA SOC providing no explicit recommendation for universal HbA1c screening prior to elective procedures, its importance cannot be understated given the body of evidence demonstrating poor outcomes with uncontrolled preoperative DM.8,10 The glycemic control at baseline may have contributed to the very few postsurgical complications observed in this study.

Although the current process at VHI prevented surgical delays and cancellations in this sample, there are still identified areas for improvement. One area is the instructions the patients received. Patients with DM are often prescribed ≥ 1 medication or a combination of insulins, noninsulin injectables, and oral DM medications, and this study population was no different. Because these medications may influence the anesthesia and perioperative periods, the ADA has specific guidance for altering administration schedules in the days leading up to surgery.10

Inappropriate administration of DM medications could lead to perioperative hypoglycemia or hyperglycemia, possibly causing surgical delays, case cancellations, and/or postoperative complications.21 Although these data reveal the specificity and documented receipt that the preoperative DM instructions did not impact the first recorded preoperative blood glucose, future studies should examine patient confidence in how to properly administer their DM medications prior to surgery. It is vital that patients receive clear instructions in accordance with the ADA SOC on whether to continue, hold, or adjust the dose of their medications to prevent fluctuations in blood glucose levels in the perioperative period, ensure safety with anesthesia, and prevent postoperative complications such as acute kidney injury. Of note, compliance with guideline recommendations for medication instructions was not examined because the data collection time frame expanded over multiple years and the recommendations have evolved each year as new data emerge.

Preoperative DM Management

The first key takeaway from this study is to ensure patients are ready for surgery with a formal assessment (typically in the form of a clinic visit) prior to the surgery. One private sector health system published their approach to this by administering an automatic preoperative HbA1c screening for those with a DM diagnosis and all patients with a random plasma glucose ≥ 200 mg/dL.22 Additionally, if the patient's HbA1c level was not at goal prior to surgery (≥ 8% for those with known DM and ≥ 6.5% with no known DM), patients were referred to endocrinology for further management. Increasing attention to the preoperative visit and extending HbA1c testing to all patients regardless of DM status also provides an opportunity to identify individuals living with undiagnosed DM.1

Even though there was no difference in the mean preoperative blood glucose level based on receipt or specificity of preoperative DM instructions, a second takeaway from this study is the importance of ensuring patients receive clear instructions on their DM medication schedule in the perioperative period. A practical first step may be updating the templates used by the primary surgery teams and providing education to the clinicians in the clinic on how to personalize the visits. Because the current preoperative DM process at VHI is managed by the primary surgical team in a clinic visit, there is an opportunity to shift this responsibility to other health care professionals, such as pharmacists—a change shown to reduce unintended omission of home medications following surgery during hospitalization and reduce costs.23,24

Limitations

This study relied on data included in the patient chart. These data include medication interventions made immediately prior to surgery, which can sometimes be inaccurately charted or difficult to find as they are not documented in the typical medication administration record. Also, the safety outcomes were collected from a discharge summary written by different clinicians, which may lead to information bias. Special attention was taken to ensure these data points were collected as accurately as possible, but it is possible some data may be inaccurate from unintentional human error. Additionally, the safety outcome was limited to a 30-day follow-up, but encompassed the entire length of postoperative stay for all included patients. Finally, given this study was retrospective with no comparison group and the intent was to improve processes at VHI, only hypotheses and potential interventions can be generated from this study. Future prospective studies with larger sample sizes and comparator groups are needed to draw further conclusions.

Conclusions

This study found that the current presurgery process at VHI appears to be successful in preventing surgical delays or cancellations due to hyperglycemia or hypoglycemia. Optimizing DM management can improve surgical outcomes by decreasing rates of postoperative complications, and this study added additional evidence in support of that in a unique population: veterans. Insight on the awareness of preoperative blood glucose management should be gleaned from this study, and based on this sample and site, the preadmission screening process and instructions provided to patients can serve as 2 starting points for optimizing elective surgery.

References
  1. Centers for Disease Control and Prevention. Diabetes basics. May 15, 2024. Accessed September 24, 2025. https://www.cdc.gov/diabetes/about/index.html
  2. Liu Y, Sayam S, Shao X, et al. Prevalence of and trends in diabetes among veterans, United States, 2005-2014. Prev Chronic Dis. 2017;14:E135. doi:10.5888/pcd14.170230
  3. Farmaki P, Damaskos C, Garmpis N, et al . Complications of the Type 2 Diabetes Mellitus. Curr Cardiol Rev. 2020;16(4):249-251. doi:10.2174/1573403X1604201229115531
  4. Frisch A, Chandra P, Smiley D, et al. Prevalence and clinical outcome of hyperglycemia in the perioperative period in noncardiac surgery. Diabetes Care. 2010;33:1783-1788. doi:10.2337/dc10-0304
  5. Noordzij PG, Boersma E, Schreiner F, et al. Increased preoperative glucose levels are associated with perioperative mortality in patients undergoing noncardiac, nonvascular surgery. Eur J Endocrinol. 2007;156:137 -142. doi:10.1530/eje.1.02321
  6. Pomposelli JJ, Baxter JK 3rd, Babineau TJ, et al. Early postoperative glucose control predicts nosocomial infection rate in diabetic patients. JPEN J Parenter Enteral Nutr. 1998;22:77-81. doi:10.1177/01486071980220027
  7. Umpierrez GE, Smiley D, Jacobs S, et al. Randomized study of basal-bolus insulin therapy in the inpatient management of patients with type 2 diabetes undergoing general surgery (RABBIT 2 surgery). Diabetes Care. 2011;34:256-261. doi:10.2337/dc10-1407
  8. Pasquel FJ, Gomez-Huelgas R, Anzola I, et al. Predictive value of admission hemoglobin A1c on inpatient glycemic control and response to insulin therapy in medicine and surgery patients with type 2 diabetes. Diabetes Care. 2015;38:e202-e203. doi:10.2337/dc15-1835
  9. Alexiewicz JM, Kumar D, Smogorzewski M, et al. Polymorphonuclear leukocytes in non-insulin-dependent diabetes mellitus: abnormalities in metabolism and function. Ann Intern Med. 1995;123:919-924. doi:10.7326/0003-4819-123-12-199512150-00004
  10. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Medical Care in Diabetes—2025. Diabetes Care. 2025;48(1 suppl 1):S321-S334. doi:10.2337/dc25-S016
  11. Kumar R, Gandhi R. Reasons for cancellation of operation on the day of intended surgery in a multidisciplinary 500 bedded hospital. J Anaesthesiol Clin Pharmacol. 2012;28:66-69. doi:10.4103/0970-9185.92442
  12. American Diabetes Association. 14. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2018. Diabetes Care. 2018;41(1 suppl 1):S144- S151. doi:10.2337/dc18-S014
  13. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2019. Diabetes Care. 2019;42(suppl 1):S173- S181. doi:10.2337/dc19-S015
  14. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2020. Diabetes Care. 2020;43(suppl 1):S193- S202. doi:10.2337/dc20-S015
  15. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2021. Diabetes Care. 2021;44(suppl 1):S211- S220. doi:10.2337/dc21-S015
  16. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Medical Care in Diabetes—2022. Diabetes Care. 2022;45(suppl 1):S244-S253. doi:10.2337/dc22-S016
  17. ElSayed NA, Aleppo G, Aroda VR, et al. 16. Diabetes care in the hospital: Standards of Care in Diabetes—2023. Diabetes Care. 2023;46(suppl 1):S267-S278. doi:10.2337/dc23-S016
  18. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Care in Diabetes—2024. Diabetes Care. 2024;47(suppl 1):S295-S306. doi:10.2337/dc24-S016
  19. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int Suppl. 2012;2:1-138. Accessed September 24, 2025. https:// www.kisupplements.org/issue/S2157-1716(12)X7200-9
  20. US Department of Veterans Affairs. VA Indiana Healthcare: about us. Accessed September 24, 2025. https:// www.va.gov/indiana-health-care/about-us/
  21. Koh WX, Phelan R, Hopman WM, et al. Cancellation of elective surgery: rates, reasons and effect on patient satisfaction. Can J Surg. 2021;64:E155-E161. doi:10.1503/cjs.008119
  22. Pai S-L, Haehn DA, Pitruzzello NE, et al. Reducing infection rates with enhanced preoperative diabetes mellitus diagnosis and optimization processes. South Med J. 2023;116:215-219. doi:10.14423/SMJ.0000000000001507
  23. Forrester TG, Sullivan S, Snoswell CL, et al. Integrating a pharmacist into the perioperative setting. Aust Health Rev. 2020;44:563-568. doi:10.1071/AH19126
  24. Hale AR, Coombes ID, Stokes J, et al. Perioperative medication management: expanding the role of the preadmission clinic pharmacist in a single centre, randomised controlled trial of collaborative prescribing. BMJ Open. 2013;3:e003027. doi:10.1136/bmjopen-2013-003027
References
  1. Centers for Disease Control and Prevention. Diabetes basics. May 15, 2024. Accessed September 24, 2025. https://www.cdc.gov/diabetes/about/index.html
  2. Liu Y, Sayam S, Shao X, et al. Prevalence of and trends in diabetes among veterans, United States, 2005-2014. Prev Chronic Dis. 2017;14:E135. doi:10.5888/pcd14.170230
  3. Farmaki P, Damaskos C, Garmpis N, et al . Complications of the Type 2 Diabetes Mellitus. Curr Cardiol Rev. 2020;16(4):249-251. doi:10.2174/1573403X1604201229115531
  4. Frisch A, Chandra P, Smiley D, et al. Prevalence and clinical outcome of hyperglycemia in the perioperative period in noncardiac surgery. Diabetes Care. 2010;33:1783-1788. doi:10.2337/dc10-0304
  5. Noordzij PG, Boersma E, Schreiner F, et al. Increased preoperative glucose levels are associated with perioperative mortality in patients undergoing noncardiac, nonvascular surgery. Eur J Endocrinol. 2007;156:137 -142. doi:10.1530/eje.1.02321
  6. Pomposelli JJ, Baxter JK 3rd, Babineau TJ, et al. Early postoperative glucose control predicts nosocomial infection rate in diabetic patients. JPEN J Parenter Enteral Nutr. 1998;22:77-81. doi:10.1177/01486071980220027
  7. Umpierrez GE, Smiley D, Jacobs S, et al. Randomized study of basal-bolus insulin therapy in the inpatient management of patients with type 2 diabetes undergoing general surgery (RABBIT 2 surgery). Diabetes Care. 2011;34:256-261. doi:10.2337/dc10-1407
  8. Pasquel FJ, Gomez-Huelgas R, Anzola I, et al. Predictive value of admission hemoglobin A1c on inpatient glycemic control and response to insulin therapy in medicine and surgery patients with type 2 diabetes. Diabetes Care. 2015;38:e202-e203. doi:10.2337/dc15-1835
  9. Alexiewicz JM, Kumar D, Smogorzewski M, et al. Polymorphonuclear leukocytes in non-insulin-dependent diabetes mellitus: abnormalities in metabolism and function. Ann Intern Med. 1995;123:919-924. doi:10.7326/0003-4819-123-12-199512150-00004
  10. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Medical Care in Diabetes—2025. Diabetes Care. 2025;48(1 suppl 1):S321-S334. doi:10.2337/dc25-S016
  11. Kumar R, Gandhi R. Reasons for cancellation of operation on the day of intended surgery in a multidisciplinary 500 bedded hospital. J Anaesthesiol Clin Pharmacol. 2012;28:66-69. doi:10.4103/0970-9185.92442
  12. American Diabetes Association. 14. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2018. Diabetes Care. 2018;41(1 suppl 1):S144- S151. doi:10.2337/dc18-S014
  13. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2019. Diabetes Care. 2019;42(suppl 1):S173- S181. doi:10.2337/dc19-S015
  14. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2020. Diabetes Care. 2020;43(suppl 1):S193- S202. doi:10.2337/dc20-S015
  15. American Diabetes Association. 15. Diabetes care in the hospital: Standards of Medical Care in Diabetes— 2021. Diabetes Care. 2021;44(suppl 1):S211- S220. doi:10.2337/dc21-S015
  16. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Medical Care in Diabetes—2022. Diabetes Care. 2022;45(suppl 1):S244-S253. doi:10.2337/dc22-S016
  17. ElSayed NA, Aleppo G, Aroda VR, et al. 16. Diabetes care in the hospital: Standards of Care in Diabetes—2023. Diabetes Care. 2023;46(suppl 1):S267-S278. doi:10.2337/dc23-S016
  18. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Care in Diabetes—2024. Diabetes Care. 2024;47(suppl 1):S295-S306. doi:10.2337/dc24-S016
  19. Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int Suppl. 2012;2:1-138. Accessed September 24, 2025. https:// www.kisupplements.org/issue/S2157-1716(12)X7200-9
  20. US Department of Veterans Affairs. VA Indiana Healthcare: about us. Accessed September 24, 2025. https:// www.va.gov/indiana-health-care/about-us/
  21. Koh WX, Phelan R, Hopman WM, et al. Cancellation of elective surgery: rates, reasons and effect on patient satisfaction. Can J Surg. 2021;64:E155-E161. doi:10.1503/cjs.008119
  22. Pai S-L, Haehn DA, Pitruzzello NE, et al. Reducing infection rates with enhanced preoperative diabetes mellitus diagnosis and optimization processes. South Med J. 2023;116:215-219. doi:10.14423/SMJ.0000000000001507
  23. Forrester TG, Sullivan S, Snoswell CL, et al. Integrating a pharmacist into the perioperative setting. Aust Health Rev. 2020;44:563-568. doi:10.1071/AH19126
  24. Hale AR, Coombes ID, Stokes J, et al. Perioperative medication management: expanding the role of the preadmission clinic pharmacist in a single centre, randomised controlled trial of collaborative prescribing. BMJ Open. 2013;3:e003027. doi:10.1136/bmjopen-2013-003027
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Efficacy of Subcutaneous Semaglutide Dose Escalation in Reducing Insulin in Patients With Type 2 Diabetes

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Efficacy of Subcutaneous Semaglutide Dose Escalation in Reducing Insulin in Patients With Type 2 Diabetes

Type 2 diabetes mellitus (T2DM) is a chronic disease becoming more prevalent each year and is the seventh-leading cause of death in the United States.1 The most common reason for hospitalization for patients with T2DM is uncontrolled glycemic levels.2 Nearly 25% of the US Department of Veterans Affairs (VA) patient population has T2DM.3 T2DM is the leading cause of blindness, end-stage renal disease, and amputation for VA patients.4

According to the 2023 American Diabetes Association (ADA) guidelines, treatment goals of T2DM include eliminating symptoms, preventing or delaying complications, and attaining glycemic goals. A typical hemoglobin A1c (HbA1c) goal range is < 7%, but individual goals can vary up to < 9% due to a multitude of factors, including patient comorbidities and clinical status.5

Initial treatment recommendations are nonpharmacologic and include comprehensive lifestyle interventions such as optimizing nutrition, physical activity, and behavioral therapy. When pharmacologic therapy is required, metformin is the preferred first-line treatment for the majority of newly diagnosed patients with T2DM and should be added to continued lifestyle management.5 If HbA1c levels remains above goal, the 2023 ADA guidelines recommend adding a second medication, including but not limited to insulin, a glucagonlike peptide-1 receptor agonist (GLP-1RA), or a sodium-glucose cotransporter 2 inhibitor. Medication choice is largely based on the patient’s concomitant conditions (eg, atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease). The 2023 ADA guidelines suggest initiating insulin therapy when a patient's blood glucose ≥ 300 mg/dL, HbA1c > 10%, or if the patient has symptoms of hyperglycemia, even at initial diagnosis. Initiating medications to minimize or avoid hypoglycemia is a priority, especially in high-risk individuals.5

Clinical evidence shows that GLP-1RAs may provide similar glycemic control to insulin with lower risk of hypoglycemia.6 Other reported benefits of GLP-1RAs include weight loss, blood pressure reduction, and improved lipid levels. The most common adverse events (AEs) with GLP-1RAs are gastrointestinal. Including GLP-1RAs in T2DM pharmacotherapy may lower the risk of hypoglycemia, especially in patients at high risk of hypoglycemia.

The 2023 ADA guidelines indicate that it is appropriate to initiate GLP-]1RAs in patients on insulin.5 However, while GLP-1RAs do not increase the risk of hypoglycemia independently, combination treatment with GLP-1RAs and insulin can still result in hypoglycemia.6 Insulin is the key suspect of this hypoglycemic risk.7 Thus, if insulin dosage can be reduced or discontinued, this might reduce the risk of hypoglycemia.

The literature is limited on how the addition of a GLP-1RA to insulin treatment will affect the patient's daily insulin doses, particularly for the veteran population. The goal of this study is to examine this gap in current research by examining semaglutide, which is the current formulary preferred GLP-1RA at the VA.

Semaglutide is subcutaneously initiated at a dose of 0.25 mg once weekly for 4 weeks to reduce gastrointestinal symptoms, then increased to 0.5 mg weekly. Additional increases to a maintenance dose of 1 mg or 2 mg weekly can occur to achieve glycemic goals. The SUSTAIN-FORTE randomized controlled trial sought to determine whether there was a difference in HbA1c level reduction and significant weight loss with the 2-mg vs 1-mg dose.8 Patients in the trial were taking metformin but needed additional medication to control their HbA1c. They were not using insulin and may or may not have been taking sulfonylureas prior to semaglutide initiation. Semaglutide 2 mg was found to significantly improve HbA1c control and promote weight loss compared with semaglutide 1 mg, while maintaining a similar safety profile.

Because this study involved patients who required additional HbA1c control, although semaglutide reduced HbA1c, not all patients were able to reduce their other diabetes medications, which depended on the baseline HbA1c level and the level upon completion of semaglutide titration. Dose reductions for the patients’ other T2DM medications were not reported at trial end. SUSTAIN-FORTE established titration up to semaglutide 2 mg as effective for HbA1c reduction, although it did not study patients also on insulin.8

Insulin is associated with hypoglycemic risk, weight gain, and other AEs.7,8 This study analyzed whether increasing semaglutide could reduce insulin doses and therefore reduce risk of AEs in patients with T2DM.

Methods

A retrospective, single-center, chart review was conducted at VA Sioux Falls Health Care System (VASFHCS). Data were collected through manual review of VASFHCS electronic medical records. Patients aged ≥ 18 years with active prescriptions for at least once-daily insulin who were initiated on 2-mg weekly dose of semaglutide at the VASFHCS clinical pharmacy practitioner medication management clinic between January 1, 2021, and September 1, 2023, were included. VASFHCS clinical pharmacy practitioners have a scope of practice that allows them to initiate, modify, or discontinue medication therapy within medication management clinics.

The most frequently used prandial insulin at VASFHCS is insulin aspart, and the most frequently used basal insulin is insulin glargine. Patients were retrospectively monitored as they progressed from baseline (the point in time where semaglutide 0.5 mg was initiated) to ≥ 3 months on semaglutide 2-mg therapy. Patients were excluded if they previously used a GLP-1RA or if they were on sliding scale insulin without an exact daily dosage.

