Health Policy

From the Institute for Healthcare Improvement, Boston, MA (Dr. Abid); Continuous Quality Improvement and Patient Safety Department, Armed Forces Hospitals Taif Region, Taif, Saudi Arabia (Dr. Abid); Primary and Secondary Healthcare Department, Government of Punjab, Lahore, Pakistan (Dr. Ahmed); Infection Prevention and Control Department, Armed Forces Hospitals Taif Region, Taif, Saudi Arabia (Dr. Din); Internal Medicine Department, Greater Baltimore Medical Center, Baltimore, MD (Dr. Abid); Department of Anesthesiology and Critical Care, DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, TX (Dr. Ratnani).

Diagnostic errors are defined by the National Academies of Sciences, Engineering, and Medicine (NASEM) as the failure to either establish an accurate and timely explanation of the patient’s health problem(s) or communicate that explanation to the patient.¹ According to a report by the Institute of Medicine, diagnostic errors account for a substantial number of adverse events in health care, affecting an estimated 12 million Americans each year.¹ Diagnostic errors are a common and serious issue in health care systems, with studies estimating that 5% to 15% of all diagnoses are incorrect.¹ Such errors can result in unnecessary treatments, delays in necessary treatments, and harm to patients. The high prevalence of diagnostic errors in primary care has been identified as a global issue.² While many factors contribute to diagnostic errors, the complex nature of health care systems, the limited processing capacity of human cognition, and deficiencies in interpersonal patient-clinician communication are primary contributors.^3,4

Discussions around the redesign of health care systems to reduce diagnostic errors have been at the forefront of medical research for years.^2,4 To decrease diagnostic errors in health care, a comprehensive strategy is necessary. This strategy should focus on utilizing both human experience (HX) in health care and artificial intelligence (AI) technologies to transform health care systems into proactive, patient-centered, and safer systems, specifically concerning diagnostic errors.¹

Human Experience and Diagnostic Errors

The role of HX in health care cannot be overstated. The HX in health care integrates the sum of all interactions, every encounter among patients, families and care partners, and the health care workforce.⁵ Patients and their families have a unique perspective on their health care experiences that can provide valuable insight into potential diagnostic errors.⁶ The new definition of diagnostic errors introduced in the 2015 NASEM report emphasized the significance of effective communication during the diagnostic procedure.¹ Engaging patients and their families in the diagnostic process can improve communication, improve diagnostic accuracy, and help to identify errors before they cause harm.⁷ However, many patients and families feel that they are not listened to or taken seriously by health care providers, and may not feel comfortable sharing information that they feel is important.⁸ To address this, health care systems can implement programs that encourage patients and families to be more engaged in the diagnostic process, such as shared decision-making, patient portals, and patient and family advisory councils.⁹ Health care systems must prioritize patient-centered care, teamwork, and communication. Patients and their families must be actively engaged in their care, and health care providers must be willing to work collaboratively and listen to patients’ concerns.^6,10

Health care providers also bring their own valuable experiences and expertise to the diagnostic process, as they are often the ones on the front lines of patient care. However, health care providers may not always feel comfortable reporting errors or near misses, and may not have the time or resources to participate in quality improvement initiatives. To address this, health care systems can implement programs that encourage providers to report errors and near misses, such as anonymous reporting systems, just-culture initiatives, and peer review.¹¹ Creating a culture of teamwork and collaboration among health care providers can improve the accuracy of diagnoses and reduce the risk of errors.¹²

A key factor in utilizing HX to reduce diagnostic errors is effective communication. Communication breakdowns among health care providers, patients, and their families are a common contributing factor resulting in diagnostic errors.² Strategies to improve communication include using clear and concise language, involving patients and their families in the decision-making process, and utilizing electronic health records (EHRs) to ensure that all health care providers have access to relevant, accurate, and up-to-date patient information.^4,13,14

Another important aspect of utilizing HX in health care to reduce diagnostic errors is the need to recognize and address cognitive biases that may influence diagnostic decisions.³ Cognitive biases are common in health care and can lead to errors in diagnosis. For example, confirmation bias, which is the tendency to look for information that confirms preexisting beliefs, can lead providers to overlook important diagnostic information.¹⁵ Biases such as anchoring bias, premature closure, and confirmation bias can lead to incorrect diagnoses and can be difficult to recognize and overcome. Addressing cognitive biases requires a commitment to self-reflection and self-awareness among health care providers as well as structured training of health care providers to improve their diagnostic reasoning skills and reduce the risk of cognitive errors.¹⁵ By implementing these strategies around HX in health care, health care systems can become more patient-centered and reduce the likelihood of diagnostic errors (Figure).

 

 

Artificial Intelligence and Diagnostic Errors

Artificial intelligence has the potential to significantly reduce diagnostic errors in health care (Figure), and its role in health care is rapidly expanding. AI technologies such as machine learning (ML) and natural language processing (NLP) have the potential to significantly reduce diagnostic errors by augmenting human cognition and improving access to relevant patient data.^1,16 Machine learning algorithms can analyze large amounts of patient data sets to identify patterns and risk factors and predict patient outcomes, which can aid health care providers in making accurate diagnoses.¹⁷ Artificial intelligence can also help to address some of the communication breakdowns that contribute to diagnostic errors.¹⁸ Natural language processing can improve the accuracy of EHR documentation and reduce the associated clinician burden, making it easier for providers to access relevant patient information and communicate more effectively with each other.¹⁸

In health care, AI can be used to analyze medical images, laboratory results, genomic data, and EHRs to identify potential diagnoses and flag patients who may be at risk for diagnostic errors. One of the primary benefits of AI in health care is its ability to process large amounts of data quickly and accurately.¹⁹ This can be particularly valuable in diagnosing rare or complex conditions. Machine learning algorithms can analyze patient data to identify subtle patterns that may not be apparent to human providers.¹⁶ This can lead to earlier and more accurate diagnoses, which can reduce diagnostic errors and improve patient outcomes.¹⁷ One example of the application of AI in health care is the use of computer-aided detection (CAD) software to analyze medical images. This software can help radiologists detect abnormalities in medical images that may be missed by the human eye, such as early-stage breast cancer.²⁰ Another example is the use of NLP and ML to analyze unstructured data in EHRs, such as physician notes, to identify potential diagnoses and flag patients who may be at risk for diagnostic errors.²¹ A recent study showed that using NLP on EHRs for screening and detecting individuals at risk for psychosis can considerably enhance the prognostic accuracy of psychosis risk calculators.²² This can help identify patients who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes. On the same note, ML-based severe sepsis prediction algorithms have been shown to reduce the average length of stay and in-hospital mortality rate.²³

However, there are also concerns about the use of AI in health care, including the potential for bias and the risk of overreliance on AI. Bias can occur when AI algorithms are trained on data that is not representative of the population being analyzed, leading to inaccurate or unfair results, hence, perpetuating and exacerbating existing biases in health care.²⁴ Over-reliance on AI can occur when health care providers rely too heavily on AI algorithms and fail to consider other important information, such as the lived experience of patients, families, and health care providers. Addressing these concerns will require ongoing efforts to ensure that AI technologies are developed and implemented in an ethical and responsible manner.²⁵

Conclusion

Reducing diagnostic errors is a critical goal for health care systems, and requires a comprehensive approach that utilizes both HX and AI technologies. Engaging patients and their families in the diagnostic process, promoting teamwork and collaboration among health care providers, addressing cognitive biases, and harnessing the power of AI can all contribute to more accurate diagnoses and better patient outcomes. By integrating the lived experience of patients, families, and health care providers with AI technologies, health care systems can be redesigned to become more proactive, safer, and patient-centered in identifying potential health problems and reducing the risk of diagnostic errors, ensuring that patients receive the care they need and deserve.

Corresponding author: Iqbal Ratnani, Department of Anesthesiology and Critical Care, DeBakey Heart and Vascular Center, Houston Methodist Hospital, 6565 Fannin St, Houston, TX 77030; IRatnani@houstonmethodist.org

Disclosures: None reported.

From the Institute for Healthcare Improvement, Boston, MA (Dr. Abid); Continuous Quality Improvement and Patient Safety Department, Armed Forces Hospitals Taif Region, Taif, Saudi Arabia (Dr. Abid); Primary and Secondary Healthcare Department, Government of Punjab, Lahore, Pakistan (Dr. Ahmed); Infection Prevention and Control Department, Armed Forces Hospitals Taif Region, Taif, Saudi Arabia (Dr. Din); Internal Medicine Department, Greater Baltimore Medical Center, Baltimore, MD (Dr. Abid); Department of Anesthesiology and Critical Care, DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, TX (Dr. Ratnani).

Diagnostic errors are defined by the National Academies of Sciences, Engineering, and Medicine (NASEM) as the failure to either establish an accurate and timely explanation of the patient’s health problem(s) or communicate that explanation to the patient.¹ According to a report by the Institute of Medicine, diagnostic errors account for a substantial number of adverse events in health care, affecting an estimated 12 million Americans each year.¹ Diagnostic errors are a common and serious issue in health care systems, with studies estimating that 5% to 15% of all diagnoses are incorrect.¹ Such errors can result in unnecessary treatments, delays in necessary treatments, and harm to patients. The high prevalence of diagnostic errors in primary care has been identified as a global issue.² While many factors contribute to diagnostic errors, the complex nature of health care systems, the limited processing capacity of human cognition, and deficiencies in interpersonal patient-clinician communication are primary contributors.^3,4

Discussions around the redesign of health care systems to reduce diagnostic errors have been at the forefront of medical research for years.^2,4 To decrease diagnostic errors in health care, a comprehensive strategy is necessary. This strategy should focus on utilizing both human experience (HX) in health care and artificial intelligence (AI) technologies to transform health care systems into proactive, patient-centered, and safer systems, specifically concerning diagnostic errors.¹

Human Experience and Diagnostic Errors

The role of HX in health care cannot be overstated. The HX in health care integrates the sum of all interactions, every encounter among patients, families and care partners, and the health care workforce.⁵ Patients and their families have a unique perspective on their health care experiences that can provide valuable insight into potential diagnostic errors.⁶ The new definition of diagnostic errors introduced in the 2015 NASEM report emphasized the significance of effective communication during the diagnostic procedure.¹ Engaging patients and their families in the diagnostic process can improve communication, improve diagnostic accuracy, and help to identify errors before they cause harm.⁷ However, many patients and families feel that they are not listened to or taken seriously by health care providers, and may not feel comfortable sharing information that they feel is important.⁸ To address this, health care systems can implement programs that encourage patients and families to be more engaged in the diagnostic process, such as shared decision-making, patient portals, and patient and family advisory councils.⁹ Health care systems must prioritize patient-centered care, teamwork, and communication. Patients and their families must be actively engaged in their care, and health care providers must be willing to work collaboratively and listen to patients’ concerns.^6,10

Health care providers also bring their own valuable experiences and expertise to the diagnostic process, as they are often the ones on the front lines of patient care. However, health care providers may not always feel comfortable reporting errors or near misses, and may not have the time or resources to participate in quality improvement initiatives. To address this, health care systems can implement programs that encourage providers to report errors and near misses, such as anonymous reporting systems, just-culture initiatives, and peer review.¹¹ Creating a culture of teamwork and collaboration among health care providers can improve the accuracy of diagnoses and reduce the risk of errors.¹²

A key factor in utilizing HX to reduce diagnostic errors is effective communication. Communication breakdowns among health care providers, patients, and their families are a common contributing factor resulting in diagnostic errors.² Strategies to improve communication include using clear and concise language, involving patients and their families in the decision-making process, and utilizing electronic health records (EHRs) to ensure that all health care providers have access to relevant, accurate, and up-to-date patient information.^4,13,14

Another important aspect of utilizing HX in health care to reduce diagnostic errors is the need to recognize and address cognitive biases that may influence diagnostic decisions.³ Cognitive biases are common in health care and can lead to errors in diagnosis. For example, confirmation bias, which is the tendency to look for information that confirms preexisting beliefs, can lead providers to overlook important diagnostic information.¹⁵ Biases such as anchoring bias, premature closure, and confirmation bias can lead to incorrect diagnoses and can be difficult to recognize and overcome. Addressing cognitive biases requires a commitment to self-reflection and self-awareness among health care providers as well as structured training of health care providers to improve their diagnostic reasoning skills and reduce the risk of cognitive errors.¹⁵ By implementing these strategies around HX in health care, health care systems can become more patient-centered and reduce the likelihood of diagnostic errors (Figure).