The primary endpoint was the percent change in total daily insulin dose from baseline to each dose increase after receiving semaglutide 2 mg for ≥ 3 months. Secondary endpoints included changes in daily prandial insulin dose, daily basal insulin dose, HbA1c, and number of hypoglycemic events reported. Data collected included age, race, weight, body mass index, total daily prandial insulin dose, total daily basal insulin dose, HbA1c, and hypoglycemic events reported at the visit when semaglutide was initiated.

Statistical Analysis

The sample size was calculated prior to data collection, and it was determined that for α = .05, 47 patients were needed to achieve 95% power. The primary endpoint was assessed using a paired t test, as were each secondary endpoint. Results with P < .05 were considered statistically significant.

Results

Sixty-two patients were included. The mean HbA1c level at baseline was 7.7%, the baseline mean prandial and insulin daily doses were 41.5 units and 85.1 units, respectively (Table 1) From baseline to initiation of a semaglutide 1-mg dose, the daily insulin dose changed –5.6% (95% CI, 2.2-14.0; P = .008). From baseline to 2-mg dose initiation daily insulin changed -22.2% (95% CI, 22.0-35.1; P < .001) and for patients receiving semaglutide 2 mg for ≥ 3 months it changed -36.9% (95% CI, 37.4-56.5; P < .001) (Figure).

1125FED-DM-Semi-T1
1125FED-DM-Semi-F1
FIGURE. Change in daily insulin dose at time of semaglutide dose changes.

After receiving the 2-mg dose for ≥ 3 months, the mean daily dose of prandial insulin decreased from 41.5 units to 24.6 units (95% CI, 12.6-21.2; P < .001); mean daily dose of basal insulin decreased from 85.1 units to 52.1 units (95% CI, 23.9-42.0; P < .001); and mean HbA1c level decreased from 7.7% to 7.1% (95% CI, 0.3-0.8; P < .001). Mean number of hypoglycemic events reported was not statistically significant, changing from 3.6 to 3.2 (95% CI, –0.6 to 0.1; P = .21) (Table 2).

1125FED-DM-Semi-T2

Discussion

This study investigated the effect of subcutaneous semaglutide dose escalation on total daily insulin dose for patients with T2DM. There was a statistically significant decrease in total daily insulin dose from baseline to 1 mg initiation; this decrease continued with further insulin dose reduction seen at the 2-mg dose initiation and additional insulin dose reduction at ≥ 3 months at this dose. It was hypothesized there would be a significant total daily insulin dose reduction at some point, especially when transitioning from the semaglutide 1-mg to the 2-mg dose, based on previous research. 9,10 The additional reduction in daily insulin dose when continuing on semaglutide 2 mg for ≥ 3 months was an unanticipated but added benefit, showing that if tolerated, maintaining the 2-mg dose will help patients reduce their insulin doses.

In terms of secondary endpoints, there was a statistically significant decrease in mean total daily dose individually for prandial and basal insulin from baseline to ≥ 3 months after semaglutide 2 mg initiation. The change in HbA1c level was also statistically significant and decreased from baseline, even as insulin doses were reduced. This change in HbA1c level was expected; previous literature has shown a significant link between improving HbA1c control when semaglutide doses are increased to 2 mg weekly.10 Due to having been shown in previous trials, it was expected that HbA1c levels would decrease even when the insulin doses were being reduced.10 Insulin dose reduction can potentially be added to the growing evidence of semaglutide benefits. The change in the number of hypoglycemic events was not statistically significant, which was unexpected since previous research show a trend in patients taking GLP-1RAs having fewer hypoglycemic events than those taking insulin.6 Further investigation with a larger sample size and prospective trial could determine whether this result is an outlier. In this study, there was no increase in HbA1c or hypoglycemic events reported with increasing semaglutide doses, which provides further evidence of the safety of semaglutide even at higher doses.

These data suggest that for a patient with T2DM who is already taking insulin, the recommended titration of semaglutide is to start with 0.5 mg and titrate up to a 2-mg subcutaneous weekly dose and to then continue at that dose. As long as the 2-mg dose is tolerated, it will provide patients with the most HbA1c control and lead to a reduction of their total daily insulin doses according to these results.

Strengths and Limitations

This study compared patient data at different points. This method did not require a second distinct control group, which would potentially introduce confounding factors, such as different baseline characteristics. Another strength is that documentation was available for all patients throughout the study so no one was lost to follow-up. This allowed comprehensive data collection and provided a stronger conclusion given the completeness of the data from baseline to follow-up.

Limitations include the retrospective design and small sample size. In addition, the study design did not allow for randomization. There is no documentation of adherence to medication regimen, which was difficult to determine due to the retrospective nature. Other changes to the patients’ medication regimen were not collected in aggregate and thus, it is possible the total daily insulin dose was impacted by other medication changes. There is also potential for inconsistent documentation of the patients’ true total daily insulin dose in the medical record, thus leading to inaccuracy of recorded data.

Conclusions

A small sample of veterans with T2DM had statistically significant reductions in total daily insulin dose when subcutaneous semaglutide was initiated, as well as after each dose increase. There was also a statistically significant reduction in HbA1c levels from baseline even as patient insulin doses were reduced. These results support the current practice of using semaglutide to treat T2DM, suggesting it may be safe and effective at reducing HbA1c levels as the dose is titrated up to 2 mg. There was no statistically significant change in the number of hypoglycemic events reported as semaglutide was titrated up. Thus, when semaglutide is increased to the maximum recommended dose of 2 mg for T2DM, patients may experience a reduction of their total daily dose of insulin and HbA1c levels. These benefits may reduce the risk of insulin-related AEs while maintaining appropriate glycemic control.

References
  1. Diabetes mellitus: in federal health care data trends 2017. Fed Pract. 2017:S20. Accessed August 6, 2025. https://www.fedprac-digital.com/federalpractitioner/data_trends_2017
  2. Centers for Disease Control and Prevention. National diabetes statistics report. May 15, 2024. Accessed September 17, 2025. https://www.cdc.gov/diabetes/php/data-research/index.html
  3. US Department of Veterans Affairs. VA research on diabetes. Updated January 15, 2021. Accessed August 6, 2025. https://www.research.va.gov/topics/diabetes.cfm
  4. Liu Y, Sayam S, Shao X, et al. Prevalence of and trends in diabetes among veterans, United States, 2005-2014. Prev Chronic Dis. 2017;14:E135. doi:10.5888/pcd14.170230
  5. American Diabetes Association. Standards of care in diabetes— 2023 abridged for primary care providers. Clin Diabetes. 2022;41:4-31. doi:10.2337/cd23-as01
  6. Zhao Z, Tang Y, Hu Y, Zhu H, Chen X, Zhao B. Hypoglycemia following the use of glucagon-like peptide-1 receptor agonists: a real-world analysis of post-marketing surveillance data. Ann Transl Med. 2021;9:1482. doi:10.21037/atm-21-4162
  7. Workgroup on Hypoglycemia, American Diabetes Association. Defining and reporting hypoglycemia in diabetes: a report from the American Diabetes Association Workgroup on Hypoglycemia. Diabetes Care. 2005;28:1245-1249. doi:10.2337/diacare.28.5.1245
  8. Frías JP, Auerbach P, Bajaj HS, et al. Efficacy and safety of once-weekly semaglutide 2.0 mg versus 1.0 mg in patients with type 2 diabetes (SUSTAIN FORTE): a double-blind, randomised, phase 3B trial. Lancet Diabetes Endocrinol. 2021;9:563-574. doi:10.1016/S2213-8587(21)00174-1
  9. Garber AJ, Handelsman Y, Grunberger G, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm - 2020 executive summary. Endocr Pract. 2020;26:107-139. doi:10.4158/CS-2019-0472
  10. Miles KE, Kerr JL. Semaglutide for the treatment of type 2 diabetes mellitus. J Pharm Technol. 2018;34:281-289. doi:10.1177/8755122518790925
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Alisha Halver, PharmDa; John Wiksen, PharmDa; Aaron Larson, PharmD, BCPSa; Amber Wegner, PharmDa

Author affiliations: aVeterans Affairs Sioux Falls Health Care System, South Dakota

Author disclosures: The authors report no actual or potential conflicts of interest regarding this article.

Correspondence: Alisha Halver (aliophoven@gmail.com)

Fed Pract. 2025;42(suppl 6). Published online November 14. doi:10.12788/fp.0642

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Alisha Halver, PharmDa; John Wiksen, PharmDa; Aaron Larson, PharmD, BCPSa; Amber Wegner, PharmDa

Author affiliations: aVeterans Affairs Sioux Falls Health Care System, South Dakota

Author disclosures: The authors report no actual or potential conflicts of interest regarding this article.

Correspondence: Alisha Halver (aliophoven@gmail.com)

Fed Pract. 2025;42(suppl 6). Published online November 14. doi:10.12788/fp.0642

Author and Disclosure Information

Alisha Halver, PharmDa; John Wiksen, PharmDa; Aaron Larson, PharmD, BCPSa; Amber Wegner, PharmDa

Author affiliations: aVeterans Affairs Sioux Falls Health Care System, South Dakota

Author disclosures: The authors report no actual or potential conflicts of interest regarding this article.

Correspondence: Alisha Halver (aliophoven@gmail.com)

Fed Pract. 2025;42(suppl 6). Published online November 14. doi:10.12788/fp.0642

Article PDF
Article PDF

Type 2 diabetes mellitus (T2DM) is a chronic disease becoming more prevalent each year and is the seventh-leading cause of death in the United States.1 The most common reason for hospitalization for patients with T2DM is uncontrolled glycemic levels.2 Nearly 25% of the US Department of Veterans Affairs (VA) patient population has T2DM.3 T2DM is the leading cause of blindness, end-stage renal disease, and amputation for VA patients.4

According to the 2023 American Diabetes Association (ADA) guidelines, treatment goals of T2DM include eliminating symptoms, preventing or delaying complications, and attaining glycemic goals. A typical hemoglobin A1c (HbA1c) goal range is < 7%, but individual goals can vary up to < 9% due to a multitude of factors, including patient comorbidities and clinical status.5

Initial treatment recommendations are nonpharmacologic and include comprehensive lifestyle interventions such as optimizing nutrition, physical activity, and behavioral therapy. When pharmacologic therapy is required, metformin is the preferred first-line treatment for the majority of newly diagnosed patients with T2DM and should be added to continued lifestyle management.5 If HbA1c levels remains above goal, the 2023 ADA guidelines recommend adding a second medication, including but not limited to insulin, a glucagonlike peptide-1 receptor agonist (GLP-1RA), or a sodium-glucose cotransporter 2 inhibitor. Medication choice is largely based on the patient’s concomitant conditions (eg, atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease). The 2023 ADA guidelines suggest initiating insulin therapy when a patient's blood glucose ≥ 300 mg/dL, HbA1c > 10%, or if the patient has symptoms of hyperglycemia, even at initial diagnosis. Initiating medications to minimize or avoid hypoglycemia is a priority, especially in high-risk individuals.5

Clinical evidence shows that GLP-1RAs may provide similar glycemic control to insulin with lower risk of hypoglycemia.6 Other reported benefits of GLP-1RAs include weight loss, blood pressure reduction, and improved lipid levels. The most common adverse events (AEs) with GLP-1RAs are gastrointestinal. Including GLP-1RAs in T2DM pharmacotherapy may lower the risk of hypoglycemia, especially in patients at high risk of hypoglycemia.

The 2023 ADA guidelines indicate that it is appropriate to initiate GLP-]1RAs in patients on insulin.5 However, while GLP-1RAs do not increase the risk of hypoglycemia independently, combination treatment with GLP-1RAs and insulin can still result in hypoglycemia.6 Insulin is the key suspect of this hypoglycemic risk.7 Thus, if insulin dosage can be reduced or discontinued, this might reduce the risk of hypoglycemia.

The literature is limited on how the addition of a GLP-1RA to insulin treatment will affect the patient's daily insulin doses, particularly for the veteran population. The goal of this study is to examine this gap in current research by examining semaglutide, which is the current formulary preferred GLP-1RA at the VA.

Semaglutide is subcutaneously initiated at a dose of 0.25 mg once weekly for 4 weeks to reduce gastrointestinal symptoms, then increased to 0.5 mg weekly. Additional increases to a maintenance dose of 1 mg or 2 mg weekly can occur to achieve glycemic goals. The SUSTAIN-FORTE randomized controlled trial sought to determine whether there was a difference in HbA1c level reduction and significant weight loss with the 2-mg vs 1-mg dose.8 Patients in the trial were taking metformin but needed additional medication to control their HbA1c. They were not using insulin and may or may not have been taking sulfonylureas prior to semaglutide initiation. Semaglutide 2 mg was found to significantly improve HbA1c control and promote weight loss compared with semaglutide 1 mg, while maintaining a similar safety profile.

Because this study involved patients who required additional HbA1c control, although semaglutide reduced HbA1c, not all patients were able to reduce their other diabetes medications, which depended on the baseline HbA1c level and the level upon completion of semaglutide titration. Dose reductions for the patients’ other T2DM medications were not reported at trial end. SUSTAIN-FORTE established titration up to semaglutide 2 mg as effective for HbA1c reduction, although it did not study patients also on insulin.8

Insulin is associated with hypoglycemic risk, weight gain, and other AEs.7,8 This study analyzed whether increasing semaglutide could reduce insulin doses and therefore reduce risk of AEs in patients with T2DM.

Methods

A retrospective, single-center, chart review was conducted at VA Sioux Falls Health Care System (VASFHCS). Data were collected through manual review of VASFHCS electronic medical records. Patients aged ≥ 18 years with active prescriptions for at least once-daily insulin who were initiated on 2-mg weekly dose of semaglutide at the VASFHCS clinical pharmacy practitioner medication management clinic between January 1, 2021, and September 1, 2023, were included. VASFHCS clinical pharmacy practitioners have a scope of practice that allows them to initiate, modify, or discontinue medication therapy within medication management clinics.

The most frequently used prandial insulin at VASFHCS is insulin aspart, and the most frequently used basal insulin is insulin glargine. Patients were retrospectively monitored as they progressed from baseline (the point in time where semaglutide 0.5 mg was initiated) to ≥ 3 months on semaglutide 2-mg therapy. Patients were excluded if they previously used a GLP-1RA or if they were on sliding scale insulin without an exact daily dosage.

The primary endpoint was the percent change in total daily insulin dose from baseline to each dose increase after receiving semaglutide 2 mg for ≥ 3 months. Secondary endpoints included changes in daily prandial insulin dose, daily basal insulin dose, HbA1c, and number of hypoglycemic events reported. Data collected included age, race, weight, body mass index, total daily prandial insulin dose, total daily basal insulin dose, HbA1c, and hypoglycemic events reported at the visit when semaglutide was initiated.

Statistical Analysis

The sample size was calculated prior to data collection, and it was determined that for α = .05, 47 patients were needed to achieve 95% power. The primary endpoint was assessed using a paired t test, as were each secondary endpoint. Results with P < .05 were considered statistically significant.

Results

Sixty-two patients were included. The mean HbA1c level at baseline was 7.7%, the baseline mean prandial and insulin daily doses were 41.5 units and 85.1 units, respectively (Table 1) From baseline to initiation of a semaglutide 1-mg dose, the daily insulin dose changed –5.6% (95% CI, 2.2-14.0; P = .008). From baseline to 2-mg dose initiation daily insulin changed -22.2% (95% CI, 22.0-35.1; P < .001) and for patients receiving semaglutide 2 mg for ≥ 3 months it changed -36.9% (95% CI, 37.4-56.5; P < .001) (Figure).

1125FED-DM-Semi-T1
1125FED-DM-Semi-F1
FIGURE. Change in daily insulin dose at time of semaglutide dose changes.

After receiving the 2-mg dose for ≥ 3 months, the mean daily dose of prandial insulin decreased from 41.5 units to 24.6 units (95% CI, 12.6-21.2; P < .001); mean daily dose of basal insulin decreased from 85.1 units to 52.1 units (95% CI, 23.9-42.0; P < .001); and mean HbA1c level decreased from 7.7% to 7.1% (95% CI, 0.3-0.8; P < .001). Mean number of hypoglycemic events reported was not statistically significant, changing from 3.6 to 3.2 (95% CI, –0.6 to 0.1; P = .21) (Table 2).

1125FED-DM-Semi-T2

Discussion

This study investigated the effect of subcutaneous semaglutide dose escalation on total daily insulin dose for patients with T2DM. There was a statistically significant decrease in total daily insulin dose from baseline to 1 mg initiation; this decrease continued with further insulin dose reduction seen at the 2-mg dose initiation and additional insulin dose reduction at ≥ 3 months at this dose. It was hypothesized there would be a significant total daily insulin dose reduction at some point, especially when transitioning from the semaglutide 1-mg to the 2-mg dose, based on previous research. 9,10 The additional reduction in daily insulin dose when continuing on semaglutide 2 mg for ≥ 3 months was an unanticipated but added benefit, showing that if tolerated, maintaining the 2-mg dose will help patients reduce their insulin doses.

In terms of secondary endpoints, there was a statistically significant decrease in mean total daily dose individually for prandial and basal insulin from baseline to ≥ 3 months after semaglutide 2 mg initiation. The change in HbA1c level was also statistically significant and decreased from baseline, even as insulin doses were reduced. This change in HbA1c level was expected; previous literature has shown a significant link between improving HbA1c control when semaglutide doses are increased to 2 mg weekly.10 Due to having been shown in previous trials, it was expected that HbA1c levels would decrease even when the insulin doses were being reduced.10 Insulin dose reduction can potentially be added to the growing evidence of semaglutide benefits. The change in the number of hypoglycemic events was not statistically significant, which was unexpected since previous research show a trend in patients taking GLP-1RAs having fewer hypoglycemic events than those taking insulin.6 Further investigation with a larger sample size and prospective trial could determine whether this result is an outlier. In this study, there was no increase in HbA1c or hypoglycemic events reported with increasing semaglutide doses, which provides further evidence of the safety of semaglutide even at higher doses.

These data suggest that for a patient with T2DM who is already taking insulin, the recommended titration of semaglutide is to start with 0.5 mg and titrate up to a 2-mg subcutaneous weekly dose and to then continue at that dose. As long as the 2-mg dose is tolerated, it will provide patients with the most HbA1c control and lead to a reduction of their total daily insulin doses according to these results.

Strengths and Limitations

This study compared patient data at different points. This method did not require a second distinct control group, which would potentially introduce confounding factors, such as different baseline characteristics. Another strength is that documentation was available for all patients throughout the study so no one was lost to follow-up. This allowed comprehensive data collection and provided a stronger conclusion given the completeness of the data from baseline to follow-up.

Limitations include the retrospective design and small sample size. In addition, the study design did not allow for randomization. There is no documentation of adherence to medication regimen, which was difficult to determine due to the retrospective nature. Other changes to the patients’ medication regimen were not collected in aggregate and thus, it is possible the total daily insulin dose was impacted by other medication changes. There is also potential for inconsistent documentation of the patients’ true total daily insulin dose in the medical record, thus leading to inaccuracy of recorded data.