 

 

Artificial Intelligence and Diagnostic Errors

Artificial intelligence has the potential to significantly reduce diagnostic errors in health care (Figure), and its role in health care is rapidly expanding. AI technologies such as machine learning (ML) and natural language processing (NLP) have the potential to significantly reduce diagnostic errors by augmenting human cognition and improving access to relevant patient data.^1,16 Machine learning algorithms can analyze large amounts of patient data sets to identify patterns and risk factors and predict patient outcomes, which can aid health care providers in making accurate diagnoses.¹⁷ Artificial intelligence can also help to address some of the communication breakdowns that contribute to diagnostic errors.¹⁸ Natural language processing can improve the accuracy of EHR documentation and reduce the associated clinician burden, making it easier for providers to access relevant patient information and communicate more effectively with each other.¹⁸

In health care, AI can be used to analyze medical images, laboratory results, genomic data, and EHRs to identify potential diagnoses and flag patients who may be at risk for diagnostic errors. One of the primary benefits of AI in health care is its ability to process large amounts of data quickly and accurately.¹⁹ This can be particularly valuable in diagnosing rare or complex conditions. Machine learning algorithms can analyze patient data to identify subtle patterns that may not be apparent to human providers.¹⁶ This can lead to earlier and more accurate diagnoses, which can reduce diagnostic errors and improve patient outcomes.¹⁷ One example of the application of AI in health care is the use of computer-aided detection (CAD) software to analyze medical images. This software can help radiologists detect abnormalities in medical images that may be missed by the human eye, such as early-stage breast cancer.²⁰ Another example is the use of NLP and ML to analyze unstructured data in EHRs, such as physician notes, to identify potential diagnoses and flag patients who may be at risk for diagnostic errors.²¹ A recent study showed that using NLP on EHRs for screening and detecting individuals at risk for psychosis can considerably enhance the prognostic accuracy of psychosis risk calculators.²² This can help identify patients who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes. On the same note, ML-based severe sepsis prediction algorithms have been shown to reduce the average length of stay and in-hospital mortality rate.²³

However, there are also concerns about the use of AI in health care, including the potential for bias and the risk of overreliance on AI. Bias can occur when AI algorithms are trained on data that is not representative of the population being analyzed, leading to inaccurate or unfair results, hence, perpetuating and exacerbating existing biases in health care.²⁴ Over-reliance on AI can occur when health care providers rely too heavily on AI algorithms and fail to consider other important information, such as the lived experience of patients, families, and health care providers. Addressing these concerns will require ongoing efforts to ensure that AI technologies are developed and implemented in an ethical and responsible manner.²⁵

Conclusion

Reducing diagnostic errors is a critical goal for health care systems, and requires a comprehensive approach that utilizes both HX and AI technologies. Engaging patients and their families in the diagnostic process, promoting teamwork and collaboration among health care providers, addressing cognitive biases, and harnessing the power of AI can all contribute to more accurate diagnoses and better patient outcomes. By integrating the lived experience of patients, families, and health care providers with AI technologies, health care systems can be redesigned to become more proactive, safer, and patient-centered in identifying potential health problems and reducing the risk of diagnostic errors, ensuring that patients receive the care they need and deserve.

Corresponding author: Iqbal Ratnani, Department of Anesthesiology and Critical Care, DeBakey Heart and Vascular Center, Houston Methodist Hospital, 6565 Fannin St, Houston, TX 77030; IRatnani@houstonmethodist.org

Disclosures: None reported.

From the Institute for Healthcare Improvement, Boston, MA (Dr. Abid); Continuous Quality Improvement and Patient Safety Department, Armed Forces Hospitals Taif Region, Taif, Saudi Arabia (Dr. Abid); Primary and Secondary Healthcare Department, Government of Punjab, Lahore, Pakistan (Dr. Ahmed); Infection Prevention and Control Department, Armed Forces Hospitals Taif Region, Taif, Saudi Arabia (Dr. Din); Internal Medicine Department, Greater Baltimore Medical Center, Baltimore, MD (Dr. Abid); Department of Anesthesiology and Critical Care, DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, TX (Dr. Ratnani).

Diagnostic errors are defined by the National Academies of Sciences, Engineering, and Medicine (NASEM) as the failure to either establish an accurate and timely explanation of the patient’s health problem(s) or communicate that explanation to the patient.¹ According to a report by the Institute of Medicine, diagnostic errors account for a substantial number of adverse events in health care, affecting an estimated 12 million Americans each year.¹ Diagnostic errors are a common and serious issue in health care systems, with studies estimating that 5% to 15% of all diagnoses are incorrect.¹ Such errors can result in unnecessary treatments, delays in necessary treatments, and harm to patients. The high prevalence of diagnostic errors in primary care has been identified as a global issue.² While many factors contribute to diagnostic errors, the complex nature of health care systems, the limited processing capacity of human cognition, and deficiencies in interpersonal patient-clinician communication are primary contributors.^3,4

Discussions around the redesign of health care systems to reduce diagnostic errors have been at the forefront of medical research for years.^2,4 To decrease diagnostic errors in health care, a comprehensive strategy is necessary. This strategy should focus on utilizing both human experience (HX) in health care and artificial intelligence (AI) technologies to transform health care systems into proactive, patient-centered, and safer systems, specifically concerning diagnostic errors.¹

Human Experience and Diagnostic Errors

The role of HX in health care cannot be overstated. The HX in health care integrates the sum of all interactions, every encounter among patients, families and care partners, and the health care workforce.⁵ Patients and their families have a unique perspective on their health care experiences that can provide valuable insight into potential diagnostic errors.⁶ The new definition of diagnostic errors introduced in the 2015 NASEM report emphasized the significance of effective communication during the diagnostic procedure.¹ Engaging patients and their families in the diagnostic process can improve communication, improve diagnostic accuracy, and help to identify errors before they cause harm.⁷ However, many patients and families feel that they are not listened to or taken seriously by health care providers, and may not feel comfortable sharing information that they feel is important.⁸ To address this, health care systems can implement programs that encourage patients and families to be more engaged in the diagnostic process, such as shared decision-making, patient portals, and patient and family advisory councils.⁹ Health care systems must prioritize patient-centered care, teamwork, and communication. Patients and their families must be actively engaged in their care, and health care providers must be willing to work collaboratively and listen to patients’ concerns.^6,10

Health care providers also bring their own valuable experiences and expertise to the diagnostic process, as they are often the ones on the front lines of patient care. However, health care providers may not always feel comfortable reporting errors or near misses, and may not have the time or resources to participate in quality improvement initiatives. To address this, health care systems can implement programs that encourage providers to report errors and near misses, such as anonymous reporting systems, just-culture initiatives, and peer review.¹¹ Creating a culture of teamwork and collaboration among health care providers can improve the accuracy of diagnoses and reduce the risk of errors.¹²

A key factor in utilizing HX to reduce diagnostic errors is effective communication. Communication breakdowns among health care providers, patients, and their families are a common contributing factor resulting in diagnostic errors.² Strategies to improve communication include using clear and concise language, involving patients and their families in the decision-making process, and utilizing electronic health records (EHRs) to ensure that all health care providers have access to relevant, accurate, and up-to-date patient information.^4,13,14

Another important aspect of utilizing HX in health care to reduce diagnostic errors is the need to recognize and address cognitive biases that may influence diagnostic decisions.³ Cognitive biases are common in health care and can lead to errors in diagnosis. For example, confirmation bias, which is the tendency to look for information that confirms preexisting beliefs, can lead providers to overlook important diagnostic information.¹⁵ Biases such as anchoring bias, premature closure, and confirmation bias can lead to incorrect diagnoses and can be difficult to recognize and overcome. Addressing cognitive biases requires a commitment to self-reflection and self-awareness among health care providers as well as structured training of health care providers to improve their diagnostic reasoning skills and reduce the risk of cognitive errors.¹⁵ By implementing these strategies around HX in health care, health care systems can become more patient-centered and reduce the likelihood of diagnostic errors (Figure).

 

 

Artificial Intelligence and Diagnostic Errors

Artificial intelligence has the potential to significantly reduce diagnostic errors in health care (Figure), and its role in health care is rapidly expanding. AI technologies such as machine learning (ML) and natural language processing (NLP) have the potential to significantly reduce diagnostic errors by augmenting human cognition and improving access to relevant patient data.^1,16 Machine learning algorithms can analyze large amounts of patient data sets to identify patterns and risk factors and predict patient outcomes, which can aid health care providers in making accurate diagnoses.¹⁷ Artificial intelligence can also help to address some of the communication breakdowns that contribute to diagnostic errors.¹⁸ Natural language processing can improve the accuracy of EHR documentation and reduce the associated clinician burden, making it easier for providers to access relevant patient information and communicate more effectively with each other.¹⁸

In health care, AI can be used to analyze medical images, laboratory results, genomic data, and EHRs to identify potential diagnoses and flag patients who may be at risk for diagnostic errors. One of the primary benefits of AI in health care is its ability to process large amounts of data quickly and accurately.¹⁹ This can be particularly valuable in diagnosing rare or complex conditions. Machine learning algorithms can analyze patient data to identify subtle patterns that may not be apparent to human providers.¹⁶ This can lead to earlier and more accurate diagnoses, which can reduce diagnostic errors and improve patient outcomes.¹⁷ One example of the application of AI in health care is the use of computer-aided detection (CAD) software to analyze medical images. This software can help radiologists detect abnormalities in medical images that may be missed by the human eye, such as early-stage breast cancer.²⁰ Another example is the use of NLP and ML to analyze unstructured data in EHRs, such as physician notes, to identify potential diagnoses and flag patients who may be at risk for diagnostic errors.²¹ A recent study showed that using NLP on EHRs for screening and detecting individuals at risk for psychosis can considerably enhance the prognostic accuracy of psychosis risk calculators.²² This can help identify patients who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes. On the same note, ML-based severe sepsis prediction algorithms have been shown to reduce the average length of stay and in-hospital mortality rate.²³

However, there are also concerns about the use of AI in health care, including the potential for bias and the risk of overreliance on AI. Bias can occur when AI algorithms are trained on data that is not representative of the population being analyzed, leading to inaccurate or unfair results, hence, perpetuating and exacerbating existing biases in health care.²⁴ Over-reliance on AI can occur when health care providers rely too heavily on AI algorithms and fail to consider other important information, such as the lived experience of patients, families, and health care providers. Addressing these concerns will require ongoing efforts to ensure that AI technologies are developed and implemented in an ethical and responsible manner.²⁵

Conclusion

Reducing diagnostic errors is a critical goal for health care systems, and requires a comprehensive approach that utilizes both HX and AI technologies. Engaging patients and their families in the diagnostic process, promoting teamwork and collaboration among health care providers, addressing cognitive biases, and harnessing the power of AI can all contribute to more accurate diagnoses and better patient outcomes. By integrating the lived experience of patients, families, and health care providers with AI technologies, health care systems can be redesigned to become more proactive, safer, and patient-centered in identifying potential health problems and reducing the risk of diagnostic errors, ensuring that patients receive the care they need and deserve.

Corresponding author: Iqbal Ratnani, Department of Anesthesiology and Critical Care, DeBakey Heart and Vascular Center, Houston Methodist Hospital, 6565 Fannin St, Houston, TX 77030; IRatnani@houstonmethodist.org

Disclosures: None reported.