Conclusions

A small sample of veterans with T2DM had statistically significant reductions in total daily insulin dose when subcutaneous semaglutide was initiated, as well as after each dose increase. There was also a statistically significant reduction in HbA1c levels from baseline even as patient insulin doses were reduced. These results support the current practice of using semaglutide to treat T2DM, suggesting it may be safe and effective at reducing HbA1c levels as the dose is titrated up to 2 mg. There was no statistically significant change in the number of hypoglycemic events reported as semaglutide was titrated up. Thus, when semaglutide is increased to the maximum recommended dose of 2 mg for T2DM, patients may experience a reduction of their total daily dose of insulin and HbA1c levels. These benefits may reduce the risk of insulin-related AEs while maintaining appropriate glycemic control.

Type 2 diabetes mellitus (T2DM) is a chronic disease becoming more prevalent each year and is the seventh-leading cause of death in the United States.1 The most common reason for hospitalization for patients with T2DM is uncontrolled glycemic levels.2 Nearly 25% of the US Department of Veterans Affairs (VA) patient population has T2DM.3 T2DM is the leading cause of blindness, end-stage renal disease, and amputation for VA patients.4

According to the 2023 American Diabetes Association (ADA) guidelines, treatment goals of T2DM include eliminating symptoms, preventing or delaying complications, and attaining glycemic goals. A typical hemoglobin A1c (HbA1c) goal range is < 7%, but individual goals can vary up to < 9% due to a multitude of factors, including patient comorbidities and clinical status.5

Initial treatment recommendations are nonpharmacologic and include comprehensive lifestyle interventions such as optimizing nutrition, physical activity, and behavioral therapy. When pharmacologic therapy is required, metformin is the preferred first-line treatment for the majority of newly diagnosed patients with T2DM and should be added to continued lifestyle management.5 If HbA1c levels remains above goal, the 2023 ADA guidelines recommend adding a second medication, including but not limited to insulin, a glucagonlike peptide-1 receptor agonist (GLP-1RA), or a sodium-glucose cotransporter 2 inhibitor. Medication choice is largely based on the patient’s concomitant conditions (eg, atherosclerotic cardiovascular disease, heart failure, or chronic kidney disease). The 2023 ADA guidelines suggest initiating insulin therapy when a patient's blood glucose ≥ 300 mg/dL, HbA1c > 10%, or if the patient has symptoms of hyperglycemia, even at initial diagnosis. Initiating medications to minimize or avoid hypoglycemia is a priority, especially in high-risk individuals.5

Clinical evidence shows that GLP-1RAs may provide similar glycemic control to insulin with lower risk of hypoglycemia.6 Other reported benefits of GLP-1RAs include weight loss, blood pressure reduction, and improved lipid levels. The most common adverse events (AEs) with GLP-1RAs are gastrointestinal. Including GLP-1RAs in T2DM pharmacotherapy may lower the risk of hypoglycemia, especially in patients at high risk of hypoglycemia.

The 2023 ADA guidelines indicate that it is appropriate to initiate GLP-]1RAs in patients on insulin.5 However, while GLP-1RAs do not increase the risk of hypoglycemia independently, combination treatment with GLP-1RAs and insulin can still result in hypoglycemia.6 Insulin is the key suspect of this hypoglycemic risk.7 Thus, if insulin dosage can be reduced or discontinued, this might reduce the risk of hypoglycemia.

The literature is limited on how the addition of a GLP-1RA to insulin treatment will affect the patient's daily insulin doses, particularly for the veteran population. The goal of this study is to examine this gap in current research by examining semaglutide, which is the current formulary preferred GLP-1RA at the VA.

Semaglutide is subcutaneously initiated at a dose of 0.25 mg once weekly for 4 weeks to reduce gastrointestinal symptoms, then increased to 0.5 mg weekly. Additional increases to a maintenance dose of 1 mg or 2 mg weekly can occur to achieve glycemic goals. The SUSTAIN-FORTE randomized controlled trial sought to determine whether there was a difference in HbA1c level reduction and significant weight loss with the 2-mg vs 1-mg dose.8 Patients in the trial were taking metformin but needed additional medication to control their HbA1c. They were not using insulin and may or may not have been taking sulfonylureas prior to semaglutide initiation. Semaglutide 2 mg was found to significantly improve HbA1c control and promote weight loss compared with semaglutide 1 mg, while maintaining a similar safety profile.

Because this study involved patients who required additional HbA1c control, although semaglutide reduced HbA1c, not all patients were able to reduce their other diabetes medications, which depended on the baseline HbA1c level and the level upon completion of semaglutide titration. Dose reductions for the patients’ other T2DM medications were not reported at trial end. SUSTAIN-FORTE established titration up to semaglutide 2 mg as effective for HbA1c reduction, although it did not study patients also on insulin.8

Insulin is associated with hypoglycemic risk, weight gain, and other AEs.7,8 This study analyzed whether increasing semaglutide could reduce insulin doses and therefore reduce risk of AEs in patients with T2DM.

Methods

A retrospective, single-center, chart review was conducted at VA Sioux Falls Health Care System (VASFHCS). Data were collected through manual review of VASFHCS electronic medical records. Patients aged ≥ 18 years with active prescriptions for at least once-daily insulin who were initiated on 2-mg weekly dose of semaglutide at the VASFHCS clinical pharmacy practitioner medication management clinic between January 1, 2021, and September 1, 2023, were included. VASFHCS clinical pharmacy practitioners have a scope of practice that allows them to initiate, modify, or discontinue medication therapy within medication management clinics.

The most frequently used prandial insulin at VASFHCS is insulin aspart, and the most frequently used basal insulin is insulin glargine. Patients were retrospectively monitored as they progressed from baseline (the point in time where semaglutide 0.5 mg was initiated) to ≥ 3 months on semaglutide 2-mg therapy. Patients were excluded if they previously used a GLP-1RA or if they were on sliding scale insulin without an exact daily dosage.

The primary endpoint was the percent change in total daily insulin dose from baseline to each dose increase after receiving semaglutide 2 mg for ≥ 3 months. Secondary endpoints included changes in daily prandial insulin dose, daily basal insulin dose, HbA1c, and number of hypoglycemic events reported. Data collected included age, race, weight, body mass index, total daily prandial insulin dose, total daily basal insulin dose, HbA1c, and hypoglycemic events reported at the visit when semaglutide was initiated.

Statistical Analysis

The sample size was calculated prior to data collection, and it was determined that for α = .05, 47 patients were needed to achieve 95% power. The primary endpoint was assessed using a paired t test, as were each secondary endpoint. Results with P < .05 were considered statistically significant.

Results

Sixty-two patients were included. The mean HbA1c level at baseline was 7.7%, the baseline mean prandial and insulin daily doses were 41.5 units and 85.1 units, respectively (Table 1) From baseline to initiation of a semaglutide 1-mg dose, the daily insulin dose changed –5.6% (95% CI, 2.2-14.0; P = .008). From baseline to 2-mg dose initiation daily insulin changed -22.2% (95% CI, 22.0-35.1; P < .001) and for patients receiving semaglutide 2 mg for ≥ 3 months it changed -36.9% (95% CI, 37.4-56.5; P < .001) (Figure).

1125FED-DM-Semi-T1
1125FED-DM-Semi-F1
FIGURE. Change in daily insulin dose at time of semaglutide dose changes.

After receiving the 2-mg dose for ≥ 3 months, the mean daily dose of prandial insulin decreased from 41.5 units to 24.6 units (95% CI, 12.6-21.2; P < .001); mean daily dose of basal insulin decreased from 85.1 units to 52.1 units (95% CI, 23.9-42.0; P < .001); and mean HbA1c level decreased from 7.7% to 7.1% (95% CI, 0.3-0.8; P < .001). Mean number of hypoglycemic events reported was not statistically significant, changing from 3.6 to 3.2 (95% CI, –0.6 to 0.1; P = .21) (Table 2).

1125FED-DM-Semi-T2

Discussion

This study investigated the effect of subcutaneous semaglutide dose escalation on total daily insulin dose for patients with T2DM. There was a statistically significant decrease in total daily insulin dose from baseline to 1 mg initiation; this decrease continued with further insulin dose reduction seen at the 2-mg dose initiation and additional insulin dose reduction at ≥ 3 months at this dose. It was hypothesized there would be a significant total daily insulin dose reduction at some point, especially when transitioning from the semaglutide 1-mg to the 2-mg dose, based on previous research. 9,10 The additional reduction in daily insulin dose when continuing on semaglutide 2 mg for ≥ 3 months was an unanticipated but added benefit, showing that if tolerated, maintaining the 2-mg dose will help patients reduce their insulin doses.

In terms of secondary endpoints, there was a statistically significant decrease in mean total daily dose individually for prandial and basal insulin from baseline to ≥ 3 months after semaglutide 2 mg initiation. The change in HbA1c level was also statistically significant and decreased from baseline, even as insulin doses were reduced. This change in HbA1c level was expected; previous literature has shown a significant link between improving HbA1c control when semaglutide doses are increased to 2 mg weekly.10 Due to having been shown in previous trials, it was expected that HbA1c levels would decrease even when the insulin doses were being reduced.10 Insulin dose reduction can potentially be added to the growing evidence of semaglutide benefits. The change in the number of hypoglycemic events was not statistically significant, which was unexpected since previous research show a trend in patients taking GLP-1RAs having fewer hypoglycemic events than those taking insulin.6 Further investigation with a larger sample size and prospective trial could determine whether this result is an outlier. In this study, there was no increase in HbA1c or hypoglycemic events reported with increasing semaglutide doses, which provides further evidence of the safety of semaglutide even at higher doses.

These data suggest that for a patient with T2DM who is already taking insulin, the recommended titration of semaglutide is to start with 0.5 mg and titrate up to a 2-mg subcutaneous weekly dose and to then continue at that dose. As long as the 2-mg dose is tolerated, it will provide patients with the most HbA1c control and lead to a reduction of their total daily insulin doses according to these results.

Strengths and Limitations

This study compared patient data at different points. This method did not require a second distinct control group, which would potentially introduce confounding factors, such as different baseline characteristics. Another strength is that documentation was available for all patients throughout the study so no one was lost to follow-up. This allowed comprehensive data collection and provided a stronger conclusion given the completeness of the data from baseline to follow-up.

Limitations include the retrospective design and small sample size. In addition, the study design did not allow for randomization. There is no documentation of adherence to medication regimen, which was difficult to determine due to the retrospective nature. Other changes to the patients’ medication regimen were not collected in aggregate and thus, it is possible the total daily insulin dose was impacted by other medication changes. There is also potential for inconsistent documentation of the patients’ true total daily insulin dose in the medical record, thus leading to inaccuracy of recorded data.

Conclusions

A small sample of veterans with T2DM had statistically significant reductions in total daily insulin dose when subcutaneous semaglutide was initiated, as well as after each dose increase. There was also a statistically significant reduction in HbA1c levels from baseline even as patient insulin doses were reduced. These results support the current practice of using semaglutide to treat T2DM, suggesting it may be safe and effective at reducing HbA1c levels as the dose is titrated up to 2 mg. There was no statistically significant change in the number of hypoglycemic events reported as semaglutide was titrated up. Thus, when semaglutide is increased to the maximum recommended dose of 2 mg for T2DM, patients may experience a reduction of their total daily dose of insulin and HbA1c levels. These benefits may reduce the risk of insulin-related AEs while maintaining appropriate glycemic control.

References
  1. Diabetes mellitus: in federal health care data trends 2017. Fed Pract. 2017:S20. Accessed August 6, 2025. https://www.fedprac-digital.com/federalpractitioner/data_trends_2017
  2. Centers for Disease Control and Prevention. National diabetes statistics report. May 15, 2024. Accessed September 17, 2025. https://www.cdc.gov/diabetes/php/data-research/index.html
  3. US Department of Veterans Affairs. VA research on diabetes. Updated January 15, 2021. Accessed August 6, 2025. https://www.research.va.gov/topics/diabetes.cfm
  4. Liu Y, Sayam S, Shao X, et al. Prevalence of and trends in diabetes among veterans, United States, 2005-2014. Prev Chronic Dis. 2017;14:E135. doi:10.5888/pcd14.170230
  5. American Diabetes Association. Standards of care in diabetes— 2023 abridged for primary care providers. Clin Diabetes. 2022;41:4-31. doi:10.2337/cd23-as01
  6. Zhao Z, Tang Y, Hu Y, Zhu H, Chen X, Zhao B. Hypoglycemia following the use of glucagon-like peptide-1 receptor agonists: a real-world analysis of post-marketing surveillance data. Ann Transl Med. 2021;9:1482. doi:10.21037/atm-21-4162
  7. Workgroup on Hypoglycemia, American Diabetes Association. Defining and reporting hypoglycemia in diabetes: a report from the American Diabetes Association Workgroup on Hypoglycemia. Diabetes Care. 2005;28:1245-1249. doi:10.2337/diacare.28.5.1245
  8. Frías JP, Auerbach P, Bajaj HS, et al. Efficacy and safety of once-weekly semaglutide 2.0 mg versus 1.0 mg in patients with type 2 diabetes (SUSTAIN FORTE): a double-blind, randomised, phase 3B trial. Lancet Diabetes Endocrinol. 2021;9:563-574. doi:10.1016/S2213-8587(21)00174-1
  9. Garber AJ, Handelsman Y, Grunberger G, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm - 2020 executive summary. Endocr Pract. 2020;26:107-139. doi:10.4158/CS-2019-0472
  10. Miles KE, Kerr JL. Semaglutide for the treatment of type 2 diabetes mellitus. J Pharm Technol. 2018;34:281-289. doi:10.1177/8755122518790925
References
  1. Diabetes mellitus: in federal health care data trends 2017. Fed Pract. 2017:S20. Accessed August 6, 2025. https://www.fedprac-digital.com/federalpractitioner/data_trends_2017
  2. Centers for Disease Control and Prevention. National diabetes statistics report. May 15, 2024. Accessed September 17, 2025. https://www.cdc.gov/diabetes/php/data-research/index.html
  3. US Department of Veterans Affairs. VA research on diabetes. Updated January 15, 2021. Accessed August 6, 2025. https://www.research.va.gov/topics/diabetes.cfm
  4. Liu Y, Sayam S, Shao X, et al. Prevalence of and trends in diabetes among veterans, United States, 2005-2014. Prev Chronic Dis. 2017;14:E135. doi:10.5888/pcd14.170230
  5. American Diabetes Association. Standards of care in diabetes— 2023 abridged for primary care providers. Clin Diabetes. 2022;41:4-31. doi:10.2337/cd23-as01
  6. Zhao Z, Tang Y, Hu Y, Zhu H, Chen X, Zhao B. Hypoglycemia following the use of glucagon-like peptide-1 receptor agonists: a real-world analysis of post-marketing surveillance data. Ann Transl Med. 2021;9:1482. doi:10.21037/atm-21-4162
  7. Workgroup on Hypoglycemia, American Diabetes Association. Defining and reporting hypoglycemia in diabetes: a report from the American Diabetes Association Workgroup on Hypoglycemia. Diabetes Care. 2005;28:1245-1249. doi:10.2337/diacare.28.5.1245
  8. Frías JP, Auerbach P, Bajaj HS, et al. Efficacy and safety of once-weekly semaglutide 2.0 mg versus 1.0 mg in patients with type 2 diabetes (SUSTAIN FORTE): a double-blind, randomised, phase 3B trial. Lancet Diabetes Endocrinol. 2021;9:563-574. doi:10.1016/S2213-8587(21)00174-1
  9. Garber AJ, Handelsman Y, Grunberger G, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm - 2020 executive summary. Endocr Pract. 2020;26:107-139. doi:10.4158/CS-2019-0472
  10. Miles KE, Kerr JL. Semaglutide for the treatment of type 2 diabetes mellitus. J Pharm Technol. 2018;34:281-289. doi:10.1177/8755122518790925
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Efficacy of Subcutaneous Semaglutide Dose Escalation in Reducing Insulin in Patients With Type 2 Diabetes

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Impact of Continuous Glucose Monitoring for American Indian/Alaska Native Adults With Type 2 Diabetes Mellitus Not Using Insulin

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Impact of Continuous Glucose Monitoring for American Indian/Alaska Native Adults With Type 2 Diabetes Mellitus Not Using Insulin

Diabetes mellitus (DM) is a national health crisis affecting > 38 million people (11.6%) in the United States.1 American Indian and Alaska Native (AI/AN) adults are disproportionately affected, with a prevalence of 14.5%—the highest among all racial and ethnic groups.1 Type 2 DM (T2DM) accounts for 90% to 95% of all DM cases and is a leading cause of morbidity and mortality due to its association with cardiovascular disease, kidney failure, and other complications.2

Maintaining glycemic control is important for managing T2DM and preventing microvascular and macrovascular complications.3 The cornerstone of diabetes self-management has been patient self-monitored blood glucose (SMBG) using finger-stick glucometers.4 However, SMBG provides measurements from a single point in time and requires frequent, painful, and inconvenient finger pricks, leading to decreased adherence.5,6 These limitations negatively affect patient engagement and overall glycemic control.7

Continuous glucose monitors (CGMs) offer real-time, continuous glucose readings and trends.8 CGMs improve glycemic control and reduce hypoglycemic episodes in patients who are insulin-dependent.9,10 Flash glucose monitors, a type of CGM that requires scanning to obtain glucose readings, provide similar benefits.11 Despite these demonstrated advantages, research has primarily focused on insulin-dependent populations, leaving a significant gap in understanding the effect of CGMs on patients with T2DM who are not insulin-dependent.12

Given the high prevalence of T2DM among AI/AN populations and the potential benefits of CGMs, this study sought to evaluate the effect of CGM use on glycemic control and other health metrics in patients with non–insulin-dependent T2DM in an AI/AN population. This focus addresses a critical knowledge gap and may inform clinical practices and policies to improve diabetes management in this high-risk group.

Methods

A retrospective observational study was conducted using deidentified electronic health records (EHRs) from 2019 to 2024 at a federally operated outpatient Indian Health Service (IHS) clinic serving an AI/AN population in the IHS Portland Area (Oregon, Washington, Idaho). The study protocol was reviewed and deemed exempt by institutional review boards at Washington State University and the Portland Area IHS.

Study Population

This study included patients diagnosed with non–insulin-dependent T2DM, had used a CGM for ≥ 1 year, and had hemoglobin A1c (HbA1c) measurements within 4 months prior to CGM initiation (baseline) and within ± 4 months after 1 year of CGM use. For other health metrics, including blood pressure (BP), weight, low-density lipoprotein cholesterol (LDL-C), and estimated glomerular filtration rate (eGFR), this study required measurements within 6 months before CGM initiation and within 6 months after 1 year of CGM use. The baseline HbA1c in the dataset ranged from 5.3% to > 14%.

Patients were excluded if they used insulin during the study period, had incomplete laboratory or clinical data for the required time frame, or had < 1 year of CGM use. The dataset did not include detailed information on oral DM medications; thus, we could not report or account for the type or number of oral hypoglycemic agents used by the patients. The IHS clinical applications coordinator compiled the dataset from the EHR, identifying patients who were prescribed and received a CGM at the clinic. All patients used the Abbott Freestyle Libre CGM, the only formulary CGM available at the clinic during the study period.

A 1-year follow-up endpoint was selected for several reasons: (1) to capture potential seasonal variations in diet and activity; (2) to align with the clinic’s standard practice of annual comprehensive diabetes evaluations; and (3) to allow sufficient time for patients to adapt to CGM use and reflect any meaningful changes in glycemic control.

All patients received standard DM care according to clinic protocols, which included DM self-management education and training. Patients met with the diabetes educator at least once, during which the educator emphasized making informed decisions using CGM data, such as adjusting dietary choices and physical activity levels to manage blood glucose concentrations effectively.

A total of 302 patients were initially identified. After applying exclusion criteria, 132 were excluded due to insulin use, and 77 were excluded due to incomplete HbA1c data within the specified time frames (Figure 1). The final sample included 93 patients.

1125FED-DM-CGM-F1
FIGURE 1. Patients included to determine effect of continuous glucose monitoring on glycemic control.
Abbreviations: eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol.

Measures

The primary outcome was the change in HbA1c levels from baseline to 1 year after CGM initiation. Secondary outcomes included changes in weight, systolic and diastolic BP, LDL-C concentrations, and eGFR. For the primary outcome, HbA1c values were collected within a grace period of ± 4 months from the baseline and 1-year time points. The laboratory’s upper reporting limit for HbA1c was 14%; values reported as “> 14%” were recorded as 14.1% for data analysis, although the actual values could have been higher.

For secondary outcomes, data were included if measurements were obtained within ± 6 months of the baseline and 1-year time points. Patients who did not have measurements within these time frames for specific metrics were excluded from secondary outcome analysis but remained in the overall study if they met the criteria for HbA1c and CGM use.

Statistical Analysis

Statistical analysis was performed using R statistical software version 4.4.2. Paired t tests were conducted to compare baseline and 1-year follow- up measurements for variables with parametric distributions. Wilcoxon signed-rank test was used for nonparametric data. A linear regression analysis was conducted to examine the relationship between baseline HbA1c levels and the change in HbA1c after 1 year of CGM use. Differences were considered significant at P < .05 set a priori. To guide future research, a posthoc power analysis was performed using Cohen’s d to estimate the required sample sizes for detecting significant effects, assuming a similar population.

Results

The study included 93 patients, with a mean (SD) age of 55 (13) years (range, 29-83 years). Of the participants, 56 were female (60%) and 37 were male (40%). All participants were identified as AI/AN and had non–insulin-dependent T2DM.

Primary Outcomes

A significant reduction in HbA1c levels was observed after 1 year of CGM use. The mean (SD) baseline HbA1c was 9.5% (2.4%), which decreased to 7.6% (2.2%) at 1-year follow-up (Table 1). This difference represents a mean change of -1.86% (2.4%) (95% CI, -2.35 to -1.37; P < .001 [paired t test, -7.53]).

1125FED-DM-CGM-T1

A linear regression model evaluated the relationship between baseline HbA1c (predictor) and the change in HbA1c after 1 year (outcome). The change in HbA1c was calculated as the difference between 1-year follow-up and baseline values. The regression model revealed a significant negative association between baseline HbA1c and the change in HbA1c (Β = -0.576; P < .001), indicating that higher baseline HbA1c values were associated with greater reductions in HbA1c over the year. The regression equation was: Change in HbA1c = 3.587 – 0.576 × Baseline HbA1c

The regression coefficient for baseline HbA1c was -0.576 (standard error, 0.083; t = -6.931; P < .001), indicating that for each 1% increase in baseline HbA1c, the reduction of HbA1c after 1 year increased by approximately 0.576% (Figure 2). The model explained 34.6% of the variance in HbA1c change (R2 = .345; adjusted R2 = .338).

1125FED-DM-CGM-F2
FIGURE 2. Impact of baseline level on the reduction in hemoglobin A1c.

Secondary Outcomes

Systolic BP decreased by a mean (SD) -4.9 (17) mm Hg; 95% CI, -8.6 to -1.11; P = .01, paired t test). However, no significant change was observed for diastolic BP (P = .77, paired t test). Similarly, no significant changes were observed in weight, LDL-C concentrations, or eGFR after 1 year of CGM use. A posthoc power analysis indicated that the study was underpowered to detect smaller effect sizes in secondary outcomes. For example, sample size estimates indicated that detecting significant changes in weight and LDL-C concentrations would require sample sizes of 152 and 220 patients, respectively (Table 2).

1125FED-DM-CGM-T2

Discussion

This study found a clinically significant reduction in HbA1c levels after 1 year among AI/AN patients with non–insulin-dependent T2DM who used CGMs. The mean HbA1c decreased 1.9%, from 9.5% at baseline to 7.6% after 1 year. This reduction is not only statistically significant (P < .001), it is clinically meaningful—even a 1% decrease in HbA1c is associated with substantial reductions in the risk of microvascular complications.3 The magnitude of the HbA1c reduction observed suggests CGM use may be associated with improved glycemic control in this high-risk population. By achieving lower HbA1c levels, patients may experience improved long-term health outcomes and a reduced burden of DM-related complications.

Changes in oral DM medications during the study period may have contributed to the observed improvements in HbA1c levels. While the dataset lacked detailed information on types or dosages of oral hypoglycemic agents used, adjustments in medication regimens are common in DM management and could significantly affect glycemic control. The inability to account for these changes results in an inability to attribute the improvements in HbA1c solely to CGM use. Future studies should collect comprehensive medication data to better isolate the effects of CGM use from other treatment modifications.

Another factor that may have contributed to the improved glycemic control is the DM self-management education and training patients received as part of standard care. Patients met with diabetes educators at least once and learned how to use the CGM device and interpret the data for self-management decisions. This education may have enhanced patient engagement and empowerment, enabling them to make informed choices about diet, physical activity, and medication adherence. Studies have shown that DM self-management education can significantly improve glycemic control and patient outcomes.13 By combining the CGM technology with targeted education, patients may have been better equipped to manage their condition, contributing to the observed reduction in HbA1c levels. Future studies should consider synergistic effects of CGM use and DM education when evaluating interventions for glycemic control.

The significant reduction in HbA1c indicates CGM use is associated with improved glycemic control in non–insulin-dependent T2DM. The linear regression analysis suggests patients with poorer glycemic control at baseline experienced greater reductions in HbA1c over the course of 1 year. This finding aligns with previous studies that have shown greater HbA1c reductions in patients with higher initial levels when using CGMs. Yaron et al reported similar findings: higher baseline HbA1c levels predicted more substantial improvements with CGM use in patients with T2DM on insulin therapy.14

This study contributes to existing research by examining the association between CGM use and glycemic control in patients with non– insulin-dependent T2DM within an AI/AN population, a group that has been underreported in previous studies. Most prior research has focused on insulin-dependent patients or populations with different ethnic backgrounds.12 By focusing on patients with non–insulin-dependent T2DM, this study highlights the broader applicability of CGMs beyond traditional use, showcasing their potential association with benefits in earlier stages of DM management. Targeting the AI/AN population addresses a critical knowledge gap, given the disproportionately high prevalence of T2DM and associated complications in this group. The findings of this study suggest integrating CGM technology into the standard care of AI/AN patients with non–insulin-dependent T2DM may be associated with improved glycemic control and may help reduce health disparities.

The modest decrease in systolic BP observed in this study may indicate potential cardiovascular benefits associated with CGM use, possibly due to improved glycemic control and increased patient engagement in self-management. However, given the limited sample size and exclusion criteria, the study lacked sufficient power to detect significant associations between CGM use and other secondary outcomes such as BP, weight, LDL-C, and eGFR. Therefore, the significant finding with systolic BP should be interpreted with caution.

The lack of significant changes in secondary outcomes may be attributed to the study’s limited sample size and the relatively short duration for observing changes in these parameters. Larger studies are needed to assess the full impact of CGM on these variables. The required sample sizes for achieving adequate power in future studies were calculated, highlighting the utility of our study as a pilot, providing critical data for the design of larger, adequately powered studies.

Limitations

The retrospective design of this study limits causal inferences. Moreover, potential confounding variables were not controlled, such as changes in medication regimens (other than insulin use), dietary counseling, or physical activity. Additionally, we could not account for the type or number of oral DM medications prescribed to patients. The dataset included only information on insulin use, without detailed records of other antidiabetic medications. This limitation may have influenced the observed change in glycemic control, as variations in medication regimens could affect HbA1c levels.

Because this study lacked a comparator group, the effect of CGM use cannot be definitively isolated from other factors (eg, medication changes, dietary modifications, or physical activity). Moreover, CGM devices can be costly and are not universally covered by all insurance or IHS programs, potentially limiting widespread implementation. Policy-level restrictions and patient-specific barriers may also hinder feasibility in other settings.

The small sample size may limit the generalizability of the findings. Of the initial 302 patients, about 69% were excluded due to insulin use or incomplete laboratory data. A ± 4-month window was selected to balance data quality with real-world practices. Extending this window further (eg, ± 6 months) might have included more participants but risked diluting the 1-year endpoint consistency. The lack of statistical significance in secondary metrics may be due to insufficient power rather than the absence of an effect.

Exclusion of patients due to incomplete data may have introduced selection bias. However, patients were included in the overall analysis if they met the criteria for HbA1c and CGM use, even if they lacked data for secondary outcomes. Additionally, the laboratory’s upper reporting limit for HbA1c was 14%, with values above this reported as “> 14%.” For analysis, these were recorded as 14.1%, which may underestimate the true baseline HbA1c levels and impact of the assessment of change. This occurred for 4 of the 93 patients included.

All patients used the Freestyle Libre CGM, which may limit the generalizability of the findings to other CGM brands or models. Differences in device features, accuracy, scanning frequency, and user experience may influence outcomes, and results might differ with other CGM technologies. The dataset did not include patients’ scanning frequency because this metric was not consistently included in the EHRs.

Conclusions

This study found that CGM use was significantly associated with improved glycemic control in patients with non–insulin-dependent T2DM within an AI/AN population, particularly among patients with higher baseline HbA1c levels. The findings suggest that CGMs may be a valuable tool for managing T2DM beyond insulin-dependent populations.

Additional research with larger sample sizes, control groups, and extended follow-up periods is recommended to explore long-term benefits and impacts on other health metrics. The sample size estimates derived from this study serve as a valuable resource for researchers designing future studies aimed at addressing these gaps. Future research that expands on our findings by including larger, more diverse cohorts, accounting for medication use, and exploring different CGM technologies will enhance understanding and contribute to more effective diabetes management strategies for varied populations.

References
  1. National diabetes statistics report. Centers for Disease Control and Prevention. May 15, 2024. Accessed October 7, 2025. https://www.cdc.gov/diabetes/php/data-research/index.html
  2. Elsayed NA, Aleppo G, Aroda VR, et al. 2. Classification and diagnosis of diabetes: standards of care in diabetes—2023. Diabetes Care. 2023;46:S19-S40. doi:10.2337/dc23-S002
  3. Fowler MJ. Microvascular and macrovascular complications of diabetes. Clin Diabetes. 2011;29:116-122. doi:10.2337/diaclin.29.3.116
  4. Pleus S, Freckmann G, Schauer S, et al. Self-monitoring of blood glucose as an integral part in the management of people with type 2 diabetes mellitus. Diabetes Ther. 2022;13:829-846. doi:10.1007/s13300-022-01254-8
  5. Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes: results from the Structured Testing Program study. Diabetes Care. 2011;34:262-267. doi:10.2337/dc10-1732
  6. Tanaka N, Yabe D, Murotani K, et al. Mental distress and health-related quality of life among type 1 and type 2 diabetes patients using self-monitoring of blood glucose: a cross-sectional questionnaire study in Japan. J Diabetes Investig. 2018;9:1203-1211. doi:10.1111/jdi.12827
  7. Hortensius J, Kars MC, Wierenga WS, et al. Perspectives of patients with type 1 or insulin-treated type 2 diabetes on self-monitoring of blood glucose: a qualitative study. BMC Public Health. 2012;12:167. doi:10.1186/1471-2458-12-167
  8. Didyuk O, Econom N, Guardia A, Livingston K, Klueh U. Continuous glucose monitoring devices: past, present, and future focus on the history and evolution of technological innovation. J Diabetes Sci Technol. 2021;15:676-683. doi:10.1177/1932296819899394
  9. Beck RW, Riddlesworth TD, Ruedy K, et al. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections: the DIAMOND randomized clinical trial. JAMA. 2017;317:371-378. doi:10.1001/jama.2016.19975
  10. Lind M, Polonsky W, Hirsch IB, et al. Continuous glucose monitoring vs conventional therapy for glycemic control in adults with type 1 diabetes treated with multiple daily insulin injections: the GOLD randomized clinical trial. JAMA. 2017;317:379-387. doi:10.1001/jama.2016.19976
  11. Bolinder J, Antuna R, Geelhoed-Duijvestijn P, et al. Novel glucose-sensing technology and hypoglycemia in type 1 diabetes: a multicenter, non-masked, randomized controlled trial. Lancet. 2016;388:2254-2263. doi:10.1016/S0140-6736(16)31535-5
  12. Seidu S, Kunutsor SK, Ajjan RA, et al. Efficacy and safety of continuous glucose monitoring and intermittently scanned continuous glucose monitoring in patients with type 2 diabetes: a systematic review and meta-analysis of interventional evidence. Diabetes Care. 2024;47:169-179. doi:10.2337/dc23-1520
  13. ElSayed NA, Aleppo G, Aroda VR, et al. 5. Facilitating positive health behaviors and well-being to improve health outcomes: standards of care in diabetes-2023. Diabetes Care. 2023;46:S68-S96. doi:10.2337/dc23-S005
  14. Yaron M, Roitman E, Aharon-Hananel G, et al. Effect of flash glucose monitoring technology on glycemic control and treatment satisfaction in patients with type 2 diabetes. Diabetes Care. 2019;42:1178-1184. doi:10.2337/dc18-0166
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Chantelle Robert, PA-Ca; Ryan G. Pett, PharmD, MPHb

Author affiliations aWashington State University, Pullman bPortland Area Indian Health Service, Oregon

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Ryan Pett (ryan.pett@ihs.gov)

Fed Pract. 2025;42(suppl 6). Published online November 10. doi:10.12788/fp.0644

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Correspondence: Ryan Pett (ryan.pett@ihs.gov)

Fed Pract. 2025;42(suppl 6). Published online November 10. doi:10.12788/fp.0644

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Fed Pract. 2025;42(suppl 6). Published online November 10. doi:10.12788/fp.0644

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Diabetes mellitus (DM) is a national health crisis affecting > 38 million people (11.6%) in the United States.1 American Indian and Alaska Native (AI/AN) adults are disproportionately affected, with a prevalence of 14.5%—the highest among all racial and ethnic groups.1 Type 2 DM (T2DM) accounts for 90% to 95% of all DM cases and is a leading cause of morbidity and mortality due to its association with cardiovascular disease, kidney failure, and other complications.2

Maintaining glycemic control is important for managing T2DM and preventing microvascular and macrovascular complications.3 The cornerstone of diabetes self-management has been patient self-monitored blood glucose (SMBG) using finger-stick glucometers.4 However, SMBG provides measurements from a single point in time and requires frequent, painful, and inconvenient finger pricks, leading to decreased adherence.5,6 These limitations negatively affect patient engagement and overall glycemic control.7

Continuous glucose monitors (CGMs) offer real-time, continuous glucose readings and trends.8 CGMs improve glycemic control and reduce hypoglycemic episodes in patients who are insulin-dependent.9,10 Flash glucose monitors, a type of CGM that requires scanning to obtain glucose readings, provide similar benefits.11 Despite these demonstrated advantages, research has primarily focused on insulin-dependent populations, leaving a significant gap in understanding the effect of CGMs on patients with T2DM who are not insulin-dependent.12

Given the high prevalence of T2DM among AI/AN populations and the potential benefits of CGMs, this study sought to evaluate the effect of CGM use on glycemic control and other health metrics in patients with non–insulin-dependent T2DM in an AI/AN population. This focus addresses a critical knowledge gap and may inform clinical practices and policies to improve diabetes management in this high-risk group.

Methods

A retrospective observational study was conducted using deidentified electronic health records (EHRs) from 2019 to 2024 at a federally operated outpatient Indian Health Service (IHS) clinic serving an AI/AN population in the IHS Portland Area (Oregon, Washington, Idaho). The study protocol was reviewed and deemed exempt by institutional review boards at Washington State University and the Portland Area IHS.

Study Population

This study included patients diagnosed with non–insulin-dependent T2DM, had used a CGM for ≥ 1 year, and had hemoglobin A1c (HbA1c) measurements within 4 months prior to CGM initiation (baseline) and within ± 4 months after 1 year of CGM use. For other health metrics, including blood pressure (BP), weight, low-density lipoprotein cholesterol (LDL-C), and estimated glomerular filtration rate (eGFR), this study required measurements within 6 months before CGM initiation and within 6 months after 1 year of CGM use. The baseline HbA1c in the dataset ranged from 5.3% to > 14%.

Patients were excluded if they used insulin during the study period, had incomplete laboratory or clinical data for the required time frame, or had < 1 year of CGM use. The dataset did not include detailed information on oral DM medications; thus, we could not report or account for the type or number of oral hypoglycemic agents used by the patients. The IHS clinical applications coordinator compiled the dataset from the EHR, identifying patients who were prescribed and received a CGM at the clinic. All patients used the Abbott Freestyle Libre CGM, the only formulary CGM available at the clinic during the study period.

A 1-year follow-up endpoint was selected for several reasons: (1) to capture potential seasonal variations in diet and activity; (2) to align with the clinic’s standard practice of annual comprehensive diabetes evaluations; and (3) to allow sufficient time for patients to adapt to CGM use and reflect any meaningful changes in glycemic control.

All patients received standard DM care according to clinic protocols, which included DM self-management education and training. Patients met with the diabetes educator at least once, during which the educator emphasized making informed decisions using CGM data, such as adjusting dietary choices and physical activity levels to manage blood glucose concentrations effectively.

A total of 302 patients were initially identified. After applying exclusion criteria, 132 were excluded due to insulin use, and 77 were excluded due to incomplete HbA1c data within the specified time frames (Figure 1). The final sample included 93 patients.

1125FED-DM-CGM-F1
FIGURE 1. Patients included to determine effect of continuous glucose monitoring on glycemic control.
Abbreviations: eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol.

Measures

The primary outcome was the change in HbA1c levels from baseline to 1 year after CGM initiation. Secondary outcomes included changes in weight, systolic and diastolic BP, LDL-C concentrations, and eGFR. For the primary outcome, HbA1c values were collected within a grace period of ± 4 months from the baseline and 1-year time points. The laboratory’s upper reporting limit for HbA1c was 14%; values reported as “> 14%” were recorded as 14.1% for data analysis, although the actual values could have been higher.

For secondary outcomes, data were included if measurements were obtained within ± 6 months of the baseline and 1-year time points. Patients who did not have measurements within these time frames for specific metrics were excluded from secondary outcome analysis but remained in the overall study if they met the criteria for HbA1c and CGM use.