As the movement to improve quality in health care has evolved over the past several decades, organizations whose missions focus on supporting and promoting quality in health care have defined essential concepts, standards, and measures that comprise quality and that can be used to guide quality improvement (QI) work. The World Health Organization (WHO) defines quality in clinical care as safe, effective, and people-centered service.¹ These 3 pillars of quality form the foundation of a quality system aiming to deliver health care in a timely, equitable, efficient, and integrated manner. The WHO estimates that 5.7 to 8.4 million deaths occur yearly in low- and middle-income countries due to poor quality care. Regarding safety, patient harm from unsafe care is estimated to be among the top 10 causes of death and disability worldwide.² A health care QI plan involves identifying areas for improvement, setting measurable goals, implementing evidence-based strategies and interventions, monitoring progress toward achieving those goals, and continuously evaluating and adjusting the plan as needed to ensure sustained improvement over time. Such a plan can be implemented at various levels of health care organizations, from individual clinical units to entire hospitals or even regional health care systems.

The Institute of Medicine (IOM) identifies 5 domains of quality in health care: effectiveness, efficiency, equity, patient-centeredness, and safety.³ Effectiveness relies on providing care processes supported by scientific evidence and achieving desired outcomes in the IOM recommendations. The primary efficiency aim maximizes the quality of health care delivered or the benefits achieved for a given resource unit. Equity relates to providing health care of equal quality to all individuals, regardless of personal characteristics. Moreover, patient-centeredness relates to meeting patients’ needs and preferences and providing education and support. Safety relates to avoiding actual or potential harm. Timeliness relates to obtaining needed care while minimizing delays. Finally, the IOM defines health care quality as the systematic evaluation and provision of evidence-based and safe care characterized by a culture of continuous improvement, resulting in optimal health outcomes. Taking all these concepts into consideration, 4 key attributes have been identified as essential to the global definition of health care quality: effectiveness, safety, culture of continuous improvement, and desired outcomes. This conceptualization of health care quality encompasses the fundamental components and has the potential to enhance the delivery of care. This definition’s theoretical and practical implications provide a comprehensive and consistent understanding of the elements required to improve health care and maintain public trust.

Health care quality is a dynamic, ever-evolving construct that requires continuous assessment and evaluation to ensure the delivery of care meets the changing needs of society. The National Quality Forum’s National Voluntary Consensus Standards for health care provide measures, guidance, and recommendations on achieving effective outcomes through evidence-based practices.⁴ These standards establish criteria by which health care systems and providers can assess and improve their quality performance.

In the United States, in order to implement and disseminate best practices, the Centers for Medicare & Medicaid Services (CMS) developed Quality Payment Programs that offer incentives to health care providers to improve the quality of care delivery. This CMS program evaluates providers based on their performance in the Merit-Based Incentive Payment System performance categories.⁵ These include measures related to patient experience, cost, clinical quality, improvement activities, and the use of certified electronic health record technology. The scores that providers receive are used to determine their performance-based reimbursements under Medicare’s fee-for-service program.

The concept of health care quality is also applicable in other countries. In the United Kingdom, QI initiatives are led by the Department of Health and Social Care. The National Institute for Health and Care Excellence (NICE) produces guidelines on best practices to ensure that care delivery meets established safety and quality standards, reaching cost-effectiveness excellence.⁶ In Australia, the Australian Commission on Quality and Safety in Health Care is responsible for setting benchmarks for performance in health care systems through a clear, structured agenda.⁷ Ultimately, health care quality is a complex and multifaceted issue that requires a comprehensive approach to ensure the best outcomes for patients. With the implementation of measures such as the CMS Quality Payment Programs and NICE guidelines, health care organizations can take steps to ensure their systems of care delivery reflect evidence-based practices and demonstrate a commitment to providing high-quality care.

Implementing a health care QI plan that encompasses the 4 key attributes of health care quality—effectiveness, safety, culture of continuous improvement, and desired outcomes—requires collaboration among different departments and stakeholders and a data-driven approach to decision-making. Effective communication with patients and their families is critical to ensuring that their needs are being met and that they are active partners in their health care journey. While a health care QI plan is essential for delivering high-quality, safe patient care, it also helps health care organizations comply with regulatory requirements, meet accreditation standards, and stay competitive in the ever-evolving health care landscape.

Corresponding author: Ebrahim Barkoudah, MD, MPH; Ebrahim.Barkoudah@baystatehealth.org

As the movement to improve quality in health care has evolved over the past several decades, organizations whose missions focus on supporting and promoting quality in health care have defined essential concepts, standards, and measures that comprise quality and that can be used to guide quality improvement (QI) work. The World Health Organization (WHO) defines quality in clinical care as safe, effective, and people-centered service.¹ These 3 pillars of quality form the foundation of a quality system aiming to deliver health care in a timely, equitable, efficient, and integrated manner. The WHO estimates that 5.7 to 8.4 million deaths occur yearly in low- and middle-income countries due to poor quality care. Regarding safety, patient harm from unsafe care is estimated to be among the top 10 causes of death and disability worldwide.² A health care QI plan involves identifying areas for improvement, setting measurable goals, implementing evidence-based strategies and interventions, monitoring progress toward achieving those goals, and continuously evaluating and adjusting the plan as needed to ensure sustained improvement over time. Such a plan can be implemented at various levels of health care organizations, from individual clinical units to entire hospitals or even regional health care systems.

The Institute of Medicine (IOM) identifies 5 domains of quality in health care: effectiveness, efficiency, equity, patient-centeredness, and safety.³ Effectiveness relies on providing care processes supported by scientific evidence and achieving desired outcomes in the IOM recommendations. The primary efficiency aim maximizes the quality of health care delivered or the benefits achieved for a given resource unit. Equity relates to providing health care of equal quality to all individuals, regardless of personal characteristics. Moreover, patient-centeredness relates to meeting patients’ needs and preferences and providing education and support. Safety relates to avoiding actual or potential harm. Timeliness relates to obtaining needed care while minimizing delays. Finally, the IOM defines health care quality as the systematic evaluation and provision of evidence-based and safe care characterized by a culture of continuous improvement, resulting in optimal health outcomes. Taking all these concepts into consideration, 4 key attributes have been identified as essential to the global definition of health care quality: effectiveness, safety, culture of continuous improvement, and desired outcomes. This conceptualization of health care quality encompasses the fundamental components and has the potential to enhance the delivery of care. This definition’s theoretical and practical implications provide a comprehensive and consistent understanding of the elements required to improve health care and maintain public trust.

Health care quality is a dynamic, ever-evolving construct that requires continuous assessment and evaluation to ensure the delivery of care meets the changing needs of society. The National Quality Forum’s National Voluntary Consensus Standards for health care provide measures, guidance, and recommendations on achieving effective outcomes through evidence-based practices.⁴ These standards establish criteria by which health care systems and providers can assess and improve their quality performance.

In the United States, in order to implement and disseminate best practices, the Centers for Medicare & Medicaid Services (CMS) developed Quality Payment Programs that offer incentives to health care providers to improve the quality of care delivery. This CMS program evaluates providers based on their performance in the Merit-Based Incentive Payment System performance categories.⁵ These include measures related to patient experience, cost, clinical quality, improvement activities, and the use of certified electronic health record technology. The scores that providers receive are used to determine their performance-based reimbursements under Medicare’s fee-for-service program.

The concept of health care quality is also applicable in other countries. In the United Kingdom, QI initiatives are led by the Department of Health and Social Care. The National Institute for Health and Care Excellence (NICE) produces guidelines on best practices to ensure that care delivery meets established safety and quality standards, reaching cost-effectiveness excellence.⁶ In Australia, the Australian Commission on Quality and Safety in Health Care is responsible for setting benchmarks for performance in health care systems through a clear, structured agenda.⁷ Ultimately, health care quality is a complex and multifaceted issue that requires a comprehensive approach to ensure the best outcomes for patients. With the implementation of measures such as the CMS Quality Payment Programs and NICE guidelines, health care organizations can take steps to ensure their systems of care delivery reflect evidence-based practices and demonstrate a commitment to providing high-quality care.

Implementing a health care QI plan that encompasses the 4 key attributes of health care quality—effectiveness, safety, culture of continuous improvement, and desired outcomes—requires collaboration among different departments and stakeholders and a data-driven approach to decision-making. Effective communication with patients and their families is critical to ensuring that their needs are being met and that they are active partners in their health care journey. While a health care QI plan is essential for delivering high-quality, safe patient care, it also helps health care organizations comply with regulatory requirements, meet accreditation standards, and stay competitive in the ever-evolving health care landscape.

Corresponding author: Ebrahim Barkoudah, MD, MPH; Ebrahim.Barkoudah@baystatehealth.org

As the movement to improve quality in health care has evolved over the past several decades, organizations whose missions focus on supporting and promoting quality in health care have defined essential concepts, standards, and measures that comprise quality and that can be used to guide quality improvement (QI) work. The World Health Organization (WHO) defines quality in clinical care as safe, effective, and people-centered service.¹ These 3 pillars of quality form the foundation of a quality system aiming to deliver health care in a timely, equitable, efficient, and integrated manner. The WHO estimates that 5.7 to 8.4 million deaths occur yearly in low- and middle-income countries due to poor quality care. Regarding safety, patient harm from unsafe care is estimated to be among the top 10 causes of death and disability worldwide.² A health care QI plan involves identifying areas for improvement, setting measurable goals, implementing evidence-based strategies and interventions, monitoring progress toward achieving those goals, and continuously evaluating and adjusting the plan as needed to ensure sustained improvement over time. Such a plan can be implemented at various levels of health care organizations, from individual clinical units to entire hospitals or even regional health care systems.

The Institute of Medicine (IOM) identifies 5 domains of quality in health care: effectiveness, efficiency, equity, patient-centeredness, and safety.³ Effectiveness relies on providing care processes supported by scientific evidence and achieving desired outcomes in the IOM recommendations. The primary efficiency aim maximizes the quality of health care delivered or the benefits achieved for a given resource unit. Equity relates to providing health care of equal quality to all individuals, regardless of personal characteristics. Moreover, patient-centeredness relates to meeting patients’ needs and preferences and providing education and support. Safety relates to avoiding actual or potential harm. Timeliness relates to obtaining needed care while minimizing delays. Finally, the IOM defines health care quality as the systematic evaluation and provision of evidence-based and safe care characterized by a culture of continuous improvement, resulting in optimal health outcomes. Taking all these concepts into consideration, 4 key attributes have been identified as essential to the global definition of health care quality: effectiveness, safety, culture of continuous improvement, and desired outcomes. This conceptualization of health care quality encompasses the fundamental components and has the potential to enhance the delivery of care. This definition’s theoretical and practical implications provide a comprehensive and consistent understanding of the elements required to improve health care and maintain public trust.

Health care quality is a dynamic, ever-evolving construct that requires continuous assessment and evaluation to ensure the delivery of care meets the changing needs of society. The National Quality Forum’s National Voluntary Consensus Standards for health care provide measures, guidance, and recommendations on achieving effective outcomes through evidence-based practices.⁴ These standards establish criteria by which health care systems and providers can assess and improve their quality performance.

In the United States, in order to implement and disseminate best practices, the Centers for Medicare & Medicaid Services (CMS) developed Quality Payment Programs that offer incentives to health care providers to improve the quality of care delivery. This CMS program evaluates providers based on their performance in the Merit-Based Incentive Payment System performance categories.⁵ These include measures related to patient experience, cost, clinical quality, improvement activities, and the use of certified electronic health record technology. The scores that providers receive are used to determine their performance-based reimbursements under Medicare’s fee-for-service program.

The concept of health care quality is also applicable in other countries. In the United Kingdom, QI initiatives are led by the Department of Health and Social Care. The National Institute for Health and Care Excellence (NICE) produces guidelines on best practices to ensure that care delivery meets established safety and quality standards, reaching cost-effectiveness excellence.⁶ In Australia, the Australian Commission on Quality and Safety in Health Care is responsible for setting benchmarks for performance in health care systems through a clear, structured agenda.⁷ Ultimately, health care quality is a complex and multifaceted issue that requires a comprehensive approach to ensure the best outcomes for patients. With the implementation of measures such as the CMS Quality Payment Programs and NICE guidelines, health care organizations can take steps to ensure their systems of care delivery reflect evidence-based practices and demonstrate a commitment to providing high-quality care.