Statistical Analysis

Statistical analysis was performed using R statistical software version 4.4.2. Paired t tests were conducted to compare baseline and 1-year follow- up measurements for variables with parametric distributions. Wilcoxon signed-rank test was used for nonparametric data. A linear regression analysis was conducted to examine the relationship between baseline HbA1c levels and the change in HbA1c after 1 year of CGM use. Differences were considered significant at P < .05 set a priori. To guide future research, a posthoc power analysis was performed using Cohen’s d to estimate the required sample sizes for detecting significant effects, assuming a similar population.

Results

The study included 93 patients, with a mean (SD) age of 55 (13) years (range, 29-83 years). Of the participants, 56 were female (60%) and 37 were male (40%). All participants were identified as AI/AN and had non–insulin-dependent T2DM.

Primary Outcomes

A significant reduction in HbA1c levels was observed after 1 year of CGM use. The mean (SD) baseline HbA1c was 9.5% (2.4%), which decreased to 7.6% (2.2%) at 1-year follow-up (Table 1). This difference represents a mean change of -1.86% (2.4%) (95% CI, -2.35 to -1.37; P < .001 [paired t test, -7.53]).

1125FED-DM-CGM-T1

A linear regression model evaluated the relationship between baseline HbA1c (predictor) and the change in HbA1c after 1 year (outcome). The change in HbA1c was calculated as the difference between 1-year follow-up and baseline values. The regression model revealed a significant negative association between baseline HbA1c and the change in HbA1c (Β = -0.576; P < .001), indicating that higher baseline HbA1c values were associated with greater reductions in HbA1c over the year. The regression equation was: Change in HbA1c = 3.587 – 0.576 × Baseline HbA1c

The regression coefficient for baseline HbA1c was -0.576 (standard error, 0.083; t = -6.931; P < .001), indicating that for each 1% increase in baseline HbA1c, the reduction of HbA1c after 1 year increased by approximately 0.576% (Figure 2). The model explained 34.6% of the variance in HbA1c change (R2 = .345; adjusted R2 = .338).

1125FED-DM-CGM-F2
FIGURE 2. Impact of baseline level on the reduction in hemoglobin A1c.

Secondary Outcomes

Systolic BP decreased by a mean (SD) -4.9 (17) mm Hg; 95% CI, -8.6 to -1.11; P = .01, paired t test). However, no significant change was observed for diastolic BP (P = .77, paired t test). Similarly, no significant changes were observed in weight, LDL-C concentrations, or eGFR after 1 year of CGM use. A posthoc power analysis indicated that the study was underpowered to detect smaller effect sizes in secondary outcomes. For example, sample size estimates indicated that detecting significant changes in weight and LDL-C concentrations would require sample sizes of 152 and 220 patients, respectively (Table 2).

1125FED-DM-CGM-T2

Discussion

This study found a clinically significant reduction in HbA1c levels after 1 year among AI/AN patients with non–insulin-dependent T2DM who used CGMs. The mean HbA1c decreased 1.9%, from 9.5% at baseline to 7.6% after 1 year. This reduction is not only statistically significant (P < .001), it is clinically meaningful—even a 1% decrease in HbA1c is associated with substantial reductions in the risk of microvascular complications.3 The magnitude of the HbA1c reduction observed suggests CGM use may be associated with improved glycemic control in this high-risk population. By achieving lower HbA1c levels, patients may experience improved long-term health outcomes and a reduced burden of DM-related complications.

Changes in oral DM medications during the study period may have contributed to the observed improvements in HbA1c levels. While the dataset lacked detailed information on types or dosages of oral hypoglycemic agents used, adjustments in medication regimens are common in DM management and could significantly affect glycemic control. The inability to account for these changes results in an inability to attribute the improvements in HbA1c solely to CGM use. Future studies should collect comprehensive medication data to better isolate the effects of CGM use from other treatment modifications.

Another factor that may have contributed to the improved glycemic control is the DM self-management education and training patients received as part of standard care. Patients met with diabetes educators at least once and learned how to use the CGM device and interpret the data for self-management decisions. This education may have enhanced patient engagement and empowerment, enabling them to make informed choices about diet, physical activity, and medication adherence. Studies have shown that DM self-management education can significantly improve glycemic control and patient outcomes.13 By combining the CGM technology with targeted education, patients may have been better equipped to manage their condition, contributing to the observed reduction in HbA1c levels. Future studies should consider synergistic effects of CGM use and DM education when evaluating interventions for glycemic control.

The significant reduction in HbA1c indicates CGM use is associated with improved glycemic control in non–insulin-dependent T2DM. The linear regression analysis suggests patients with poorer glycemic control at baseline experienced greater reductions in HbA1c over the course of 1 year. This finding aligns with previous studies that have shown greater HbA1c reductions in patients with higher initial levels when using CGMs. Yaron et al reported similar findings: higher baseline HbA1c levels predicted more substantial improvements with CGM use in patients with T2DM on insulin therapy.14

This study contributes to existing research by examining the association between CGM use and glycemic control in patients with non– insulin-dependent T2DM within an AI/AN population, a group that has been underreported in previous studies. Most prior research has focused on insulin-dependent patients or populations with different ethnic backgrounds.12 By focusing on patients with non–insulin-dependent T2DM, this study highlights the broader applicability of CGMs beyond traditional use, showcasing their potential association with benefits in earlier stages of DM management. Targeting the AI/AN population addresses a critical knowledge gap, given the disproportionately high prevalence of T2DM and associated complications in this group. The findings of this study suggest integrating CGM technology into the standard care of AI/AN patients with non–insulin-dependent T2DM may be associated with improved glycemic control and may help reduce health disparities.

The modest decrease in systolic BP observed in this study may indicate potential cardiovascular benefits associated with CGM use, possibly due to improved glycemic control and increased patient engagement in self-management. However, given the limited sample size and exclusion criteria, the study lacked sufficient power to detect significant associations between CGM use and other secondary outcomes such as BP, weight, LDL-C, and eGFR. Therefore, the significant finding with systolic BP should be interpreted with caution.

The lack of significant changes in secondary outcomes may be attributed to the study’s limited sample size and the relatively short duration for observing changes in these parameters. Larger studies are needed to assess the full impact of CGM on these variables. The required sample sizes for achieving adequate power in future studies were calculated, highlighting the utility of our study as a pilot, providing critical data for the design of larger, adequately powered studies.

Limitations

The retrospective design of this study limits causal inferences. Moreover, potential confounding variables were not controlled, such as changes in medication regimens (other than insulin use), dietary counseling, or physical activity. Additionally, we could not account for the type or number of oral DM medications prescribed to patients. The dataset included only information on insulin use, without detailed records of other antidiabetic medications. This limitation may have influenced the observed change in glycemic control, as variations in medication regimens could affect HbA1c levels.

Because this study lacked a comparator group, the effect of CGM use cannot be definitively isolated from other factors (eg, medication changes, dietary modifications, or physical activity). Moreover, CGM devices can be costly and are not universally covered by all insurance or IHS programs, potentially limiting widespread implementation. Policy-level restrictions and patient-specific barriers may also hinder feasibility in other settings.

The small sample size may limit the generalizability of the findings. Of the initial 302 patients, about 69% were excluded due to insulin use or incomplete laboratory data. A ± 4-month window was selected to balance data quality with real-world practices. Extending this window further (eg, ± 6 months) might have included more participants but risked diluting the 1-year endpoint consistency. The lack of statistical significance in secondary metrics may be due to insufficient power rather than the absence of an effect.

Exclusion of patients due to incomplete data may have introduced selection bias. However, patients were included in the overall analysis if they met the criteria for HbA1c and CGM use, even if they lacked data for secondary outcomes. Additionally, the laboratory’s upper reporting limit for HbA1c was 14%, with values above this reported as “> 14%.” For analysis, these were recorded as 14.1%, which may underestimate the true baseline HbA1c levels and impact of the assessment of change. This occurred for 4 of the 93 patients included.

All patients used the Freestyle Libre CGM, which may limit the generalizability of the findings to other CGM brands or models. Differences in device features, accuracy, scanning frequency, and user experience may influence outcomes, and results might differ with other CGM technologies. The dataset did not include patients’ scanning frequency because this metric was not consistently included in the EHRs.

Conclusions

This study found that CGM use was significantly associated with improved glycemic control in patients with non–insulin-dependent T2DM within an AI/AN population, particularly among patients with higher baseline HbA1c levels. The findings suggest that CGMs may be a valuable tool for managing T2DM beyond insulin-dependent populations.

Additional research with larger sample sizes, control groups, and extended follow-up periods is recommended to explore long-term benefits and impacts on other health metrics. The sample size estimates derived from this study serve as a valuable resource for researchers designing future studies aimed at addressing these gaps. Future research that expands on our findings by including larger, more diverse cohorts, accounting for medication use, and exploring different CGM technologies will enhance understanding and contribute to more effective diabetes management strategies for varied populations.

Diabetes mellitus (DM) is a national health crisis affecting > 38 million people (11.6%) in the United States.1 American Indian and Alaska Native (AI/AN) adults are disproportionately affected, with a prevalence of 14.5%—the highest among all racial and ethnic groups.1 Type 2 DM (T2DM) accounts for 90% to 95% of all DM cases and is a leading cause of morbidity and mortality due to its association with cardiovascular disease, kidney failure, and other complications.2

Maintaining glycemic control is important for managing T2DM and preventing microvascular and macrovascular complications.3 The cornerstone of diabetes self-management has been patient self-monitored blood glucose (SMBG) using finger-stick glucometers.4 However, SMBG provides measurements from a single point in time and requires frequent, painful, and inconvenient finger pricks, leading to decreased adherence.5,6 These limitations negatively affect patient engagement and overall glycemic control.7

Continuous glucose monitors (CGMs) offer real-time, continuous glucose readings and trends.8 CGMs improve glycemic control and reduce hypoglycemic episodes in patients who are insulin-dependent.9,10 Flash glucose monitors, a type of CGM that requires scanning to obtain glucose readings, provide similar benefits.11 Despite these demonstrated advantages, research has primarily focused on insulin-dependent populations, leaving a significant gap in understanding the effect of CGMs on patients with T2DM who are not insulin-dependent.12

Given the high prevalence of T2DM among AI/AN populations and the potential benefits of CGMs, this study sought to evaluate the effect of CGM use on glycemic control and other health metrics in patients with non–insulin-dependent T2DM in an AI/AN population. This focus addresses a critical knowledge gap and may inform clinical practices and policies to improve diabetes management in this high-risk group.

Methods

A retrospective observational study was conducted using deidentified electronic health records (EHRs) from 2019 to 2024 at a federally operated outpatient Indian Health Service (IHS) clinic serving an AI/AN population in the IHS Portland Area (Oregon, Washington, Idaho). The study protocol was reviewed and deemed exempt by institutional review boards at Washington State University and the Portland Area IHS.

Study Population

This study included patients diagnosed with non–insulin-dependent T2DM, had used a CGM for ≥ 1 year, and had hemoglobin A1c (HbA1c) measurements within 4 months prior to CGM initiation (baseline) and within ± 4 months after 1 year of CGM use. For other health metrics, including blood pressure (BP), weight, low-density lipoprotein cholesterol (LDL-C), and estimated glomerular filtration rate (eGFR), this study required measurements within 6 months before CGM initiation and within 6 months after 1 year of CGM use. The baseline HbA1c in the dataset ranged from 5.3% to > 14%.

Patients were excluded if they used insulin during the study period, had incomplete laboratory or clinical data for the required time frame, or had < 1 year of CGM use. The dataset did not include detailed information on oral DM medications; thus, we could not report or account for the type or number of oral hypoglycemic agents used by the patients. The IHS clinical applications coordinator compiled the dataset from the EHR, identifying patients who were prescribed and received a CGM at the clinic. All patients used the Abbott Freestyle Libre CGM, the only formulary CGM available at the clinic during the study period.

A 1-year follow-up endpoint was selected for several reasons: (1) to capture potential seasonal variations in diet and activity; (2) to align with the clinic’s standard practice of annual comprehensive diabetes evaluations; and (3) to allow sufficient time for patients to adapt to CGM use and reflect any meaningful changes in glycemic control.

All patients received standard DM care according to clinic protocols, which included DM self-management education and training. Patients met with the diabetes educator at least once, during which the educator emphasized making informed decisions using CGM data, such as adjusting dietary choices and physical activity levels to manage blood glucose concentrations effectively.

A total of 302 patients were initially identified. After applying exclusion criteria, 132 were excluded due to insulin use, and 77 were excluded due to incomplete HbA1c data within the specified time frames (Figure 1). The final sample included 93 patients.

1125FED-DM-CGM-F1
FIGURE 1. Patients included to determine effect of continuous glucose monitoring on glycemic control.
Abbreviations: eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol.

Measures

The primary outcome was the change in HbA1c levels from baseline to 1 year after CGM initiation. Secondary outcomes included changes in weight, systolic and diastolic BP, LDL-C concentrations, and eGFR. For the primary outcome, HbA1c values were collected within a grace period of ± 4 months from the baseline and 1-year time points. The laboratory’s upper reporting limit for HbA1c was 14%; values reported as “> 14%” were recorded as 14.1% for data analysis, although the actual values could have been higher.

For secondary outcomes, data were included if measurements were obtained within ± 6 months of the baseline and 1-year time points. Patients who did not have measurements within these time frames for specific metrics were excluded from secondary outcome analysis but remained in the overall study if they met the criteria for HbA1c and CGM use.

Statistical Analysis

Statistical analysis was performed using R statistical software version 4.4.2. Paired t tests were conducted to compare baseline and 1-year follow- up measurements for variables with parametric distributions. Wilcoxon signed-rank test was used for nonparametric data. A linear regression analysis was conducted to examine the relationship between baseline HbA1c levels and the change in HbA1c after 1 year of CGM use. Differences were considered significant at P < .05 set a priori. To guide future research, a posthoc power analysis was performed using Cohen’s d to estimate the required sample sizes for detecting significant effects, assuming a similar population.

Results

The study included 93 patients, with a mean (SD) age of 55 (13) years (range, 29-83 years). Of the participants, 56 were female (60%) and 37 were male (40%). All participants were identified as AI/AN and had non–insulin-dependent T2DM.

Primary Outcomes

A significant reduction in HbA1c levels was observed after 1 year of CGM use. The mean (SD) baseline HbA1c was 9.5% (2.4%), which decreased to 7.6% (2.2%) at 1-year follow-up (Table 1). This difference represents a mean change of -1.86% (2.4%) (95% CI, -2.35 to -1.37; P < .001 [paired t test, -7.53]).

1125FED-DM-CGM-T1

A linear regression model evaluated the relationship between baseline HbA1c (predictor) and the change in HbA1c after 1 year (outcome). The change in HbA1c was calculated as the difference between 1-year follow-up and baseline values. The regression model revealed a significant negative association between baseline HbA1c and the change in HbA1c (Β = -0.576; P < .001), indicating that higher baseline HbA1c values were associated with greater reductions in HbA1c over the year. The regression equation was: Change in HbA1c = 3.587 – 0.576 × Baseline HbA1c

The regression coefficient for baseline HbA1c was -0.576 (standard error, 0.083; t = -6.931; P < .001), indicating that for each 1% increase in baseline HbA1c, the reduction of HbA1c after 1 year increased by approximately 0.576% (Figure 2). The model explained 34.6% of the variance in HbA1c change (R2 = .345; adjusted R2 = .338).

1125FED-DM-CGM-F2
FIGURE 2. Impact of baseline level on the reduction in hemoglobin A1c.

Secondary Outcomes

Systolic BP decreased by a mean (SD) -4.9 (17) mm Hg; 95% CI, -8.6 to -1.11; P = .01, paired t test). However, no significant change was observed for diastolic BP (P = .77, paired t test). Similarly, no significant changes were observed in weight, LDL-C concentrations, or eGFR after 1 year of CGM use. A posthoc power analysis indicated that the study was underpowered to detect smaller effect sizes in secondary outcomes. For example, sample size estimates indicated that detecting significant changes in weight and LDL-C concentrations would require sample sizes of 152 and 220 patients, respectively (Table 2).

1125FED-DM-CGM-T2

Discussion

This study found a clinically significant reduction in HbA1c levels after 1 year among AI/AN patients with non–insulin-dependent T2DM who used CGMs. The mean HbA1c decreased 1.9%, from 9.5% at baseline to 7.6% after 1 year. This reduction is not only statistically significant (P < .001), it is clinically meaningful—even a 1% decrease in HbA1c is associated with substantial reductions in the risk of microvascular complications.3 The magnitude of the HbA1c reduction observed suggests CGM use may be associated with improved glycemic control in this high-risk population. By achieving lower HbA1c levels, patients may experience improved long-term health outcomes and a reduced burden of DM-related complications.

Changes in oral DM medications during the study period may have contributed to the observed improvements in HbA1c levels. While the dataset lacked detailed information on types or dosages of oral hypoglycemic agents used, adjustments in medication regimens are common in DM management and could significantly affect glycemic control. The inability to account for these changes results in an inability to attribute the improvements in HbA1c solely to CGM use. Future studies should collect comprehensive medication data to better isolate the effects of CGM use from other treatment modifications.

Another factor that may have contributed to the improved glycemic control is the DM self-management education and training patients received as part of standard care. Patients met with diabetes educators at least once and learned how to use the CGM device and interpret the data for self-management decisions. This education may have enhanced patient engagement and empowerment, enabling them to make informed choices about diet, physical activity, and medication adherence. Studies have shown that DM self-management education can significantly improve glycemic control and patient outcomes.13 By combining the CGM technology with targeted education, patients may have been better equipped to manage their condition, contributing to the observed reduction in HbA1c levels. Future studies should consider synergistic effects of CGM use and DM education when evaluating interventions for glycemic control.

The significant reduction in HbA1c indicates CGM use is associated with improved glycemic control in non–insulin-dependent T2DM. The linear regression analysis suggests patients with poorer glycemic control at baseline experienced greater reductions in HbA1c over the course of 1 year. This finding aligns with previous studies that have shown greater HbA1c reductions in patients with higher initial levels when using CGMs. Yaron et al reported similar findings: higher baseline HbA1c levels predicted more substantial improvements with CGM use in patients with T2DM on insulin therapy.14

This study contributes to existing research by examining the association between CGM use and glycemic control in patients with non– insulin-dependent T2DM within an AI/AN population, a group that has been underreported in previous studies. Most prior research has focused on insulin-dependent patients or populations with different ethnic backgrounds.12 By focusing on patients with non–insulin-dependent T2DM, this study highlights the broader applicability of CGMs beyond traditional use, showcasing their potential association with benefits in earlier stages of DM management. Targeting the AI/AN population addresses a critical knowledge gap, given the disproportionately high prevalence of T2DM and associated complications in this group. The findings of this study suggest integrating CGM technology into the standard care of AI/AN patients with non–insulin-dependent T2DM may be associated with improved glycemic control and may help reduce health disparities.

The modest decrease in systolic BP observed in this study may indicate potential cardiovascular benefits associated with CGM use, possibly due to improved glycemic control and increased patient engagement in self-management. However, given the limited sample size and exclusion criteria, the study lacked sufficient power to detect significant associations between CGM use and other secondary outcomes such as BP, weight, LDL-C, and eGFR. Therefore, the significant finding with systolic BP should be interpreted with caution.

The lack of significant changes in secondary outcomes may be attributed to the study’s limited sample size and the relatively short duration for observing changes in these parameters. Larger studies are needed to assess the full impact of CGM on these variables. The required sample sizes for achieving adequate power in future studies were calculated, highlighting the utility of our study as a pilot, providing critical data for the design of larger, adequately powered studies.

Limitations

The retrospective design of this study limits causal inferences. Moreover, potential confounding variables were not controlled, such as changes in medication regimens (other than insulin use), dietary counseling, or physical activity. Additionally, we could not account for the type or number of oral DM medications prescribed to patients. The dataset included only information on insulin use, without detailed records of other antidiabetic medications. This limitation may have influenced the observed change in glycemic control, as variations in medication regimens could affect HbA1c levels.

Because this study lacked a comparator group, the effect of CGM use cannot be definitively isolated from other factors (eg, medication changes, dietary modifications, or physical activity). Moreover, CGM devices can be costly and are not universally covered by all insurance or IHS programs, potentially limiting widespread implementation. Policy-level restrictions and patient-specific barriers may also hinder feasibility in other settings.

The small sample size may limit the generalizability of the findings. Of the initial 302 patients, about 69% were excluded due to insulin use or incomplete laboratory data. A ± 4-month window was selected to balance data quality with real-world practices. Extending this window further (eg, ± 6 months) might have included more participants but risked diluting the 1-year endpoint consistency. The lack of statistical significance in secondary metrics may be due to insufficient power rather than the absence of an effect.

Exclusion of patients due to incomplete data may have introduced selection bias. However, patients were included in the overall analysis if they met the criteria for HbA1c and CGM use, even if they lacked data for secondary outcomes. Additionally, the laboratory’s upper reporting limit for HbA1c was 14%, with values above this reported as “> 14%.” For analysis, these were recorded as 14.1%, which may underestimate the true baseline HbA1c levels and impact of the assessment of change. This occurred for 4 of the 93 patients included.

All patients used the Freestyle Libre CGM, which may limit the generalizability of the findings to other CGM brands or models. Differences in device features, accuracy, scanning frequency, and user experience may influence outcomes, and results might differ with other CGM technologies. The dataset did not include patients’ scanning frequency because this metric was not consistently included in the EHRs.

Conclusions

This study found that CGM use was significantly associated with improved glycemic control in patients with non–insulin-dependent T2DM within an AI/AN population, particularly among patients with higher baseline HbA1c levels. The findings suggest that CGMs may be a valuable tool for managing T2DM beyond insulin-dependent populations.

Additional research with larger sample sizes, control groups, and extended follow-up periods is recommended to explore long-term benefits and impacts on other health metrics. The sample size estimates derived from this study serve as a valuable resource for researchers designing future studies aimed at addressing these gaps. Future research that expands on our findings by including larger, more diverse cohorts, accounting for medication use, and exploring different CGM technologies will enhance understanding and contribute to more effective diabetes management strategies for varied populations.

References
  1. National diabetes statistics report. Centers for Disease Control and Prevention. May 15, 2024. Accessed October 7, 2025. https://www.cdc.gov/diabetes/php/data-research/index.html
  2. Elsayed NA, Aleppo G, Aroda VR, et al. 2. Classification and diagnosis of diabetes: standards of care in diabetes—2023. Diabetes Care. 2023;46:S19-S40. doi:10.2337/dc23-S002
  3. Fowler MJ. Microvascular and macrovascular complications of diabetes. Clin Diabetes. 2011;29:116-122. doi:10.2337/diaclin.29.3.116
  4. Pleus S, Freckmann G, Schauer S, et al. Self-monitoring of blood glucose as an integral part in the management of people with type 2 diabetes mellitus. Diabetes Ther. 2022;13:829-846. doi:10.1007/s13300-022-01254-8
  5. Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes: results from the Structured Testing Program study. Diabetes Care. 2011;34:262-267. doi:10.2337/dc10-1732
  6. Tanaka N, Yabe D, Murotani K, et al. Mental distress and health-related quality of life among type 1 and type 2 diabetes patients using self-monitoring of blood glucose: a cross-sectional questionnaire study in Japan. J Diabetes Investig. 2018;9:1203-1211. doi:10.1111/jdi.12827
  7. Hortensius J, Kars MC, Wierenga WS, et al. Perspectives of patients with type 1 or insulin-treated type 2 diabetes on self-monitoring of blood glucose: a qualitative study. BMC Public Health. 2012;12:167. doi:10.1186/1471-2458-12-167
  8. Didyuk O, Econom N, Guardia A, Livingston K, Klueh U. Continuous glucose monitoring devices: past, present, and future focus on the history and evolution of technological innovation. J Diabetes Sci Technol. 2021;15:676-683. doi:10.1177/1932296819899394
  9. Beck RW, Riddlesworth TD, Ruedy K, et al. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections: the DIAMOND randomized clinical trial. JAMA. 2017;317:371-378. doi:10.1001/jama.2016.19975
  10. Lind M, Polonsky W, Hirsch IB, et al. Continuous glucose monitoring vs conventional therapy for glycemic control in adults with type 1 diabetes treated with multiple daily insulin injections: the GOLD randomized clinical trial. JAMA. 2017;317:379-387. doi:10.1001/jama.2016.19976
  11. Bolinder J, Antuna R, Geelhoed-Duijvestijn P, et al. Novel glucose-sensing technology and hypoglycemia in type 1 diabetes: a multicenter, non-masked, randomized controlled trial. Lancet. 2016;388:2254-2263. doi:10.1016/S0140-6736(16)31535-5
  12. Seidu S, Kunutsor SK, Ajjan RA, et al. Efficacy and safety of continuous glucose monitoring and intermittently scanned continuous glucose monitoring in patients with type 2 diabetes: a systematic review and meta-analysis of interventional evidence. Diabetes Care. 2024;47:169-179. doi:10.2337/dc23-1520
  13. ElSayed NA, Aleppo G, Aroda VR, et al. 5. Facilitating positive health behaviors and well-being to improve health outcomes: standards of care in diabetes-2023. Diabetes Care. 2023;46:S68-S96. doi:10.2337/dc23-S005
  14. Yaron M, Roitman E, Aharon-Hananel G, et al. Effect of flash glucose monitoring technology on glycemic control and treatment satisfaction in patients with type 2 diabetes. Diabetes Care. 2019;42:1178-1184. doi:10.2337/dc18-0166
References
  1. National diabetes statistics report. Centers for Disease Control and Prevention. May 15, 2024. Accessed October 7, 2025. https://www.cdc.gov/diabetes/php/data-research/index.html
  2. Elsayed NA, Aleppo G, Aroda VR, et al. 2. Classification and diagnosis of diabetes: standards of care in diabetes—2023. Diabetes Care. 2023;46:S19-S40. doi:10.2337/dc23-S002
  3. Fowler MJ. Microvascular and macrovascular complications of diabetes. Clin Diabetes. 2011;29:116-122. doi:10.2337/diaclin.29.3.116
  4. Pleus S, Freckmann G, Schauer S, et al. Self-monitoring of blood glucose as an integral part in the management of people with type 2 diabetes mellitus. Diabetes Ther. 2022;13:829-846. doi:10.1007/s13300-022-01254-8
  5. Polonsky WH, Fisher L, Schikman CH, et al. Structured self-monitoring of blood glucose significantly reduces A1C levels in poorly controlled, noninsulin-treated type 2 diabetes: results from the Structured Testing Program study. Diabetes Care. 2011;34:262-267. doi:10.2337/dc10-1732
  6. Tanaka N, Yabe D, Murotani K, et al. Mental distress and health-related quality of life among type 1 and type 2 diabetes patients using self-monitoring of blood glucose: a cross-sectional questionnaire study in Japan. J Diabetes Investig. 2018;9:1203-1211. doi:10.1111/jdi.12827
  7. Hortensius J, Kars MC, Wierenga WS, et al. Perspectives of patients with type 1 or insulin-treated type 2 diabetes on self-monitoring of blood glucose: a qualitative study. BMC Public Health. 2012;12:167. doi:10.1186/1471-2458-12-167
  8. Didyuk O, Econom N, Guardia A, Livingston K, Klueh U. Continuous glucose monitoring devices: past, present, and future focus on the history and evolution of technological innovation. J Diabetes Sci Technol. 2021;15:676-683. doi:10.1177/1932296819899394
  9. Beck RW, Riddlesworth TD, Ruedy K, et al. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections: the DIAMOND randomized clinical trial. JAMA. 2017;317:371-378. doi:10.1001/jama.2016.19975
  10. Lind M, Polonsky W, Hirsch IB, et al. Continuous glucose monitoring vs conventional therapy for glycemic control in adults with type 1 diabetes treated with multiple daily insulin injections: the GOLD randomized clinical trial. JAMA. 2017;317:379-387. doi:10.1001/jama.2016.19976
  11. Bolinder J, Antuna R, Geelhoed-Duijvestijn P, et al. Novel glucose-sensing technology and hypoglycemia in type 1 diabetes: a multicenter, non-masked, randomized controlled trial. Lancet. 2016;388:2254-2263. doi:10.1016/S0140-6736(16)31535-5
  12. Seidu S, Kunutsor SK, Ajjan RA, et al. Efficacy and safety of continuous glucose monitoring and intermittently scanned continuous glucose monitoring in patients with type 2 diabetes: a systematic review and meta-analysis of interventional evidence. Diabetes Care. 2024;47:169-179. doi:10.2337/dc23-1520
  13. ElSayed NA, Aleppo G, Aroda VR, et al. 5. Facilitating positive health behaviors and well-being to improve health outcomes: standards of care in diabetes-2023. Diabetes Care. 2023;46:S68-S96. doi:10.2337/dc23-S005
  14. Yaron M, Roitman E, Aharon-Hananel G, et al. Effect of flash glucose monitoring technology on glycemic control and treatment satisfaction in patients with type 2 diabetes. Diabetes Care. 2019;42:1178-1184. doi:10.2337/dc18-0166
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Reducing Sex Disparities in Statin Therapy Among Female Veterans With Type 2 Diabetes and/or Cardiovascular Disease

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Reducing Sex Disparities in Statin Therapy Among Female Veterans With Type 2 Diabetes and/or Cardiovascular Disease

Cardiovascular disease (CVD) is the leading cause of death among women in the United States.1 Most CVD is due to the buildup of plaque (ie, cholesterol, proteins, calcium, and inflammatory cells) in artery walls.2 The plaque may lead to atherosclerotic cardiovascular disease (ASCVD), which includes coronary heart disease, cerebrovascular disease, peripheral artery disease, and aortic atherosclerotic disease.2,3 Control and reduction of ASCVD risk factors, including high cholesterol levels, elevated blood pressure, insulin resistance, smoking, and a sedentary lifestyle, can contribute to a reduction in ASCVD morbidity and mortality.2 People with type 2 diabetes mellitus (T2DM) have an increased prevalence of lipid abnormalities, contributing to their high risk of ASCVD.4,5

The prescribing of statins (3-hydroxy-3-methyl-glutaryl-coenzmye A reductase inhibitors) is the cornerstone of lipid-lowering therapy and cardiovascular risk reduction for primary and secondary prevention of ASCVD.6 The American Diabetes Association (ADA) and American College of Cardiology/American Heart Association (ACC/AHA) recommend moderate- to high-intensity statins for primary prevention in patients with T2DM and high-intensity statins for secondary prevention in those with or without diabetes when not contraindicated.4,5,7 Despite eligibility according to guideline recommendations, research predominantly shows that women are less likely to receive statin therapy; however, this trend is improving. [6,8-11] To explain the sex differences in statin use, Nanna et al found that there is a combination of women being offered statin therapy less frequently, declining therapy more frequently, and discontinuing treatment more frequently.11 One possibility for discontinuing treatment could be statin-associated muscle symptoms (SAMS), which occur in about 10% of patients.12 The incidence of adverse effects (AEs) may be related to the way statins are metabolized.

Pharmacogenomic testing is free for veterans through the US Department of Veterans Affairs (VA) PHASER program, which offers information and recommendations for a panel of 11 gene variants. The panel includes genes related to common medication classes such as anticoagulants, antiplatelets, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, opioids, antidepressants, and statins. The VA PHASER panel includes the solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which is predominantly expressed in the liver and facilitates the hepatic uptake of most statins.13,14 A reduced function of SLCO1B1 can lead to higher statin levels, resulting in increased concentrations that may potentially cause SAMS.13,14 Some alleles associated with reduced function include SLCO1B1*5, *15, *23, *31, and *46 to *49, whereas others are associated with increased function, such as SLCO1B1 *14 and *20 (Appendix).15 Supporting evidence shows the SLCO1B1*5 nucleotide polymorphism increases plasma levels of simvastatin and atorvastatin, affecting effectiveness or toxicity. 13 Females tend to have a lower body weight and higher percentage of body fat compared with males, which might lead to higher concentrations of lipophilic drugs, including atorvastatin and simvastatin, which may be exacerbated by decreased function of SLCO1B1*5.15 With pharmacogenomic testing, therapeutic recommendations can be made to improve the overall safety and efficacy of statins, thus improving adherence using a patient-specific approach.14,15

Methods

Carl Vinson VA Medical Center (CVVAMC) serves about 42,000 veterans in Central and South Georgia, of which about 15% are female. Of the female veterans enrolled in care, 63% identify as Black, 27% White, and 1.5% as Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander. The 2020 Veterans Chartbook report showed that female veterans and minority racial and ethnic groups had worse access to health care and higher mortality rates than their male and non-Hispanic White counterparts.16

The Primary Care Equity Dashboard (PCED) was developed to engage the VA health care workforce in the process of identifying and addressing inequities in local patient populations.17 Using electronic quality measure data, the PCED provides Veterans Integrated Service Network-level and facility-level performance on several metrics.18 The PCED had not been previously used at the CVVAMC, and few publications or quality improvement projects regarding its use have been reported by the VA Office of Health Equity. PCED helped identify disparities when comparing female to male patients in the prescribing of statin therapy for patients with CVD and statin therapy for patients with T2DM.

VA PHASER pharmacogenomic analyses provided an opportunity to expand this quality improvement project. Sanford Health and the VA collaborated on the PHASER program to offer free genetic testing for veterans. The program launched in 2019 and expanded to various VA sites, including CVVAMC in March 2023. This program has been extended to December 31, 2025.

The primary objective of this quality improvement project was to increase statin prescribing among female veterans with T2DM and/or CVD to reduce cardiovascular risk. Secondary outcomes included increased pharmacogenomic testing and the assessment of pharmacogenomic results related to statin therapy. This project was approved by the CVVAMC Pharmacy and Therapeutics Committee. The PCED was used to identify female veterans with T2DM and/or CVD without an active prescription for a statin between July and October 2023. A review of Computerized Patient Record System patient charts was completed to screen for prespecified inclusion and exclusion criteria. Veterans were included if they were assigned female at birth, were enrolled in care at CVVAMC, and had a diagnosis of T2DM or CVD (history of myocardial infarction, coronary bypass graft, percutaneous coronary intervention, or other revascularization in any setting).

Veterans were excluded if they were currently pregnant, trying to conceive, breastfeeding, had a T1DM diagnosis, had previously documented hypersensitivity to a statin, active liver failure or decompensated cirrhosis, previously documented statin-associated rhabdomyolysis or autoimmune myopathy, an active prescription for a proprotein convertase subtilisin/kexin type 9 inhibitor, or previously documented statin intolerance (defined as the inability to tolerate ≥ 3 statins, with ≥ 1 prescribed at low intensity or alternate-day dosing). The female veterans were compared to 2 comparators: the facility's male veterans and the VA national average, identified via the PCED.

Once a veteran was screened, they were telephoned between October 2023 and February 2024 and provided education on statin use and pharmacogenomic testing using a standardized note template. An order was placed for participants who provided verbal consent for pharmacogenomic testing. Those who agreed to statin initiation were referred to a clinical pharmacist practitioner (CPP) who contacted them at a later date to prescribe a statin following the recommendations of the 2019 ACC/AHA and 2023 ADA guidelines and pharmacogenomic testing, if applicable.4,5,7 Appropriate monitoring and follow-up occurred at the discretion of each CPP. Data collection included: age, race, diagnoses (T2DM, CVD, or both), baseline lipid panel (total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein), hepatic function, name and dose of statin, reasons for declining statin therapy, and pharmacogenomic testing results related to SLCO1B1.

Results

At baseline in July 2023, 77.8% of female veterans with T2DM were prescribed a statin, which exceeded the national VA average (77.0%), but was below the rate for male veterans (78.7%) in the facility comparator group.17 Additionally, 82.2% of females with CVD were prescribed a statin, which was below the national VA average of 86.0% and the 84.9% of male veterans in the facility comparator group.17 The PCED identified 189 female veterans from July 2023 to October 2023 who may benefit from statin therapy. Thirty-three females met the exclusion criteria. Of the 156 included veterans, 129 (82.7%) were successfully contacted and 27 (17.3%) could not be reached by telephone after 3 attempts (Figure 1). The 129 female veterans contacted had a mean age of 59 years and the majority were Black (82.9%) (Table 1).

1125FED-DM-Statin-T1
1125FED-DM-Statin-F1
FIGURE 1. Flow Diagram of Patient Selection
Abbreviations: CVD, cardiovascular disease; PCSK9, proprotein convertase subtilisin/
kexin type 9; T2DM, type 2 diabetes mellitus; VAMC, Veterans Affairs medical center.

Primary Outcomes

Of the 129 contacted veterans, 31 (24.0%) had a non-VA statin prescription, 13 (10.1%) had an active VA statin prescription, and 85 (65.9%) did not have a statin prescription, despite being eligible. Statin adherence was confirmed with participants, and the medication list was updated accordingly.

Of the 85 veterans with no active statin therapy, 37 (43.5%) accepted a new statin prescription and 48 (56.5%) declined. There were various reasons provided for declining statin therapy: 17 participants (35.4%) declined due to concern for AEs (Table 2).

1125FED-DM-Statin-T2

From July 2023 to March 2024, the percentage of female veterans with active statin therapy with T2DM increased from 77.8% to 79.0%. For those with active statin therapy with CVD, usage increased from 82.2% to 90.2%, which exceeded the national VA average and facility male comparator group (Figures 2 and 3).17

1125FED-DM-Statin-F2
FIGURE 2. Statin Prescribing in Veterans With Type 2 Diabetes Mellitus
1125FED-DM-Statin-F3
FIGURE 3. Statin Prescribing in Veterans With Cardiovascular Disease

Secondary Outcomes

Seventy-one of 129 veterans (55.0%) gave verbal consent, and 47 (66.2%) completed the pharmacogenomic testing; 58 (45.0%) declined. Five veterans (10.6%) had a known SLCO1B1 allele variant present. One veteran required a change in statin therapy based on the results (eAppendix).