Implementing a health care QI plan that encompasses the 4 key attributes of health care quality—effectiveness, safety, culture of continuous improvement, and desired outcomes—requires collaboration among different departments and stakeholders and a data-driven approach to decision-making. Effective communication with patients and their families is critical to ensuring that their needs are being met and that they are active partners in their health care journey. While a health care QI plan is essential for delivering high-quality, safe patient care, it also helps health care organizations comply with regulatory requirements, meet accreditation standards, and stay competitive in the ever-evolving health care landscape.

Corresponding author: Ebrahim Barkoudah, MD, MPH; Ebrahim.Barkoudah@baystatehealth.org

The Food and Drug Administration has announced new action to address ongoing concerns about misuse, abuse, addiction, and overdose of prescription stimulants used to treat attention-deficit/hyperactivity disorder (ADHD).

“The current prescribing information for some prescription stimulants does not provide up-to-date warnings about the harms of misuse and abuse, and particularly that most individuals who misuse prescription stimulants get their drugs from other family members or peers,” the FDA said in a drug safety communication.

Going forward, updated drug labels will clearly state that patients should never share their prescription stimulants with anyone, and the boxed warning will describe the risks of misuse, abuse, addiction, and overdose consistently for all medicines in the class, the FDA said.

The boxed warning will also advise heath care professionals to monitor patients closely for signs and symptoms of misuse, abuse, and addiction.

Patient medication guides will be updated to educate patients and caregivers about these risks.

The FDA encourages prescribers to assess patient risk of misuse, abuse, and addiction before prescribing a stimulant and to counsel patients not to share the medication.
 

Friends and family

A recent literature review by the FDA found that friends and family members are the most common source of prescription stimulant misuse and abuse (nonmedical use). Estimates of such use range from 56% to 80%.

Misuse/abuse of a patient’s own prescription make up 10%-20% of people who report nonmedical stimulant use.

Less commonly reported sources include drug dealers or strangers (4%-7% of people who report nonmedical use) and the Internet (1%-2%).

The groups at highest risk for misuse/abuse of prescription stimulants are young adults aged 18-25 years, college students, and adolescents and young adults who have been diagnosed with ADHD, the FDA said.

Recent data from the Centers for Disease Control and Prevention show that during the first year of the COVID-19 pandemic, prescriptions for stimulants increased 10% among older children and adults.
 

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

The Food and Drug Administration has announced new action to address ongoing concerns about misuse, abuse, addiction, and overdose of prescription stimulants used to treat attention-deficit/hyperactivity disorder (ADHD).

“The current prescribing information for some prescription stimulants does not provide up-to-date warnings about the harms of misuse and abuse, and particularly that most individuals who misuse prescription stimulants get their drugs from other family members or peers,” the FDA said in a drug safety communication.

Going forward, updated drug labels will clearly state that patients should never share their prescription stimulants with anyone, and the boxed warning will describe the risks of misuse, abuse, addiction, and overdose consistently for all medicines in the class, the FDA said.

The boxed warning will also advise heath care professionals to monitor patients closely for signs and symptoms of misuse, abuse, and addiction.

Patient medication guides will be updated to educate patients and caregivers about these risks.

The FDA encourages prescribers to assess patient risk of misuse, abuse, and addiction before prescribing a stimulant and to counsel patients not to share the medication.
 

Friends and family

A recent literature review by the FDA found that friends and family members are the most common source of prescription stimulant misuse and abuse (nonmedical use). Estimates of such use range from 56% to 80%.

Misuse/abuse of a patient’s own prescription make up 10%-20% of people who report nonmedical stimulant use.

Less commonly reported sources include drug dealers or strangers (4%-7% of people who report nonmedical use) and the Internet (1%-2%).

The groups at highest risk for misuse/abuse of prescription stimulants are young adults aged 18-25 years, college students, and adolescents and young adults who have been diagnosed with ADHD, the FDA said.

Recent data from the Centers for Disease Control and Prevention show that during the first year of the COVID-19 pandemic, prescriptions for stimulants increased 10% among older children and adults.
 

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

The Food and Drug Administration has announced new action to address ongoing concerns about misuse, abuse, addiction, and overdose of prescription stimulants used to treat attention-deficit/hyperactivity disorder (ADHD).

“The current prescribing information for some prescription stimulants does not provide up-to-date warnings about the harms of misuse and abuse, and particularly that most individuals who misuse prescription stimulants get their drugs from other family members or peers,” the FDA said in a drug safety communication.

Going forward, updated drug labels will clearly state that patients should never share their prescription stimulants with anyone, and the boxed warning will describe the risks of misuse, abuse, addiction, and overdose consistently for all medicines in the class, the FDA said.

The boxed warning will also advise heath care professionals to monitor patients closely for signs and symptoms of misuse, abuse, and addiction.

Patient medication guides will be updated to educate patients and caregivers about these risks.

The FDA encourages prescribers to assess patient risk of misuse, abuse, and addiction before prescribing a stimulant and to counsel patients not to share the medication.
 

Friends and family

A recent literature review by the FDA found that friends and family members are the most common source of prescription stimulant misuse and abuse (nonmedical use). Estimates of such use range from 56% to 80%.

Misuse/abuse of a patient’s own prescription make up 10%-20% of people who report nonmedical stimulant use.

Less commonly reported sources include drug dealers or strangers (4%-7% of people who report nonmedical use) and the Internet (1%-2%).

The groups at highest risk for misuse/abuse of prescription stimulants are young adults aged 18-25 years, college students, and adolescents and young adults who have been diagnosed with ADHD, the FDA said.

Recent data from the Centers for Disease Control and Prevention show that during the first year of the COVID-19 pandemic, prescriptions for stimulants increased 10% among older children and adults.
 

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

The Food and Drug Administration has approved the oral medication fezolinetant (Veozah) for the treatment of moderate to severe hot flashes in menopausal women, according to an FDA statement. The approved dose is 45 mg once daily.

Fezolinetant, a neurokinin 3 (NK3) receptor antagonist, is the first drug of its kind to earn FDA approval for the vasomotor symptoms associated with menopause, according to the statement. The drug works by binding to the NK3 receptor, which plays a role in regulating body temperature, and blocking its activity. Fezolinetant is not a hormone, and can be taken by women for whom hormones are contraindicated, such as those with a history of vaginal bleeding, stroke, heart attack, blood clots, or liver disease, the FDA stated.

The approval was based on data from the SKYLIGHT 2 trial, results of which were presented at the annual meeting of the Endocrine Society, reported by this news organization, and published in the Journal of Clinical Endocrinology and Metabolism.

In the two-phase trial, women were randomized to 30 mg or 45 mg of fezolinetant or a placebo. After 12 weeks, women in placebo groups were rerandomized to fezolinetant for a 40-week safety study.

The study population included women aged 40-65 years, with an average minimum of seven moderate-to-severe hot flashes per day. The study included 120 sites in North America and Europe.

At 12 weeks, both placebo and fezolinetant patients experienced reductions in moderate to severe vasomotor symptoms of approximately 60%, as well as a significant decrease in vasomotor symptom severity.

The FDA statement noted that patients should undergo baseline blood work before starting fezolinetant to test for liver infection or damage, and the prescribing information includes a warning for liver injury; blood work should be repeated at 3, 6, and 9 months after starting the medication, according to the FDA and a press release from the manufacturer Astellas.

The most common side effects associated with fezolinetant include abdominal pain, diarrhea, insomnia, back pain, hot flashes, and elevated liver values, according to the FDA statement. The FDA granted Astellas Pharma’s application a Priority Review designation. Astellas has priced the drug at $550 for a 30-day supply, significantly higher than the Institute for Clinical and Economic Review’s previously recommended range of $2,000 to $2,500 per year.

Full prescribing information is available here.

The Food and Drug Administration has approved the oral medication fezolinetant (Veozah) for the treatment of moderate to severe hot flashes in menopausal women, according to an FDA statement. The approved dose is 45 mg once daily.

Fezolinetant, a neurokinin 3 (NK3) receptor antagonist, is the first drug of its kind to earn FDA approval for the vasomotor symptoms associated with menopause, according to the statement. The drug works by binding to the NK3 receptor, which plays a role in regulating body temperature, and blocking its activity. Fezolinetant is not a hormone, and can be taken by women for whom hormones are contraindicated, such as those with a history of vaginal bleeding, stroke, heart attack, blood clots, or liver disease, the FDA stated.

The approval was based on data from the SKYLIGHT 2 trial, results of which were presented at the annual meeting of the Endocrine Society, reported by this news organization, and published in the Journal of Clinical Endocrinology and Metabolism.

In the two-phase trial, women were randomized to 30 mg or 45 mg of fezolinetant or a placebo. After 12 weeks, women in placebo groups were rerandomized to fezolinetant for a 40-week safety study.

The study population included women aged 40-65 years, with an average minimum of seven moderate-to-severe hot flashes per day. The study included 120 sites in North America and Europe.

At 12 weeks, both placebo and fezolinetant patients experienced reductions in moderate to severe vasomotor symptoms of approximately 60%, as well as a significant decrease in vasomotor symptom severity.

The FDA statement noted that patients should undergo baseline blood work before starting fezolinetant to test for liver infection or damage, and the prescribing information includes a warning for liver injury; blood work should be repeated at 3, 6, and 9 months after starting the medication, according to the FDA and a press release from the manufacturer Astellas.

The most common side effects associated with fezolinetant include abdominal pain, diarrhea, insomnia, back pain, hot flashes, and elevated liver values, according to the FDA statement. The FDA granted Astellas Pharma’s application a Priority Review designation. Astellas has priced the drug at $550 for a 30-day supply, significantly higher than the Institute for Clinical and Economic Review’s previously recommended range of $2,000 to $2,500 per year.

Full prescribing information is available here.

The Food and Drug Administration has approved the oral medication fezolinetant (Veozah) for the treatment of moderate to severe hot flashes in menopausal women, according to an FDA statement. The approved dose is 45 mg once daily.

Fezolinetant, a neurokinin 3 (NK3) receptor antagonist, is the first drug of its kind to earn FDA approval for the vasomotor symptoms associated with menopause, according to the statement. The drug works by binding to the NK3 receptor, which plays a role in regulating body temperature, and blocking its activity. Fezolinetant is not a hormone, and can be taken by women for whom hormones are contraindicated, such as those with a history of vaginal bleeding, stroke, heart attack, blood clots, or liver disease, the FDA stated.

The approval was based on data from the SKYLIGHT 2 trial, results of which were presented at the annual meeting of the Endocrine Society, reported by this news organization, and published in the Journal of Clinical Endocrinology and Metabolism.

In the two-phase trial, women were randomized to 30 mg or 45 mg of fezolinetant or a placebo. After 12 weeks, women in placebo groups were rerandomized to fezolinetant for a 40-week safety study.

The study population included women aged 40-65 years, with an average minimum of seven moderate-to-severe hot flashes per day. The study included 120 sites in North America and Europe.

At 12 weeks, both placebo and fezolinetant patients experienced reductions in moderate to severe vasomotor symptoms of approximately 60%, as well as a significant decrease in vasomotor symptom severity.

The FDA statement noted that patients should undergo baseline blood work before starting fezolinetant to test for liver infection or damage, and the prescribing information includes a warning for liver injury; blood work should be repeated at 3, 6, and 9 months after starting the medication, according to the FDA and a press release from the manufacturer Astellas.

The most common side effects associated with fezolinetant include abdominal pain, diarrhea, insomnia, back pain, hot flashes, and elevated liver values, according to the FDA statement. The FDA granted Astellas Pharma’s application a Priority Review designation. Astellas has priced the drug at $550 for a 30-day supply, significantly higher than the Institute for Clinical and Economic Review’s previously recommended range of $2,000 to $2,500 per year.