1125FED-DM-Statin-A1

Discussion

This project aimed to increase statin prescribing among female veterans with T2DM and/or CVD to reduce cardiovascular risk and increase pharmacogenomic testing using the PCED and care managed by CPPs. The results of this quality improvement project illustrated that both metrics have improved at CVVAMC as a result of the intervention. The results in both metrics now exceed the PCED national VA average, and the CVD metric also exceeds that of the facility male comparator group. While there was only a 1.2% increase from July 2023 to March 2024 for patients with T2DM, there was an 8.0% increase for patients with CVD. Despite standardized education on statin use, more veterans declined therapy than accepted it, mostly due to concern for AEs. Recording the reasons for declining statin therapy offered valuable insight that can be used in additional discussions with veterans and clinicians.

Pharmacogenomics gives clinicians the unique opportunity to take a proactive approach to better predict drug responses, potentially allowing for less trial and error with medications, fewer AEs, greater trust in the clinician, and improved medication adherence. The CPPs incorporated pharmacogenomic testing into their practice, which led to identifying 5 SLCO1B1 gene abnormalities. The PCED served as a powerful tool for advancing equity-focused quality improvement initiatives on a local level and was crucial in prioritizing the detection of veterans potentially receiving suboptimal care.

Limitations

The nature of “cold calls” made it challenging to establish contact for inclusion in this study. An alternative to increase engagement could have been scheduled phone or face-to-face visits. While the use of the PCED was crucial, data did not account for statins listed in the non-VA medication list. All 31 patients with statins prescribed outside the VA had a start date added to provide the most accurate representation of the data moving forward.

Another limitation in this project was its small sample size and population. CVVAMC serves about 6200 female veterans, with roughly 63% identifying as Black. The preponderance of Black individuals (83%) in this project is typical for the female patient population at CVVAMC but may not reflect the demographics of other populations. Other limitations to this project consisted of scheduling conflicts. Appointments for laboratory draws at community-based outpatient clinics were subject to availability, which resulted in some delay in completion of pharmacogenomic testing.

Conclusions

CPPs can help reduce inequity in health care delivery. Increased incorporation of the PCED into regular practice within the VA is recommended to continue addressing sex disparities in statin use, diabetes control, blood pressure management, cancer screenings, and vaccination needs. CVVAMC plans to expand its use through another quality improvement project focused on reducing sex disparities in blood pressure management. Improving educational resources made available to veterans on the importance of statin therapy and potential to mitigate AEs through use of the VA PHASER program also would be helpful. This project successfully improved CVVAMC metrics for female veterans appropriately prescribed statin therapy and increased access to pharmacogenomic testing. Most importantly, it helped close the sex-based gap in CVD risk reduction care.

References
  1. Heron M. Deaths: leading causes for 2018. Nat Vital Stat Rep. 2021;70:1-114.
  2. US Department of Veterans Affairs, US Department of Defense. VA/DoD Clinical practice guideline for the management of dyslipidemia for cardiovascular risk reduction. Published June 2020. Accessed August 25, 2025. https://www.healthquality.va.gov/guidelines/CD/lipids/VADODDyslipidemiaCPG5087212020.pdf
  3. Atherosclerotic Cardiovascular Disease (ASCVD). American Heart Association. Accessed August 26, 2025. https:// www.heart.org/en/professional/quality-improvement/ascvd
  4. American Diabetes Association Professional Practice Committee. 10. Cardiovascular disease and risk management: standards of medical care in diabetes-2022. Diabetes Care. 2022;45(Suppl 1):S144-S174. doi:10.2337/dc22-S010
  5. American Diabetes Association. Standards of Care in Diabetes— 2023 abridged for primary care providers. Clinical Diabetes. 2022;41(1):4-31. doi:10.2337/cd23-as01
  6. Virani SS, Woodard LD, Ramsey DJ, et al. Gender disparities in evidence-based statin therapy in patients with cardiovascular disease. Am J Cardiol. 2015;115:21-26. doi:10.1016/j.amjcard.2014.09.041
  7. Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/ AHA Guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/ American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
  8. Buchanan CH, Brown EA, Bishu KG, et al. The magnitude and potential causes of gender disparities in statin therapy in veterans with type 2 diabetes: a 10-year nationwide longitudinal cohort study. Womens Health Issues. 2022;32:274-283. doi:10.1016/j.whi.2021.10.003
  9. Ahmed F, Lin J, Ahmed T, et al. Health disparities: statin prescribing patterns among patients with diabetes in a family medicine clinic. Health Equity. 2022;6:291-297. doi:10.1089/heq.2021.0144
  10. Metser G, Bradley C, Moise N, Liyanage-Don N, Kronish I, Ye S. Gaps and disparities in primary prevention statin prescription during outpatient care. Am J Cardiol. 2021;161:36-41. doi:10.1016/j.amjcard.2021.08.070
  11. Nanna MG, Wang TY, Xiang Q, et al. Sex differences in the use of statins in community practice. Circ Cardiovasc Qual Outcomes. 2019;12(8):e005562. doi:10.1161/CIRCOUTCOMES.118.005562
  12. Kitzmiller JP, Mikulik EB, Dauki AM, Murkherjee C, Luzum JA. Pharmacogenomics of statins: understanding susceptibility to adverse effects. Pharmgenomics Pers Med. 2016;9:97-106. doi:10.2147/PGPM.S86013
  13. Türkmen D, Masoli JAH, Kuo CL, Bowden J, Melzer D, Pilling LC. Statin treatment effectiveness and the SLCO1B1*5 reduced function genotype: long-term outcomes in women and men. Br J Clin Pharmacol. 2022;88:3230-3240. doi:10.1111/bcp.15245
  14. Cooper-DeHoff RM, Niemi M, Ramsey LB, et al. The Clinical Pharmacogenetics Implementation Consortium guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and statin-associated musculoskeletal symptoms. Clin Pharmacol Ther. 2022;111:1007-1021. doi:10.1002/cpt.2557
  15. Ramsey LB, Gong L, Lee SB, et al. PharmVar GeneFocus: SLCO1B1. Clin Pharmacol Ther. 2023;113:782-793. doi:10.1002/cpt.2705
  16. National Healthcare Quality and Disparities Report: Chartbook on Healthcare for Veterans. Rockville (MD): Agency for Healthcare Research and Quality (US); November 2020.
  17. Procario G. Primary Care Equity Dashboard [database online]. Power Bi. 2023. Accessed August 26, 2025. https://app.powerbigov.us
  18. Hausmann LRM, Lamorte C, Estock JL. Understanding the context for incorporating equity into quality improvement throughout a national health care system. Health Equity. 2023;7(1):312-320. doi:10.1089/heq.2023.0009
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Schylar Cheyenne Hathaway, PharmDa; Lindsey Pearsall, PharmD, BCACPa; Paul Hansen, PharmD, BCACPa; Nathaniel Swanson, PharmDa; Marci Swanson, PharmD, BCACPa; Deborah Hobbs, PharmDa

Author affiliations aCarl Vinson Veterans Affairs Medical Center, Dublin, Georgia

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Schylar Hathaway (schylar.c.hathaway@ gmail.com)

Fed Pract. 2025;42(suppl 6). Published online November 10. doi:10.12788/fp.0624

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Author affiliations aCarl Vinson Veterans Affairs Medical Center, Dublin, Georgia

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Schylar Hathaway (schylar.c.hathaway@ gmail.com)

Fed Pract. 2025;42(suppl 6). Published online November 10. doi:10.12788/fp.0624

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Author affiliations aCarl Vinson Veterans Affairs Medical Center, Dublin, Georgia

Author disclosures The authors report no actual or potential conflicts of interest with regard to this article.

Correspondence: Schylar Hathaway (schylar.c.hathaway@ gmail.com)

Fed Pract. 2025;42(suppl 6). Published online November 10. doi:10.12788/fp.0624

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Cardiovascular disease (CVD) is the leading cause of death among women in the United States.1 Most CVD is due to the buildup of plaque (ie, cholesterol, proteins, calcium, and inflammatory cells) in artery walls.2 The plaque may lead to atherosclerotic cardiovascular disease (ASCVD), which includes coronary heart disease, cerebrovascular disease, peripheral artery disease, and aortic atherosclerotic disease.2,3 Control and reduction of ASCVD risk factors, including high cholesterol levels, elevated blood pressure, insulin resistance, smoking, and a sedentary lifestyle, can contribute to a reduction in ASCVD morbidity and mortality.2 People with type 2 diabetes mellitus (T2DM) have an increased prevalence of lipid abnormalities, contributing to their high risk of ASCVD.4,5

The prescribing of statins (3-hydroxy-3-methyl-glutaryl-coenzmye A reductase inhibitors) is the cornerstone of lipid-lowering therapy and cardiovascular risk reduction for primary and secondary prevention of ASCVD.6 The American Diabetes Association (ADA) and American College of Cardiology/American Heart Association (ACC/AHA) recommend moderate- to high-intensity statins for primary prevention in patients with T2DM and high-intensity statins for secondary prevention in those with or without diabetes when not contraindicated.4,5,7 Despite eligibility according to guideline recommendations, research predominantly shows that women are less likely to receive statin therapy; however, this trend is improving. [6,8-11] To explain the sex differences in statin use, Nanna et al found that there is a combination of women being offered statin therapy less frequently, declining therapy more frequently, and discontinuing treatment more frequently.11 One possibility for discontinuing treatment could be statin-associated muscle symptoms (SAMS), which occur in about 10% of patients.12 The incidence of adverse effects (AEs) may be related to the way statins are metabolized.

Pharmacogenomic testing is free for veterans through the US Department of Veterans Affairs (VA) PHASER program, which offers information and recommendations for a panel of 11 gene variants. The panel includes genes related to common medication classes such as anticoagulants, antiplatelets, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, opioids, antidepressants, and statins. The VA PHASER panel includes the solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which is predominantly expressed in the liver and facilitates the hepatic uptake of most statins.13,14 A reduced function of SLCO1B1 can lead to higher statin levels, resulting in increased concentrations that may potentially cause SAMS.13,14 Some alleles associated with reduced function include SLCO1B1*5, *15, *23, *31, and *46 to *49, whereas others are associated with increased function, such as SLCO1B1 *14 and *20 (Appendix).15 Supporting evidence shows the SLCO1B1*5 nucleotide polymorphism increases plasma levels of simvastatin and atorvastatin, affecting effectiveness or toxicity. 13 Females tend to have a lower body weight and higher percentage of body fat compared with males, which might lead to higher concentrations of lipophilic drugs, including atorvastatin and simvastatin, which may be exacerbated by decreased function of SLCO1B1*5.15 With pharmacogenomic testing, therapeutic recommendations can be made to improve the overall safety and efficacy of statins, thus improving adherence using a patient-specific approach.14,15

Methods

Carl Vinson VA Medical Center (CVVAMC) serves about 42,000 veterans in Central and South Georgia, of which about 15% are female. Of the female veterans enrolled in care, 63% identify as Black, 27% White, and 1.5% as Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander. The 2020 Veterans Chartbook report showed that female veterans and minority racial and ethnic groups had worse access to health care and higher mortality rates than their male and non-Hispanic White counterparts.16

The Primary Care Equity Dashboard (PCED) was developed to engage the VA health care workforce in the process of identifying and addressing inequities in local patient populations.17 Using electronic quality measure data, the PCED provides Veterans Integrated Service Network-level and facility-level performance on several metrics.18 The PCED had not been previously used at the CVVAMC, and few publications or quality improvement projects regarding its use have been reported by the VA Office of Health Equity. PCED helped identify disparities when comparing female to male patients in the prescribing of statin therapy for patients with CVD and statin therapy for patients with T2DM.

VA PHASER pharmacogenomic analyses provided an opportunity to expand this quality improvement project. Sanford Health and the VA collaborated on the PHASER program to offer free genetic testing for veterans. The program launched in 2019 and expanded to various VA sites, including CVVAMC in March 2023. This program has been extended to December 31, 2025.

The primary objective of this quality improvement project was to increase statin prescribing among female veterans with T2DM and/or CVD to reduce cardiovascular risk. Secondary outcomes included increased pharmacogenomic testing and the assessment of pharmacogenomic results related to statin therapy. This project was approved by the CVVAMC Pharmacy and Therapeutics Committee. The PCED was used to identify female veterans with T2DM and/or CVD without an active prescription for a statin between July and October 2023. A review of Computerized Patient Record System patient charts was completed to screen for prespecified inclusion and exclusion criteria. Veterans were included if they were assigned female at birth, were enrolled in care at CVVAMC, and had a diagnosis of T2DM or CVD (history of myocardial infarction, coronary bypass graft, percutaneous coronary intervention, or other revascularization in any setting).

Veterans were excluded if they were currently pregnant, trying to conceive, breastfeeding, had a T1DM diagnosis, had previously documented hypersensitivity to a statin, active liver failure or decompensated cirrhosis, previously documented statin-associated rhabdomyolysis or autoimmune myopathy, an active prescription for a proprotein convertase subtilisin/kexin type 9 inhibitor, or previously documented statin intolerance (defined as the inability to tolerate ≥ 3 statins, with ≥ 1 prescribed at low intensity or alternate-day dosing). The female veterans were compared to 2 comparators: the facility's male veterans and the VA national average, identified via the PCED.

Once a veteran was screened, they were telephoned between October 2023 and February 2024 and provided education on statin use and pharmacogenomic testing using a standardized note template. An order was placed for participants who provided verbal consent for pharmacogenomic testing. Those who agreed to statin initiation were referred to a clinical pharmacist practitioner (CPP) who contacted them at a later date to prescribe a statin following the recommendations of the 2019 ACC/AHA and 2023 ADA guidelines and pharmacogenomic testing, if applicable.4,5,7 Appropriate monitoring and follow-up occurred at the discretion of each CPP. Data collection included: age, race, diagnoses (T2DM, CVD, or both), baseline lipid panel (total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein), hepatic function, name and dose of statin, reasons for declining statin therapy, and pharmacogenomic testing results related to SLCO1B1.

Results

At baseline in July 2023, 77.8% of female veterans with T2DM were prescribed a statin, which exceeded the national VA average (77.0%), but was below the rate for male veterans (78.7%) in the facility comparator group.17 Additionally, 82.2% of females with CVD were prescribed a statin, which was below the national VA average of 86.0% and the 84.9% of male veterans in the facility comparator group.17 The PCED identified 189 female veterans from July 2023 to October 2023 who may benefit from statin therapy. Thirty-three females met the exclusion criteria. Of the 156 included veterans, 129 (82.7%) were successfully contacted and 27 (17.3%) could not be reached by telephone after 3 attempts (Figure 1). The 129 female veterans contacted had a mean age of 59 years and the majority were Black (82.9%) (Table 1).

1125FED-DM-Statin-T1
1125FED-DM-Statin-F1
FIGURE 1. Flow Diagram of Patient Selection
Abbreviations: CVD, cardiovascular disease; PCSK9, proprotein convertase subtilisin/
kexin type 9; T2DM, type 2 diabetes mellitus; VAMC, Veterans Affairs medical center.

Primary Outcomes

Of the 129 contacted veterans, 31 (24.0%) had a non-VA statin prescription, 13 (10.1%) had an active VA statin prescription, and 85 (65.9%) did not have a statin prescription, despite being eligible. Statin adherence was confirmed with participants, and the medication list was updated accordingly.

Of the 85 veterans with no active statin therapy, 37 (43.5%) accepted a new statin prescription and 48 (56.5%) declined. There were various reasons provided for declining statin therapy: 17 participants (35.4%) declined due to concern for AEs (Table 2).

1125FED-DM-Statin-T2

From July 2023 to March 2024, the percentage of female veterans with active statin therapy with T2DM increased from 77.8% to 79.0%. For those with active statin therapy with CVD, usage increased from 82.2% to 90.2%, which exceeded the national VA average and facility male comparator group (Figures 2 and 3).17

1125FED-DM-Statin-F2
FIGURE 2. Statin Prescribing in Veterans With Type 2 Diabetes Mellitus
1125FED-DM-Statin-F3
FIGURE 3. Statin Prescribing in Veterans With Cardiovascular Disease

Secondary Outcomes

Seventy-one of 129 veterans (55.0%) gave verbal consent, and 47 (66.2%) completed the pharmacogenomic testing; 58 (45.0%) declined. Five veterans (10.6%) had a known SLCO1B1 allele variant present. One veteran required a change in statin therapy based on the results (eAppendix).

1125FED-DM-Statin-A1

Discussion

This project aimed to increase statin prescribing among female veterans with T2DM and/or CVD to reduce cardiovascular risk and increase pharmacogenomic testing using the PCED and care managed by CPPs. The results of this quality improvement project illustrated that both metrics have improved at CVVAMC as a result of the intervention. The results in both metrics now exceed the PCED national VA average, and the CVD metric also exceeds that of the facility male comparator group. While there was only a 1.2% increase from July 2023 to March 2024 for patients with T2DM, there was an 8.0% increase for patients with CVD. Despite standardized education on statin use, more veterans declined therapy than accepted it, mostly due to concern for AEs. Recording the reasons for declining statin therapy offered valuable insight that can be used in additional discussions with veterans and clinicians.

Pharmacogenomics gives clinicians the unique opportunity to take a proactive approach to better predict drug responses, potentially allowing for less trial and error with medications, fewer AEs, greater trust in the clinician, and improved medication adherence. The CPPs incorporated pharmacogenomic testing into their practice, which led to identifying 5 SLCO1B1 gene abnormalities. The PCED served as a powerful tool for advancing equity-focused quality improvement initiatives on a local level and was crucial in prioritizing the detection of veterans potentially receiving suboptimal care.

Limitations

The nature of “cold calls” made it challenging to establish contact for inclusion in this study. An alternative to increase engagement could have been scheduled phone or face-to-face visits. While the use of the PCED was crucial, data did not account for statins listed in the non-VA medication list. All 31 patients with statins prescribed outside the VA had a start date added to provide the most accurate representation of the data moving forward.

Another limitation in this project was its small sample size and population. CVVAMC serves about 6200 female veterans, with roughly 63% identifying as Black. The preponderance of Black individuals (83%) in this project is typical for the female patient population at CVVAMC but may not reflect the demographics of other populations. Other limitations to this project consisted of scheduling conflicts. Appointments for laboratory draws at community-based outpatient clinics were subject to availability, which resulted in some delay in completion of pharmacogenomic testing.

Conclusions

CPPs can help reduce inequity in health care delivery. Increased incorporation of the PCED into regular practice within the VA is recommended to continue addressing sex disparities in statin use, diabetes control, blood pressure management, cancer screenings, and vaccination needs. CVVAMC plans to expand its use through another quality improvement project focused on reducing sex disparities in blood pressure management. Improving educational resources made available to veterans on the importance of statin therapy and potential to mitigate AEs through use of the VA PHASER program also would be helpful. This project successfully improved CVVAMC metrics for female veterans appropriately prescribed statin therapy and increased access to pharmacogenomic testing. Most importantly, it helped close the sex-based gap in CVD risk reduction care.