Full prescribing information is available here.

The U.S. Food and Drug Administration has approved pegunigalsidase alfa (Elfabrio, Chiesi Global Rare Diseases/Protalix BioTherapeutics), an enzyme replacement therapy (ERT) to treat adults with confirmed Fabry disease.

Fabry disease is a rare inherited X-linked lysosomal disorder caused by a deficiency of the enzyme alpha-galactosidase A (GLA), which leads to the buildup of globotriaosylceramide (GL-3) in blood vessels, kidneys, the heart, nerves, and other organs, increasing the risk for kidney failure, myocardial infarction, stroke, and other problems.

Elfabrio delivers a functional version of GLA. It’s given by intravenous infusion every 2 weeks.

Evidence for safety, tolerability, and efficacy of Elfabrio stems from a comprehensive clinical program in more than 140 patients with up to 7.5 years of follow up treatment.

It has been studied in both ERT-naïve and ERT-experienced patients. In one head-to-head trial, Elfabrio was non-inferior in safety and efficacy to agalsidase beta (Fabrazyme, Sanofi Genzyme), the companies said in a press statement announcing approval.

“The totality of clinical data suggests that Elfabrio has the potential to be a long-lasting therapy,” Dror Bashan, president and CEO of Protalix, said in the statement.

Patients treated with Elfabrio have experienced hypersensitivity reactions, including anaphylaxis. In clinical trials, 20 (14%) patients treated with Elfabrio experienced hypersensitivity reactions; 4 patients (3%) experienced anaphylaxis reactions that occurred within 5-40 minutes of the start of the initial infusion.

Before administering Elfabrio, pretreatment with antihistamines, antipyretics, and/or corticosteroids should be considered, the label advises.

Patients and caregivers should be informed of the signs and symptoms of hypersensitivity reactions and infusion-associated reactions and instructed to seek medical care immediately if such symptoms occur.

A case of membranoproliferative glomerulonephritis with immune depositions in the kidney was reported during clinical trials. Monitoring serum creatinine and urinary protein-to-creatinine ratio is advised. If glomerulonephritis is suspected, treatment should be stopped until a diagnostic evaluation can be conducted.

Full prescribing information is available online.

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

The U.S. Food and Drug Administration has approved pegunigalsidase alfa (Elfabrio, Chiesi Global Rare Diseases/Protalix BioTherapeutics), an enzyme replacement therapy (ERT) to treat adults with confirmed Fabry disease.

Fabry disease is a rare inherited X-linked lysosomal disorder caused by a deficiency of the enzyme alpha-galactosidase A (GLA), which leads to the buildup of globotriaosylceramide (GL-3) in blood vessels, kidneys, the heart, nerves, and other organs, increasing the risk for kidney failure, myocardial infarction, stroke, and other problems.

Elfabrio delivers a functional version of GLA. It’s given by intravenous infusion every 2 weeks.

Evidence for safety, tolerability, and efficacy of Elfabrio stems from a comprehensive clinical program in more than 140 patients with up to 7.5 years of follow up treatment.

It has been studied in both ERT-naïve and ERT-experienced patients. In one head-to-head trial, Elfabrio was non-inferior in safety and efficacy to agalsidase beta (Fabrazyme, Sanofi Genzyme), the companies said in a press statement announcing approval.

“The totality of clinical data suggests that Elfabrio has the potential to be a long-lasting therapy,” Dror Bashan, president and CEO of Protalix, said in the statement.

Patients treated with Elfabrio have experienced hypersensitivity reactions, including anaphylaxis. In clinical trials, 20 (14%) patients treated with Elfabrio experienced hypersensitivity reactions; 4 patients (3%) experienced anaphylaxis reactions that occurred within 5-40 minutes of the start of the initial infusion.

Before administering Elfabrio, pretreatment with antihistamines, antipyretics, and/or corticosteroids should be considered, the label advises.

Patients and caregivers should be informed of the signs and symptoms of hypersensitivity reactions and infusion-associated reactions and instructed to seek medical care immediately if such symptoms occur.

A case of membranoproliferative glomerulonephritis with immune depositions in the kidney was reported during clinical trials. Monitoring serum creatinine and urinary protein-to-creatinine ratio is advised. If glomerulonephritis is suspected, treatment should be stopped until a diagnostic evaluation can be conducted.

Full prescribing information is available online.

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

The U.S. Food and Drug Administration has approved pegunigalsidase alfa (Elfabrio, Chiesi Global Rare Diseases/Protalix BioTherapeutics), an enzyme replacement therapy (ERT) to treat adults with confirmed Fabry disease.

Fabry disease is a rare inherited X-linked lysosomal disorder caused by a deficiency of the enzyme alpha-galactosidase A (GLA), which leads to the buildup of globotriaosylceramide (GL-3) in blood vessels, kidneys, the heart, nerves, and other organs, increasing the risk for kidney failure, myocardial infarction, stroke, and other problems.

Elfabrio delivers a functional version of GLA. It’s given by intravenous infusion every 2 weeks.

Evidence for safety, tolerability, and efficacy of Elfabrio stems from a comprehensive clinical program in more than 140 patients with up to 7.5 years of follow up treatment.

It has been studied in both ERT-naïve and ERT-experienced patients. In one head-to-head trial, Elfabrio was non-inferior in safety and efficacy to agalsidase beta (Fabrazyme, Sanofi Genzyme), the companies said in a press statement announcing approval.

“The totality of clinical data suggests that Elfabrio has the potential to be a long-lasting therapy,” Dror Bashan, president and CEO of Protalix, said in the statement.

Patients treated with Elfabrio have experienced hypersensitivity reactions, including anaphylaxis. In clinical trials, 20 (14%) patients treated with Elfabrio experienced hypersensitivity reactions; 4 patients (3%) experienced anaphylaxis reactions that occurred within 5-40 minutes of the start of the initial infusion.

Before administering Elfabrio, pretreatment with antihistamines, antipyretics, and/or corticosteroids should be considered, the label advises.

Patients and caregivers should be informed of the signs and symptoms of hypersensitivity reactions and infusion-associated reactions and instructed to seek medical care immediately if such symptoms occur.

A case of membranoproliferative glomerulonephritis with immune depositions in the kidney was reported during clinical trials. Monitoring serum creatinine and urinary protein-to-creatinine ratio is advised. If glomerulonephritis is suspected, treatment should be stopped until a diagnostic evaluation can be conducted.

Full prescribing information is available online.

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

The Food and Drug Administration has approved the antipsychotic brexpiprazole (Rexulti, Otsuka and Lundbeck) for agitation associated with Alzheimer’s disease (AD), making it the first FDA-approved drug for this indication.

“Agitation is one of the most common and challenging aspects of care among patients with dementia due to Alzheimer’s disease,” Tiffany Farchione, MD, director of the division of psychiatry in the FDA’s Center for Drug Evaluation and Research, said in a news release.

Olivier Le Moal/Getty Images

Agitation can include symptoms that range from pacing or restlessness to verbal and physical aggression. “These symptoms are leading causes of assisted living or nursing home placement and have been associated with accelerated disease progression,” Dr. Farchione said.

Brexpiprazole was approved by the FDA in 2015 as an adjunctive therapy to antidepressants for adults with major depressive disorder and for adults with schizophrenia.

Approval of the supplemental application for brexpiprazole for agitation associated with AD dementia was based on results of two randomized, double-blind, placebo-controlled studies.

In both studies, patients who received 2 mg or 3 mg of brexpiprazole showed statistically significant and clinically meaningful improvements in agitation symptoms, as shown by total Cohen-Mansfield Agitation Inventory (CMAI) score, compared with patients who received placebo.

The recommended starting dosage for the treatment of agitation associated with AD dementia is 0.5 mg once daily on days 1-7; it was increased to 1 mg once daily on days 8-14 and then to the recommended target dose of 2 mg once daily.

The dosage can be increased to the maximum recommended daily dosage of 3 mg once daily after at least 14 days, depending on clinical response and tolerability.

The most common side effects of brexpiprazole in patients with agitation associated with AD dementia include headache, dizziness, urinary tract infection, nasopharyngitis, and sleep disturbances.

The drug includes a boxed warning for medications in this class that elderly patients with dementia-related psychosis treated with antipsychotic drugs are at an increased risk of death.

The supplemental application for brexpiprazole for agitation had fast-track designation.

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

The Food and Drug Administration has approved the antipsychotic brexpiprazole (Rexulti, Otsuka and Lundbeck) for agitation associated with Alzheimer’s disease (AD), making it the first FDA-approved drug for this indication.

“Agitation is one of the most common and challenging aspects of care among patients with dementia due to Alzheimer’s disease,” Tiffany Farchione, MD, director of the division of psychiatry in the FDA’s Center for Drug Evaluation and Research, said in a news release.

Olivier Le Moal/Getty Images

Agitation can include symptoms that range from pacing or restlessness to verbal and physical aggression. “These symptoms are leading causes of assisted living or nursing home placement and have been associated with accelerated disease progression,” Dr. Farchione said.

Brexpiprazole was approved by the FDA in 2015 as an adjunctive therapy to antidepressants for adults with major depressive disorder and for adults with schizophrenia.

Approval of the supplemental application for brexpiprazole for agitation associated with AD dementia was based on results of two randomized, double-blind, placebo-controlled studies.

In both studies, patients who received 2 mg or 3 mg of brexpiprazole showed statistically significant and clinically meaningful improvements in agitation symptoms, as shown by total Cohen-Mansfield Agitation Inventory (CMAI) score, compared with patients who received placebo.

The recommended starting dosage for the treatment of agitation associated with AD dementia is 0.5 mg once daily on days 1-7; it was increased to 1 mg once daily on days 8-14 and then to the recommended target dose of 2 mg once daily.

The dosage can be increased to the maximum recommended daily dosage of 3 mg once daily after at least 14 days, depending on clinical response and tolerability.

The most common side effects of brexpiprazole in patients with agitation associated with AD dementia include headache, dizziness, urinary tract infection, nasopharyngitis, and sleep disturbances.

The drug includes a boxed warning for medications in this class that elderly patients with dementia-related psychosis treated with antipsychotic drugs are at an increased risk of death.

The supplemental application for brexpiprazole for agitation had fast-track designation.

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

The Food and Drug Administration has approved the antipsychotic brexpiprazole (Rexulti, Otsuka and Lundbeck) for agitation associated with Alzheimer’s disease (AD), making it the first FDA-approved drug for this indication.

“Agitation is one of the most common and challenging aspects of care among patients with dementia due to Alzheimer’s disease,” Tiffany Farchione, MD, director of the division of psychiatry in the FDA’s Center for Drug Evaluation and Research, said in a news release.

Olivier Le Moal/Getty Images

Agitation can include symptoms that range from pacing or restlessness to verbal and physical aggression. “These symptoms are leading causes of assisted living or nursing home placement and have been associated with accelerated disease progression,” Dr. Farchione said.

Brexpiprazole was approved by the FDA in 2015 as an adjunctive therapy to antidepressants for adults with major depressive disorder and for adults with schizophrenia.

Approval of the supplemental application for brexpiprazole for agitation associated with AD dementia was based on results of two randomized, double-blind, placebo-controlled studies.

In both studies, patients who received 2 mg or 3 mg of brexpiprazole showed statistically significant and clinically meaningful improvements in agitation symptoms, as shown by total Cohen-Mansfield Agitation Inventory (CMAI) score, compared with patients who received placebo.

The recommended starting dosage for the treatment of agitation associated with AD dementia is 0.5 mg once daily on days 1-7; it was increased to 1 mg once daily on days 8-14 and then to the recommended target dose of 2 mg once daily.

The dosage can be increased to the maximum recommended daily dosage of 3 mg once daily after at least 14 days, depending on clinical response and tolerability.

The most common side effects of brexpiprazole in patients with agitation associated with AD dementia include headache, dizziness, urinary tract infection, nasopharyngitis, and sleep disturbances.

The drug includes a boxed warning for medications in this class that elderly patients with dementia-related psychosis treated with antipsychotic drugs are at an increased risk of death.

The supplemental application for brexpiprazole for agitation had fast-track designation.

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

Leaders of medical student groups and legislators in a few states are trying to convince medical schools to end a century-old practice of legacy admissions, which they say offer preferential treatment to applicants based on their association with donors or alumni.

While an estimated 25% of public colleges and universities still use legacy admissions, a growing list of top medical schools have moved away from the practice over the last decade, including Johns Hopkins University, Baltimore, and Tufts University, Medford, Mass.

Legacy admissions contradict schools’ more inclusive policies, Senila Yasmin, MPH, a second-year medical student at Tufts University, said in an interview. While Tufts maintains legacy admissions for its undergraduate applicants, the medical school stopped the practice in 2021, said Ms. Yasmin, a member of a student group that lobbied against the school’s legacy preferences.

Describing herself as a low-income, first-generation Muslim-Pakistani American, Ms. Yasmin wants to use her experience at Tufts to improve accessibility for students like herself.

As a member of the American Medical Association (AMA) Medical Student Section, she coauthored a resolution stating that legacy admissions go against the AMA’s strategic plan to advance racial justice and health equity. The Student Section passed the resolution in November, and in June, the AMA House of Delegates will vote on whether to adopt the policy. 

Along with a Supreme Court decision that could strike down race-conscious college admissions, an AMA policy could convince medical schools to rethink legacy admissions and how to maintain diverse student bodies. In June, the court is expected to issue a decision in the Students for Fair Admissions lawsuit against Harvard University, Cambridge, Mass., and the University of North Carolina, Chapel Hill, which alleges that considering race in holistic admissions constitutes racial discrimination and violates the Equal Protection Clause.

Opponents of legacy admissions, like Ms. Yasmin, say it penalizes students from racial minorities and lower socioeconomic backgrounds, hampering a fair and equitable admissions process that attracts diverse medical school admissions.
 

Diversity of medical applicants

Diversity in medical schools  continued to increase last year with more Black, Hispanic, and female students applying and enrolling, according to a recent report by the Association of American Medical Colleges (AAMC). However, universities often include nonacademic criteria in their admission assessments to improve educational access for underrepresented minorities.

Medical schools carefully consider each applicant’s background “to yield a diverse class of students,” Geoffrey Young, PhD, AAMC’s senior director of transforming the health care workforce, told this news organization.

Some schools, such as Morehouse School of Medicine, Atlanta, the University of Virginia School of Medicine, Charlottesville, and the University of Arizona College of Medicine, Tucson, perform a thorough review of candidates while offering admissions practices designed specifically for legacy applicants. The schools assert that legacy designation doesn’t factor into the student’s likelihood of acceptance.

The arrangement may show that schools want to commit to equity and fairness but have trouble moving away from entrenched traditions, two professors from Penn State College of Medicine, Hershey, Pa., who sit on separate medical admissions subcommittees, wrote last year in Bioethics Today.
 

Legislation may hasten legacies’ end

In December, Ms. Yasmin and a group of Massachusetts Medical Society student-members presented another resolution to the state medical society, which adopted it.

The society’s new policy opposes the use of legacy status in medical school admissions and supports mechanisms to eliminate its inclusion from the application process, Theodore Calianos II, MD, FACS, president of the Massachusetts Medical Society, said in an interview.

“Legacy preferences limit racial and socioeconomic diversity on campuses, so we asked, ‘What can we do so that everyone has equal access to medical education?’ It is exciting to see the students and young physicians – the future of medicine – become involved in policymaking.”

Proposed laws may also hasten the end of legacy admissions. Last year, the U.S. Senate began considering a bill prohibiting colleges receiving federal financial aid from giving preferential treatment to students based on their relations to donors or alumni. However, the bill allows the Department of Education to make exceptions for institutions serving historically underrepresented groups.

The New York State Senate and the New York State Assembly also are reviewing bills that ban legacy and early admissions policies at public and private universities. Connecticut announced similar legislation last year. Massachusetts legislators are considering two bills: one that would ban the practice at the state’s public universities and another that would require all schools using legacy status to pay a “public service fee” equal to a percentage of its endowment. Colleges with endowment assets exceeding $2 billion must pay at least $2 million, according to the bill’s text.

At schools like Harvard,  whose endowment surpasses $50 billion, the option to pay the penalty will make the law moot, Michael Walls, DO, MPH, president of the American Medical Student Association (AMSA), said in an interview. “Smaller schools wouldn’t be able to afford the fine and are less likely to be doing [legacy admissions] anyway,” he said. “The schools that want to continue doing it could just pay the fine.”

Dr. Walls said AMSA supports race-conscious admissions processes and anything that increases fairness for medical school applicants. “Whatever [fair] means is up for interpretation, but it would be great to eliminate legacy admissions,” he said.   
 

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

Leaders of medical student groups and legislators in a few states are trying to convince medical schools to end a century-old practice of legacy admissions, which they say offer preferential treatment to applicants based on their association with donors or alumni.

While an estimated 25% of public colleges and universities still use legacy admissions, a growing list of top medical schools have moved away from the practice over the last decade, including Johns Hopkins University, Baltimore, and Tufts University, Medford, Mass.

Legacy admissions contradict schools’ more inclusive policies, Senila Yasmin, MPH, a second-year medical student at Tufts University, said in an interview. While Tufts maintains legacy admissions for its undergraduate applicants, the medical school stopped the practice in 2021, said Ms. Yasmin, a member of a student group that lobbied against the school’s legacy preferences.

Describing herself as a low-income, first-generation Muslim-Pakistani American, Ms. Yasmin wants to use her experience at Tufts to improve accessibility for students like herself.

As a member of the American Medical Association (AMA) Medical Student Section, she coauthored a resolution stating that legacy admissions go against the AMA’s strategic plan to advance racial justice and health equity. The Student Section passed the resolution in November, and in June, the AMA House of Delegates will vote on whether to adopt the policy. 

Along with a Supreme Court decision that could strike down race-conscious college admissions, an AMA policy could convince medical schools to rethink legacy admissions and how to maintain diverse student bodies. In June, the court is expected to issue a decision in the Students for Fair Admissions lawsuit against Harvard University, Cambridge, Mass., and the University of North Carolina, Chapel Hill, which alleges that considering race in holistic admissions constitutes racial discrimination and violates the Equal Protection Clause.

Opponents of legacy admissions, like Ms. Yasmin, say it penalizes students from racial minorities and lower socioeconomic backgrounds, hampering a fair and equitable admissions process that attracts diverse medical school admissions.
 

Diversity of medical applicants

Diversity in medical schools  continued to increase last year with more Black, Hispanic, and female students applying and enrolling, according to a recent report by the Association of American Medical Colleges (AAMC). However, universities often include nonacademic criteria in their admission assessments to improve educational access for underrepresented minorities.

Medical schools carefully consider each applicant’s background “to yield a diverse class of students,” Geoffrey Young, PhD, AAMC’s senior director of transforming the health care workforce, told this news organization.

Some schools, such as Morehouse School of Medicine, Atlanta, the University of Virginia School of Medicine, Charlottesville, and the University of Arizona College of Medicine, Tucson, perform a thorough review of candidates while offering admissions practices designed specifically for legacy applicants. The schools assert that legacy designation doesn’t factor into the student’s likelihood of acceptance.

The arrangement may show that schools want to commit to equity and fairness but have trouble moving away from entrenched traditions, two professors from Penn State College of Medicine, Hershey, Pa., who sit on separate medical admissions subcommittees, wrote last year in Bioethics Today.
 

Legislation may hasten legacies’ end

In December, Ms. Yasmin and a group of Massachusetts Medical Society student-members presented another resolution to the state medical society, which adopted it.

The society’s new policy opposes the use of legacy status in medical school admissions and supports mechanisms to eliminate its inclusion from the application process, Theodore Calianos II, MD, FACS, president of the Massachusetts Medical Society, said in an interview.

“Legacy preferences limit racial and socioeconomic diversity on campuses, so we asked, ‘What can we do so that everyone has equal access to medical education?’ It is exciting to see the students and young physicians – the future of medicine – become involved in policymaking.”

Proposed laws may also hasten the end of legacy admissions. Last year, the U.S. Senate began considering a bill prohibiting colleges receiving federal financial aid from giving preferential treatment to students based on their relations to donors or alumni. However, the bill allows the Department of Education to make exceptions for institutions serving historically underrepresented groups.

The New York State Senate and the New York State Assembly also are reviewing bills that ban legacy and early admissions policies at public and private universities. Connecticut announced similar legislation last year. Massachusetts legislators are considering two bills: one that would ban the practice at the state’s public universities and another that would require all schools using legacy status to pay a “public service fee” equal to a percentage of its endowment. Colleges with endowment assets exceeding $2 billion must pay at least $2 million, according to the bill’s text.

At schools like Harvard,  whose endowment surpasses $50 billion, the option to pay the penalty will make the law moot, Michael Walls, DO, MPH, president of the American Medical Student Association (AMSA), said in an interview. “Smaller schools wouldn’t be able to afford the fine and are less likely to be doing [legacy admissions] anyway,” he said. “The schools that want to continue doing it could just pay the fine.”

Dr. Walls said AMSA supports race-conscious admissions processes and anything that increases fairness for medical school applicants. “Whatever [fair] means is up for interpretation, but it would be great to eliminate legacy admissions,” he said.   
 

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

Leaders of medical student groups and legislators in a few states are trying to convince medical schools to end a century-old practice of legacy admissions, which they say offer preferential treatment to applicants based on their association with donors or alumni.

While an estimated 25% of public colleges and universities still use legacy admissions, a growing list of top medical schools have moved away from the practice over the last decade, including Johns Hopkins University, Baltimore, and Tufts University, Medford, Mass.

Legacy admissions contradict schools’ more inclusive policies, Senila Yasmin, MPH, a second-year medical student at Tufts University, said in an interview. While Tufts maintains legacy admissions for its undergraduate applicants, the medical school stopped the practice in 2021, said Ms. Yasmin, a member of a student group that lobbied against the school’s legacy preferences.

Describing herself as a low-income, first-generation Muslim-Pakistani American, Ms. Yasmin wants to use her experience at Tufts to improve accessibility for students like herself.

As a member of the American Medical Association (AMA) Medical Student Section, she coauthored a resolution stating that legacy admissions go against the AMA’s strategic plan to advance racial justice and health equity. The Student Section passed the resolution in November, and in June, the AMA House of Delegates will vote on whether to adopt the policy. 

Along with a Supreme Court decision that could strike down race-conscious college admissions, an AMA policy could convince medical schools to rethink legacy admissions and how to maintain diverse student bodies. In June, the court is expected to issue a decision in the Students for Fair Admissions lawsuit against Harvard University, Cambridge, Mass., and the University of North Carolina, Chapel Hill, which alleges that considering race in holistic admissions constitutes racial discrimination and violates the Equal Protection Clause.

Opponents of legacy admissions, like Ms. Yasmin, say it penalizes students from racial minorities and lower socioeconomic backgrounds, hampering a fair and equitable admissions process that attracts diverse medical school admissions.
 

Diversity of medical applicants

Diversity in medical schools  continued to increase last year with more Black, Hispanic, and female students applying and enrolling, according to a recent report by the Association of American Medical Colleges (AAMC). However, universities often include nonacademic criteria in their admission assessments to improve educational access for underrepresented minorities.

Medical schools carefully consider each applicant’s background “to yield a diverse class of students,” Geoffrey Young, PhD, AAMC’s senior director of transforming the health care workforce, told this news organization.