Cardiovascular disease (CVD) is the leading cause of death among women in the United States.1 Most CVD is due to the buildup of plaque (ie, cholesterol, proteins, calcium, and inflammatory cells) in artery walls.2 The plaque may lead to atherosclerotic cardiovascular disease (ASCVD), which includes coronary heart disease, cerebrovascular disease, peripheral artery disease, and aortic atherosclerotic disease.2,3 Control and reduction of ASCVD risk factors, including high cholesterol levels, elevated blood pressure, insulin resistance, smoking, and a sedentary lifestyle, can contribute to a reduction in ASCVD morbidity and mortality.2 People with type 2 diabetes mellitus (T2DM) have an increased prevalence of lipid abnormalities, contributing to their high risk of ASCVD.4,5

The prescribing of statins (3-hydroxy-3-methyl-glutaryl-coenzmye A reductase inhibitors) is the cornerstone of lipid-lowering therapy and cardiovascular risk reduction for primary and secondary prevention of ASCVD.6 The American Diabetes Association (ADA) and American College of Cardiology/American Heart Association (ACC/AHA) recommend moderate- to high-intensity statins for primary prevention in patients with T2DM and high-intensity statins for secondary prevention in those with or without diabetes when not contraindicated.4,5,7 Despite eligibility according to guideline recommendations, research predominantly shows that women are less likely to receive statin therapy; however, this trend is improving. [6,8-11] To explain the sex differences in statin use, Nanna et al found that there is a combination of women being offered statin therapy less frequently, declining therapy more frequently, and discontinuing treatment more frequently.11 One possibility for discontinuing treatment could be statin-associated muscle symptoms (SAMS), which occur in about 10% of patients.12 The incidence of adverse effects (AEs) may be related to the way statins are metabolized.

Pharmacogenomic testing is free for veterans through the US Department of Veterans Affairs (VA) PHASER program, which offers information and recommendations for a panel of 11 gene variants. The panel includes genes related to common medication classes such as anticoagulants, antiplatelets, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, opioids, antidepressants, and statins. The VA PHASER panel includes the solute carrier organic anion transporter family member 1B1 (SLCO1B1) gene, which is predominantly expressed in the liver and facilitates the hepatic uptake of most statins.13,14 A reduced function of SLCO1B1 can lead to higher statin levels, resulting in increased concentrations that may potentially cause SAMS.13,14 Some alleles associated with reduced function include SLCO1B1*5, *15, *23, *31, and *46 to *49, whereas others are associated with increased function, such as SLCO1B1 *14 and *20 (Appendix).15 Supporting evidence shows the SLCO1B1*5 nucleotide polymorphism increases plasma levels of simvastatin and atorvastatin, affecting effectiveness or toxicity. 13 Females tend to have a lower body weight and higher percentage of body fat compared with males, which might lead to higher concentrations of lipophilic drugs, including atorvastatin and simvastatin, which may be exacerbated by decreased function of SLCO1B1*5.15 With pharmacogenomic testing, therapeutic recommendations can be made to improve the overall safety and efficacy of statins, thus improving adherence using a patient-specific approach.14,15

Methods

Carl Vinson VA Medical Center (CVVAMC) serves about 42,000 veterans in Central and South Georgia, of which about 15% are female. Of the female veterans enrolled in care, 63% identify as Black, 27% White, and 1.5% as Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander. The 2020 Veterans Chartbook report showed that female veterans and minority racial and ethnic groups had worse access to health care and higher mortality rates than their male and non-Hispanic White counterparts.16

The Primary Care Equity Dashboard (PCED) was developed to engage the VA health care workforce in the process of identifying and addressing inequities in local patient populations.17 Using electronic quality measure data, the PCED provides Veterans Integrated Service Network-level and facility-level performance on several metrics.18 The PCED had not been previously used at the CVVAMC, and few publications or quality improvement projects regarding its use have been reported by the VA Office of Health Equity. PCED helped identify disparities when comparing female to male patients in the prescribing of statin therapy for patients with CVD and statin therapy for patients with T2DM.

VA PHASER pharmacogenomic analyses provided an opportunity to expand this quality improvement project. Sanford Health and the VA collaborated on the PHASER program to offer free genetic testing for veterans. The program launched in 2019 and expanded to various VA sites, including CVVAMC in March 2023. This program has been extended to December 31, 2025.

The primary objective of this quality improvement project was to increase statin prescribing among female veterans with T2DM and/or CVD to reduce cardiovascular risk. Secondary outcomes included increased pharmacogenomic testing and the assessment of pharmacogenomic results related to statin therapy. This project was approved by the CVVAMC Pharmacy and Therapeutics Committee. The PCED was used to identify female veterans with T2DM and/or CVD without an active prescription for a statin between July and October 2023. A review of Computerized Patient Record System patient charts was completed to screen for prespecified inclusion and exclusion criteria. Veterans were included if they were assigned female at birth, were enrolled in care at CVVAMC, and had a diagnosis of T2DM or CVD (history of myocardial infarction, coronary bypass graft, percutaneous coronary intervention, or other revascularization in any setting).

Veterans were excluded if they were currently pregnant, trying to conceive, breastfeeding, had a T1DM diagnosis, had previously documented hypersensitivity to a statin, active liver failure or decompensated cirrhosis, previously documented statin-associated rhabdomyolysis or autoimmune myopathy, an active prescription for a proprotein convertase subtilisin/kexin type 9 inhibitor, or previously documented statin intolerance (defined as the inability to tolerate ≥ 3 statins, with ≥ 1 prescribed at low intensity or alternate-day dosing). The female veterans were compared to 2 comparators: the facility's male veterans and the VA national average, identified via the PCED.

Once a veteran was screened, they were telephoned between October 2023 and February 2024 and provided education on statin use and pharmacogenomic testing using a standardized note template. An order was placed for participants who provided verbal consent for pharmacogenomic testing. Those who agreed to statin initiation were referred to a clinical pharmacist practitioner (CPP) who contacted them at a later date to prescribe a statin following the recommendations of the 2019 ACC/AHA and 2023 ADA guidelines and pharmacogenomic testing, if applicable.4,5,7 Appropriate monitoring and follow-up occurred at the discretion of each CPP. Data collection included: age, race, diagnoses (T2DM, CVD, or both), baseline lipid panel (total cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein), hepatic function, name and dose of statin, reasons for declining statin therapy, and pharmacogenomic testing results related to SLCO1B1.

Results

At baseline in July 2023, 77.8% of female veterans with T2DM were prescribed a statin, which exceeded the national VA average (77.0%), but was below the rate for male veterans (78.7%) in the facility comparator group.17 Additionally, 82.2% of females with CVD were prescribed a statin, which was below the national VA average of 86.0% and the 84.9% of male veterans in the facility comparator group.17 The PCED identified 189 female veterans from July 2023 to October 2023 who may benefit from statin therapy. Thirty-three females met the exclusion criteria. Of the 156 included veterans, 129 (82.7%) were successfully contacted and 27 (17.3%) could not be reached by telephone after 3 attempts (Figure 1). The 129 female veterans contacted had a mean age of 59 years and the majority were Black (82.9%) (Table 1).

1125FED-DM-Statin-T1
1125FED-DM-Statin-F1
FIGURE 1. Flow Diagram of Patient Selection
Abbreviations: CVD, cardiovascular disease; PCSK9, proprotein convertase subtilisin/
kexin type 9; T2DM, type 2 diabetes mellitus; VAMC, Veterans Affairs medical center.

Primary Outcomes

Of the 129 contacted veterans, 31 (24.0%) had a non-VA statin prescription, 13 (10.1%) had an active VA statin prescription, and 85 (65.9%) did not have a statin prescription, despite being eligible. Statin adherence was confirmed with participants, and the medication list was updated accordingly.

Of the 85 veterans with no active statin therapy, 37 (43.5%) accepted a new statin prescription and 48 (56.5%) declined. There were various reasons provided for declining statin therapy: 17 participants (35.4%) declined due to concern for AEs (Table 2).

1125FED-DM-Statin-T2

From July 2023 to March 2024, the percentage of female veterans with active statin therapy with T2DM increased from 77.8% to 79.0%. For those with active statin therapy with CVD, usage increased from 82.2% to 90.2%, which exceeded the national VA average and facility male comparator group (Figures 2 and 3).17

1125FED-DM-Statin-F2
FIGURE 2. Statin Prescribing in Veterans With Type 2 Diabetes Mellitus
1125FED-DM-Statin-F3
FIGURE 3. Statin Prescribing in Veterans With Cardiovascular Disease

Secondary Outcomes

Seventy-one of 129 veterans (55.0%) gave verbal consent, and 47 (66.2%) completed the pharmacogenomic testing; 58 (45.0%) declined. Five veterans (10.6%) had a known SLCO1B1 allele variant present. One veteran required a change in statin therapy based on the results (eAppendix).

1125FED-DM-Statin-A1

Discussion

This project aimed to increase statin prescribing among female veterans with T2DM and/or CVD to reduce cardiovascular risk and increase pharmacogenomic testing using the PCED and care managed by CPPs. The results of this quality improvement project illustrated that both metrics have improved at CVVAMC as a result of the intervention. The results in both metrics now exceed the PCED national VA average, and the CVD metric also exceeds that of the facility male comparator group. While there was only a 1.2% increase from July 2023 to March 2024 for patients with T2DM, there was an 8.0% increase for patients with CVD. Despite standardized education on statin use, more veterans declined therapy than accepted it, mostly due to concern for AEs. Recording the reasons for declining statin therapy offered valuable insight that can be used in additional discussions with veterans and clinicians.

Pharmacogenomics gives clinicians the unique opportunity to take a proactive approach to better predict drug responses, potentially allowing for less trial and error with medications, fewer AEs, greater trust in the clinician, and improved medication adherence. The CPPs incorporated pharmacogenomic testing into their practice, which led to identifying 5 SLCO1B1 gene abnormalities. The PCED served as a powerful tool for advancing equity-focused quality improvement initiatives on a local level and was crucial in prioritizing the detection of veterans potentially receiving suboptimal care.

Limitations

The nature of “cold calls” made it challenging to establish contact for inclusion in this study. An alternative to increase engagement could have been scheduled phone or face-to-face visits. While the use of the PCED was crucial, data did not account for statins listed in the non-VA medication list. All 31 patients with statins prescribed outside the VA had a start date added to provide the most accurate representation of the data moving forward.

Another limitation in this project was its small sample size and population. CVVAMC serves about 6200 female veterans, with roughly 63% identifying as Black. The preponderance of Black individuals (83%) in this project is typical for the female patient population at CVVAMC but may not reflect the demographics of other populations. Other limitations to this project consisted of scheduling conflicts. Appointments for laboratory draws at community-based outpatient clinics were subject to availability, which resulted in some delay in completion of pharmacogenomic testing.

Conclusions

CPPs can help reduce inequity in health care delivery. Increased incorporation of the PCED into regular practice within the VA is recommended to continue addressing sex disparities in statin use, diabetes control, blood pressure management, cancer screenings, and vaccination needs. CVVAMC plans to expand its use through another quality improvement project focused on reducing sex disparities in blood pressure management. Improving educational resources made available to veterans on the importance of statin therapy and potential to mitigate AEs through use of the VA PHASER program also would be helpful. This project successfully improved CVVAMC metrics for female veterans appropriately prescribed statin therapy and increased access to pharmacogenomic testing. Most importantly, it helped close the sex-based gap in CVD risk reduction care.

References
  1. Heron M. Deaths: leading causes for 2018. Nat Vital Stat Rep. 2021;70:1-114.
  2. US Department of Veterans Affairs, US Department of Defense. VA/DoD Clinical practice guideline for the management of dyslipidemia for cardiovascular risk reduction. Published June 2020. Accessed August 25, 2025. https://www.healthquality.va.gov/guidelines/CD/lipids/VADODDyslipidemiaCPG5087212020.pdf
  3. Atherosclerotic Cardiovascular Disease (ASCVD). American Heart Association. Accessed August 26, 2025. https:// www.heart.org/en/professional/quality-improvement/ascvd
  4. American Diabetes Association Professional Practice Committee. 10. Cardiovascular disease and risk management: standards of medical care in diabetes-2022. Diabetes Care. 2022;45(Suppl 1):S144-S174. doi:10.2337/dc22-S010
  5. American Diabetes Association. Standards of Care in Diabetes— 2023 abridged for primary care providers. Clinical Diabetes. 2022;41(1):4-31. doi:10.2337/cd23-as01
  6. Virani SS, Woodard LD, Ramsey DJ, et al. Gender disparities in evidence-based statin therapy in patients with cardiovascular disease. Am J Cardiol. 2015;115:21-26. doi:10.1016/j.amjcard.2014.09.041
  7. Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/ AHA Guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/ American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
  8. Buchanan CH, Brown EA, Bishu KG, et al. The magnitude and potential causes of gender disparities in statin therapy in veterans with type 2 diabetes: a 10-year nationwide longitudinal cohort study. Womens Health Issues. 2022;32:274-283. doi:10.1016/j.whi.2021.10.003
  9. Ahmed F, Lin J, Ahmed T, et al. Health disparities: statin prescribing patterns among patients with diabetes in a family medicine clinic. Health Equity. 2022;6:291-297. doi:10.1089/heq.2021.0144
  10. Metser G, Bradley C, Moise N, Liyanage-Don N, Kronish I, Ye S. Gaps and disparities in primary prevention statin prescription during outpatient care. Am J Cardiol. 2021;161:36-41. doi:10.1016/j.amjcard.2021.08.070
  11. Nanna MG, Wang TY, Xiang Q, et al. Sex differences in the use of statins in community practice. Circ Cardiovasc Qual Outcomes. 2019;12(8):e005562. doi:10.1161/CIRCOUTCOMES.118.005562
  12. Kitzmiller JP, Mikulik EB, Dauki AM, Murkherjee C, Luzum JA. Pharmacogenomics of statins: understanding susceptibility to adverse effects. Pharmgenomics Pers Med. 2016;9:97-106. doi:10.2147/PGPM.S86013
  13. Türkmen D, Masoli JAH, Kuo CL, Bowden J, Melzer D, Pilling LC. Statin treatment effectiveness and the SLCO1B1*5 reduced function genotype: long-term outcomes in women and men. Br J Clin Pharmacol. 2022;88:3230-3240. doi:10.1111/bcp.15245
  14. Cooper-DeHoff RM, Niemi M, Ramsey LB, et al. The Clinical Pharmacogenetics Implementation Consortium guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and statin-associated musculoskeletal symptoms. Clin Pharmacol Ther. 2022;111:1007-1021. doi:10.1002/cpt.2557
  15. Ramsey LB, Gong L, Lee SB, et al. PharmVar GeneFocus: SLCO1B1. Clin Pharmacol Ther. 2023;113:782-793. doi:10.1002/cpt.2705
  16. National Healthcare Quality and Disparities Report: Chartbook on Healthcare for Veterans. Rockville (MD): Agency for Healthcare Research and Quality (US); November 2020.
  17. Procario G. Primary Care Equity Dashboard [database online]. Power Bi. 2023. Accessed August 26, 2025. https://app.powerbigov.us
  18. Hausmann LRM, Lamorte C, Estock JL. Understanding the context for incorporating equity into quality improvement throughout a national health care system. Health Equity. 2023;7(1):312-320. doi:10.1089/heq.2023.0009
References
  1. Heron M. Deaths: leading causes for 2018. Nat Vital Stat Rep. 2021;70:1-114.
  2. US Department of Veterans Affairs, US Department of Defense. VA/DoD Clinical practice guideline for the management of dyslipidemia for cardiovascular risk reduction. Published June 2020. Accessed August 25, 2025. https://www.healthquality.va.gov/guidelines/CD/lipids/VADODDyslipidemiaCPG5087212020.pdf
  3. Atherosclerotic Cardiovascular Disease (ASCVD). American Heart Association. Accessed August 26, 2025. https:// www.heart.org/en/professional/quality-improvement/ascvd
  4. American Diabetes Association Professional Practice Committee. 10. Cardiovascular disease and risk management: standards of medical care in diabetes-2022. Diabetes Care. 2022;45(Suppl 1):S144-S174. doi:10.2337/dc22-S010
  5. American Diabetes Association. Standards of Care in Diabetes— 2023 abridged for primary care providers. Clinical Diabetes. 2022;41(1):4-31. doi:10.2337/cd23-as01
  6. Virani SS, Woodard LD, Ramsey DJ, et al. Gender disparities in evidence-based statin therapy in patients with cardiovascular disease. Am J Cardiol. 2015;115:21-26. doi:10.1016/j.amjcard.2014.09.041
  7. Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/ AHA Guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/ American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
  8. Buchanan CH, Brown EA, Bishu KG, et al. The magnitude and potential causes of gender disparities in statin therapy in veterans with type 2 diabetes: a 10-year nationwide longitudinal cohort study. Womens Health Issues. 2022;32:274-283. doi:10.1016/j.whi.2021.10.003
  9. Ahmed F, Lin J, Ahmed T, et al. Health disparities: statin prescribing patterns among patients with diabetes in a family medicine clinic. Health Equity. 2022;6:291-297. doi:10.1089/heq.2021.0144
  10. Metser G, Bradley C, Moise N, Liyanage-Don N, Kronish I, Ye S. Gaps and disparities in primary prevention statin prescription during outpatient care. Am J Cardiol. 2021;161:36-41. doi:10.1016/j.amjcard.2021.08.070
  11. Nanna MG, Wang TY, Xiang Q, et al. Sex differences in the use of statins in community practice. Circ Cardiovasc Qual Outcomes. 2019;12(8):e005562. doi:10.1161/CIRCOUTCOMES.118.005562
  12. Kitzmiller JP, Mikulik EB, Dauki AM, Murkherjee C, Luzum JA. Pharmacogenomics of statins: understanding susceptibility to adverse effects. Pharmgenomics Pers Med. 2016;9:97-106. doi:10.2147/PGPM.S86013
  13. Türkmen D, Masoli JAH, Kuo CL, Bowden J, Melzer D, Pilling LC. Statin treatment effectiveness and the SLCO1B1*5 reduced function genotype: long-term outcomes in women and men. Br J Clin Pharmacol. 2022;88:3230-3240. doi:10.1111/bcp.15245
  14. Cooper-DeHoff RM, Niemi M, Ramsey LB, et al. The Clinical Pharmacogenetics Implementation Consortium guideline for SLCO1B1, ABCG2, and CYP2C9 genotypes and statin-associated musculoskeletal symptoms. Clin Pharmacol Ther. 2022;111:1007-1021. doi:10.1002/cpt.2557
  15. Ramsey LB, Gong L, Lee SB, et al. PharmVar GeneFocus: SLCO1B1. Clin Pharmacol Ther. 2023;113:782-793. doi:10.1002/cpt.2705
  16. National Healthcare Quality and Disparities Report: Chartbook on Healthcare for Veterans. Rockville (MD): Agency for Healthcare Research and Quality (US); November 2020.
  17. Procario G. Primary Care Equity Dashboard [database online]. Power Bi. 2023. Accessed August 26, 2025. https://app.powerbigov.us
  18. Hausmann LRM, Lamorte C, Estock JL. Understanding the context for incorporating equity into quality improvement throughout a national health care system. Health Equity. 2023;7(1):312-320. doi:10.1089/heq.2023.0009
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Reducing Sex Disparities in Statin Therapy Among Female Veterans With Type 2 Diabetes and/or Cardiovascular Disease

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