Some schools, such as Morehouse School of Medicine, Atlanta, the University of Virginia School of Medicine, Charlottesville, and the University of Arizona College of Medicine, Tucson, perform a thorough review of candidates while offering admissions practices designed specifically for legacy applicants. The schools assert that legacy designation doesn’t factor into the student’s likelihood of acceptance.

The arrangement may show that schools want to commit to equity and fairness but have trouble moving away from entrenched traditions, two professors from Penn State College of Medicine, Hershey, Pa., who sit on separate medical admissions subcommittees, wrote last year in Bioethics Today.
 

Legislation may hasten legacies’ end

In December, Ms. Yasmin and a group of Massachusetts Medical Society student-members presented another resolution to the state medical society, which adopted it.

The society’s new policy opposes the use of legacy status in medical school admissions and supports mechanisms to eliminate its inclusion from the application process, Theodore Calianos II, MD, FACS, president of the Massachusetts Medical Society, said in an interview.

“Legacy preferences limit racial and socioeconomic diversity on campuses, so we asked, ‘What can we do so that everyone has equal access to medical education?’ It is exciting to see the students and young physicians – the future of medicine – become involved in policymaking.”

Proposed laws may also hasten the end of legacy admissions. Last year, the U.S. Senate began considering a bill prohibiting colleges receiving federal financial aid from giving preferential treatment to students based on their relations to donors or alumni. However, the bill allows the Department of Education to make exceptions for institutions serving historically underrepresented groups.

The New York State Senate and the New York State Assembly also are reviewing bills that ban legacy and early admissions policies at public and private universities. Connecticut announced similar legislation last year. Massachusetts legislators are considering two bills: one that would ban the practice at the state’s public universities and another that would require all schools using legacy status to pay a “public service fee” equal to a percentage of its endowment. Colleges with endowment assets exceeding $2 billion must pay at least $2 million, according to the bill’s text.

At schools like Harvard,  whose endowment surpasses $50 billion, the option to pay the penalty will make the law moot, Michael Walls, DO, MPH, president of the American Medical Student Association (AMSA), said in an interview. “Smaller schools wouldn’t be able to afford the fine and are less likely to be doing [legacy admissions] anyway,” he said. “The schools that want to continue doing it could just pay the fine.”

Dr. Walls said AMSA supports race-conscious admissions processes and anything that increases fairness for medical school applicants. “Whatever [fair] means is up for interpretation, but it would be great to eliminate legacy admissions,” he said.   
 

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

SEATTLE – Use of a new kind of assay – sequential beta-hydroxybutyrate testing – with a cut-off for ruling out insulinoma in patients with hypoglycemia may allow for a shortening of the standard 72-hour fasting time, therefore yielding significant hospital cost savings, new data suggest.

Insulinomas are small, rare types of pancreatic tumors that are benign but secrete excess insulin, leading to hypoglycemia. More than 99% of people with insulinomas develop hypoglycemia within 72 hours, hence, the use of a 72-hour fast to detect these tumors.

But most people who are evaluated for hypoglycemia do not have an insulinoma and fasting in hospital for 3 days is burdensome and costly.  

As part of a quality improvement project, Cleveland Clinic endocrinology fellow Michelle D. Lundholm, MD, and colleagues modified their hospital’s protocol to include measurement of beta-hydroxybutyrate (BHB), a marker of insulin suppression, every 12 hours with a cutoff of ≥ 2.7mmol/L for stopping the fast if hypoglycemia (venous glucose ≤ 45mg/dL) hasn’t occurred. This intervention cut in half the number of patients who needed to fast for the full 72 hours, without missing any insulinomas.

“We are excited to share how a relatively simple adjustment to our protocol allowed us to successfully reduce the burden of fasting on patients and more effectively utilize hospital resources. We hope that this encourages other centers to consider doing the same,” Dr. Lundholm said in an interview.

“These data support a 48-hour fast. The literature supports that’s sufficient to detect 95% of insulinomas. ... But, given our small insulinoma cohort, we are looking forward to learning from other studies,” she added.

Dr. Lundholm presented the late-breaking oral abstract at the annual scientific & clinical congress of the American Association of Clinical Endocrinology.

Asked to comment, session moderator Jenna Sarvaideo, MD, said: “We’re often steeped in tradition. That’s why this abstract and this quality improvement project is so exciting to me because it challenges the history. … and I think it’s ultimately helping patients.”

Dr. Sarvaideo, of Clement J. Zablocki VA Medical Center, Milwaukee, noted that, typically, although the fast will be stopped before 72 hours if the patient develops hypoglycemia, “often they don’t, so we keep going on and on. If we just paid more attention to the beta-hydroxybutyrate, I think that would be practice changing.”

She added that more data would be optimal, given that there were under 100 patients in the study, “but I do think that devising protocols is … very much still at the hands of the endocrinologists. I think that this work could make groups reevaluate their protocol and change it, maybe even with a small dataset and then move on from there and see what they see.”

Indeed, Dr. Lundholm pointed out that some institutions, such as the Mayo Clinic, already include 6-hour BHB measurements (along with glucose and insulin) in their protocols.

“For any institution that already draws regular BHB levels like this, it would be very easy to implement a new stopping criterion without adding any additional costs,” she said in an interview.
 

All insulinomas became apparent in less than 48 hours

The first report to look at the value of testing BHB at regular intervals was published by the Mayo Clinic in 2005 after they noticed patients without insulinoma were complaining of ketosis symptoms such as foul breath and digestive problems toward the end of the fast.

However, although BHB testing is used today as part of the evaluation, it’s typically only drawn at the start of the protocol and again at the time of hypoglycemia or at the end of 72 hours because more frequent values hadn’t been thought to be useful for guiding clinical management, Dr. Lundholm explained. 

Between January 2018 and June 2020, Dr. Lundholm and colleagues followed 34 Cleveland Clinic patients who completed the usual 72-hour fast protocol. Overall, 71% were female, and 26% had undergone prior bariatric surgery procedures. Eleven (32%) developed hypoglycemia and stopped fasting. The other 23 (68%) fasted for the full 72 hours.

Dr. Lundholm and colleagues determined that the fast could have ended earlier in 35% of patients based on an elevated BHB without missing any insulinomas.

And so, in June 2020 the group revised their protocol to include the BHB ≥ 2.7mmol/L stopping criterion. Of the 30 patients evaluated from June 2020 to January 2023, 87% were female and 17% had undergone a bariatric procedure.

Here, 15 (50%) reached a BHB ≥ 2.7mmol/L and ended their fast at an average of 43.8 hours. Another seven (23%) ended the fast after developing hypoglycemia. Just eight patients (27%) fasted for the full 72 hours.

Overall, this resulted in approximately 376 fewer cumulative hours of inpatient admission than if patients had fasted for the full time.

Of the 64 patients who have completed the fasting protocol since 2018, seven (11%) who did have an insulinoma developed hypoglycemia within 48 hours and with a BHB < 2.7 mmol/L (median, 0.15).
 

Advantages: cost, adherence

A day in a general medicine bed at Cleveland Clinic was quoted as costing $2,420, based on publicly available information as of Jan. 1, 2023. “If half of patients leave 1 day earlier, this equates to about $1,210 per patient in savings from bed costs alone,” Dr. Lundholm told this news organization.  

The revised protocol required an additional two to four blood draws, depending on the length of the fast. “The cost of these extra blood tests varies by lab and by count, but even at its highest does not exceed the amount of savings from bed costs,” she noted.

Patient adherence is another potential benefit of the revised protocol.

“Any study that requires 72 hours of patient cooperation is a challenge, particularly in an uncomfortable position like fasting. When we looked at these adherence numbers, we found that the percentage of patients who prematurely ended their fast decreased from 35% to 17% with the updated protocol,” Dr. Lundholm continued.

“This translates to fewer inconclusive results and fewer readmissions for repeat 72-hour fasting. While this was not our primary outcome, it was another noted benefit of our change,” she said.

Dr. Lundholm and Dr. Sarvaideo have reported no relevant financial relationships.

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

SEATTLE – Use of a new kind of assay – sequential beta-hydroxybutyrate testing – with a cut-off for ruling out insulinoma in patients with hypoglycemia may allow for a shortening of the standard 72-hour fasting time, therefore yielding significant hospital cost savings, new data suggest.

Insulinomas are small, rare types of pancreatic tumors that are benign but secrete excess insulin, leading to hypoglycemia. More than 99% of people with insulinomas develop hypoglycemia within 72 hours, hence, the use of a 72-hour fast to detect these tumors.

But most people who are evaluated for hypoglycemia do not have an insulinoma and fasting in hospital for 3 days is burdensome and costly.  

As part of a quality improvement project, Cleveland Clinic endocrinology fellow Michelle D. Lundholm, MD, and colleagues modified their hospital’s protocol to include measurement of beta-hydroxybutyrate (BHB), a marker of insulin suppression, every 12 hours with a cutoff of ≥ 2.7mmol/L for stopping the fast if hypoglycemia (venous glucose ≤ 45mg/dL) hasn’t occurred. This intervention cut in half the number of patients who needed to fast for the full 72 hours, without missing any insulinomas.

“We are excited to share how a relatively simple adjustment to our protocol allowed us to successfully reduce the burden of fasting on patients and more effectively utilize hospital resources. We hope that this encourages other centers to consider doing the same,” Dr. Lundholm said in an interview.

“These data support a 48-hour fast. The literature supports that’s sufficient to detect 95% of insulinomas. ... But, given our small insulinoma cohort, we are looking forward to learning from other studies,” she added.

Dr. Lundholm presented the late-breaking oral abstract at the annual scientific & clinical congress of the American Association of Clinical Endocrinology.

Asked to comment, session moderator Jenna Sarvaideo, MD, said: “We’re often steeped in tradition. That’s why this abstract and this quality improvement project is so exciting to me because it challenges the history. … and I think it’s ultimately helping patients.”

Dr. Sarvaideo, of Clement J. Zablocki VA Medical Center, Milwaukee, noted that, typically, although the fast will be stopped before 72 hours if the patient develops hypoglycemia, “often they don’t, so we keep going on and on. If we just paid more attention to the beta-hydroxybutyrate, I think that would be practice changing.”

She added that more data would be optimal, given that there were under 100 patients in the study, “but I do think that devising protocols is … very much still at the hands of the endocrinologists. I think that this work could make groups reevaluate their protocol and change it, maybe even with a small dataset and then move on from there and see what they see.”

Indeed, Dr. Lundholm pointed out that some institutions, such as the Mayo Clinic, already include 6-hour BHB measurements (along with glucose and insulin) in their protocols.

“For any institution that already draws regular BHB levels like this, it would be very easy to implement a new stopping criterion without adding any additional costs,” she said in an interview.
 

All insulinomas became apparent in less than 48 hours

The first report to look at the value of testing BHB at regular intervals was published by the Mayo Clinic in 2005 after they noticed patients without insulinoma were complaining of ketosis symptoms such as foul breath and digestive problems toward the end of the fast.

However, although BHB testing is used today as part of the evaluation, it’s typically only drawn at the start of the protocol and again at the time of hypoglycemia or at the end of 72 hours because more frequent values hadn’t been thought to be useful for guiding clinical management, Dr. Lundholm explained. 

Between January 2018 and June 2020, Dr. Lundholm and colleagues followed 34 Cleveland Clinic patients who completed the usual 72-hour fast protocol. Overall, 71% were female, and 26% had undergone prior bariatric surgery procedures. Eleven (32%) developed hypoglycemia and stopped fasting. The other 23 (68%) fasted for the full 72 hours.

Dr. Lundholm and colleagues determined that the fast could have ended earlier in 35% of patients based on an elevated BHB without missing any insulinomas.

And so, in June 2020 the group revised their protocol to include the BHB ≥ 2.7mmol/L stopping criterion. Of the 30 patients evaluated from June 2020 to January 2023, 87% were female and 17% had undergone a bariatric procedure.

Here, 15 (50%) reached a BHB ≥ 2.7mmol/L and ended their fast at an average of 43.8 hours. Another seven (23%) ended the fast after developing hypoglycemia. Just eight patients (27%) fasted for the full 72 hours.

Overall, this resulted in approximately 376 fewer cumulative hours of inpatient admission than if patients had fasted for the full time.

Of the 64 patients who have completed the fasting protocol since 2018, seven (11%) who did have an insulinoma developed hypoglycemia within 48 hours and with a BHB < 2.7 mmol/L (median, 0.15).
 

Advantages: cost, adherence

A day in a general medicine bed at Cleveland Clinic was quoted as costing $2,420, based on publicly available information as of Jan. 1, 2023. “If half of patients leave 1 day earlier, this equates to about $1,210 per patient in savings from bed costs alone,” Dr. Lundholm told this news organization.  

The revised protocol required an additional two to four blood draws, depending on the length of the fast. “The cost of these extra blood tests varies by lab and by count, but even at its highest does not exceed the amount of savings from bed costs,” she noted.

Patient adherence is another potential benefit of the revised protocol.

“Any study that requires 72 hours of patient cooperation is a challenge, particularly in an uncomfortable position like fasting. When we looked at these adherence numbers, we found that the percentage of patients who prematurely ended their fast decreased from 35% to 17% with the updated protocol,” Dr. Lundholm continued.

“This translates to fewer inconclusive results and fewer readmissions for repeat 72-hour fasting. While this was not our primary outcome, it was another noted benefit of our change,” she said.

Dr. Lundholm and Dr. Sarvaideo have reported no relevant financial relationships.

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

SEATTLE – Use of a new kind of assay – sequential beta-hydroxybutyrate testing – with a cut-off for ruling out insulinoma in patients with hypoglycemia may allow for a shortening of the standard 72-hour fasting time, therefore yielding significant hospital cost savings, new data suggest.

Insulinomas are small, rare types of pancreatic tumors that are benign but secrete excess insulin, leading to hypoglycemia. More than 99% of people with insulinomas develop hypoglycemia within 72 hours, hence, the use of a 72-hour fast to detect these tumors.

But most people who are evaluated for hypoglycemia do not have an insulinoma and fasting in hospital for 3 days is burdensome and costly.  

As part of a quality improvement project, Cleveland Clinic endocrinology fellow Michelle D. Lundholm, MD, and colleagues modified their hospital’s protocol to include measurement of beta-hydroxybutyrate (BHB), a marker of insulin suppression, every 12 hours with a cutoff of ≥ 2.7mmol/L for stopping the fast if hypoglycemia (venous glucose ≤ 45mg/dL) hasn’t occurred. This intervention cut in half the number of patients who needed to fast for the full 72 hours, without missing any insulinomas.

“We are excited to share how a relatively simple adjustment to our protocol allowed us to successfully reduce the burden of fasting on patients and more effectively utilize hospital resources. We hope that this encourages other centers to consider doing the same,” Dr. Lundholm said in an interview.

“These data support a 48-hour fast. The literature supports that’s sufficient to detect 95% of insulinomas. ... But, given our small insulinoma cohort, we are looking forward to learning from other studies,” she added.

Dr. Lundholm presented the late-breaking oral abstract at the annual scientific & clinical congress of the American Association of Clinical Endocrinology.

Asked to comment, session moderator Jenna Sarvaideo, MD, said: “We’re often steeped in tradition. That’s why this abstract and this quality improvement project is so exciting to me because it challenges the history. … and I think it’s ultimately helping patients.”

Dr. Sarvaideo, of Clement J. Zablocki VA Medical Center, Milwaukee, noted that, typically, although the fast will be stopped before 72 hours if the patient develops hypoglycemia, “often they don’t, so we keep going on and on. If we just paid more attention to the beta-hydroxybutyrate, I think that would be practice changing.”

She added that more data would be optimal, given that there were under 100 patients in the study, “but I do think that devising protocols is … very much still at the hands of the endocrinologists. I think that this work could make groups reevaluate their protocol and change it, maybe even with a small dataset and then move on from there and see what they see.”

Indeed, Dr. Lundholm pointed out that some institutions, such as the Mayo Clinic, already include 6-hour BHB measurements (along with glucose and insulin) in their protocols.

“For any institution that already draws regular BHB levels like this, it would be very easy to implement a new stopping criterion without adding any additional costs,” she said in an interview.
 

All insulinomas became apparent in less than 48 hours

The first report to look at the value of testing BHB at regular intervals was published by the Mayo Clinic in 2005 after they noticed patients without insulinoma were complaining of ketosis symptoms such as foul breath and digestive problems toward the end of the fast.

However, although BHB testing is used today as part of the evaluation, it’s typically only drawn at the start of the protocol and again at the time of hypoglycemia or at the end of 72 hours because more frequent values hadn’t been thought to be useful for guiding clinical management, Dr. Lundholm explained. 

Between January 2018 and June 2020, Dr. Lundholm and colleagues followed 34 Cleveland Clinic patients who completed the usual 72-hour fast protocol. Overall, 71% were female, and 26% had undergone prior bariatric surgery procedures. Eleven (32%) developed hypoglycemia and stopped fasting. The other 23 (68%) fasted for the full 72 hours.

Dr. Lundholm and colleagues determined that the fast could have ended earlier in 35% of patients based on an elevated BHB without missing any insulinomas.

And so, in June 2020 the group revised their protocol to include the BHB ≥ 2.7mmol/L stopping criterion. Of the 30 patients evaluated from June 2020 to January 2023, 87% were female and 17% had undergone a bariatric procedure.

Here, 15 (50%) reached a BHB ≥ 2.7mmol/L and ended their fast at an average of 43.8 hours. Another seven (23%) ended the fast after developing hypoglycemia. Just eight patients (27%) fasted for the full 72 hours.

Overall, this resulted in approximately 376 fewer cumulative hours of inpatient admission than if patients had fasted for the full time.

Of the 64 patients who have completed the fasting protocol since 2018, seven (11%) who did have an insulinoma developed hypoglycemia within 48 hours and with a BHB < 2.7 mmol/L (median, 0.15).
 

Advantages: cost, adherence

A day in a general medicine bed at Cleveland Clinic was quoted as costing $2,420, based on publicly available information as of Jan. 1, 2023. “If half of patients leave 1 day earlier, this equates to about $1,210 per patient in savings from bed costs alone,” Dr. Lundholm told this news organization.  

The revised protocol required an additional two to four blood draws, depending on the length of the fast. “The cost of these extra blood tests varies by lab and by count, but even at its highest does not exceed the amount of savings from bed costs,” she noted.

Patient adherence is another potential benefit of the revised protocol.

“Any study that requires 72 hours of patient cooperation is a challenge, particularly in an uncomfortable position like fasting. When we looked at these adherence numbers, we found that the percentage of patients who prematurely ended their fast decreased from 35% to 17% with the updated protocol,” Dr. Lundholm continued.

“This translates to fewer inconclusive results and fewer readmissions for repeat 72-hour fasting. While this was not our primary outcome, it was another noted benefit of our change,” she said.

Dr. Lundholm and Dr. Sarvaideo have reported no relevant financial relationships.

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

The U.S. Preventive Services Task Force (USPSTF) on May 9 released a draft recommendation statement and evidence review that provides critical updates to its breast cancer screening recommendations.

The major change: USPSTF proposed reducing the recommended start age for routine screening mammograms from age 50 to age 40. The latest recommendation, which carries a B grade, also calls for screening every other year and sets a cutoff age of 74.

The task force’s A and B ratings indicate strong confidence in the evidence for benefit, meaning that clinicians should encourage their patients to get these services as appropriate.

The influential federal advisory panel last updated these recommendations in 2016. At the time, USPSTF recommended routine screening mammograms starting at age 50, and gave a C grade to starting before that.

In the 2016 recommendations, “we felt a woman could start screening in her 40s depending on how she feels about the harms and benefits in an individualized personal decision,” USPSTF member John Wong, MD, chief of clinical decision making and a primary care physician at Tufts Medical Center in Boston, said in an interview. “In this draft recommendation, we now recommend that all women get screened starting at age 40.”

Two major factors prompted the change, explained Dr. Wong. One is that more women are being diagnosed with breast cancer in their 40s. The other is that a growing body of evidence showing that Black women get breast cancer younger, are more likely to die of breast cancer, and would benefit from earlier screening.

“It is now clear that screening every other year starting at age 40 has the potential to save about 20% more lives among all women and there is even greater potential benefit for Black women, who are much more likely to die from breast cancer,” Dr. Wong said.

The American Cancer Society (ACS) called the draft recommendations a “significant positive change,” while noting that the task force recommendations only apply to women at average risk for breast cancer.

The American College of Radiology (ACR) already recommends yearly mammograms for average risk women starting at age 40. Its latest guidelines on mammography call for women at higher-than-average risk for breast cancer to undergo a risk assessment by age 25 to determine if screening before age 40 is needed.

When asked about the differing views, Debra Monticciolo, MD, division chief for breast imaging at Massachusetts General Hospital, said annual screenings that follow ACR recommendations would save more lives than the every-other-year approach backed by the task force. Dr. Monticciolo also highlighted that the available scientific evidence supports earlier assessment as well as augmented and earlier-than-age-40 screening of many women – particularly Black women.

“These evidence-based updates should spur more-informed doctor–patient conversations and help providers save more lives,” Dr. Monticciolo said in a press release.
 

Insurance access

Typically, upgrading a USPSTF recommendation from C to B leads to better access and insurance coverage for patients. The Affordable Care Act (ACA) of 2010 requires insurers to cover the cost of services that get A and B recommendations from the USPSTF without charging copays – a mandate intended to promote greater use for highly regarded services.

But Congress created a special workaround that effectively makes the ACA mandate apply to the 2002 task force recommendations on mammography. In those recommendations, the task force gave a B grade to screening mammograms every 1 or 2 years starting at age 40 without an age limit. 

Federal lawmakers have sought to provide copay-free access to mammograms for this entire population even when the USPSTF recommendations in 2009 and 2016 gave a C grade to routine screening for women under 50.

Still, “it is important to note that our recommendation is based solely on the science of what works to prevent breast cancer and it is not a recommendation for or against insurance coverage,” the task force acknowledged when unveiling the new draft update. “Coverage decisions involve considerations beyond the evidence about clinical benefit, and in the end, these decisions are the responsibility of payors, regulators, and legislators.”
 

Uncertainties persist

The new draft recommendations also highlight the persistent gaps in knowledge about the uses of mammography, despite years of widespread use of this screening tool.

The updated draft recommendations emphasize the lack of sufficient evidence to address major areas of concern related to screening and treating Black women, older women, women with dense breasts, and those with ductal carcinoma in situ (DCIS).

The task force called for more research addressing the underlying causes of elevated breast cancer mortality rates among Black women.

The USPSTF also issued an ‘I’ statement for providing women with dense breasts additional screening with breast ultrasound or MRI and for screening women older than 75 for breast cancer. Such statements indicate that the available evidence is lacking, poor quality, or conflicting, and thus the USPSTF can’t assess the benefits and harms or make a recommendation for or against providing the preventive service.

“Nearly half of all women have dense breasts, which increases their risk for breast cancer and means that mammograms may not work as well for them. We need to know more about whether and how additional screening might help women with dense breasts stay healthy,” the task force explained.

The task force also called for more research on approaches to reduce the risk for overdiagnosis and overtreatment for breast lesions, such as DCIS, which are identified through screening.

One analysis – the COMET study – is currently underway to assess whether women could be spared surgery for DCIS and opt for watchful waiting instead.

“If we can find that monitoring them carefully, either with or without some sort of endocrine therapy, is just as effective in keeping patients free of invasive cancer as surgery, then I think we could help to de-escalate treatment for this very low-risk group of patients,” Shelley Hwang, MD, MPH, principal investigator of the COMET study, told this news organization in December.

The task force will accept comments from the public on this draft update through June 5.

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

The U.S. Preventive Services Task Force (USPSTF) on May 9 released a draft recommendation statement and evidence review that provides critical updates to its breast cancer screening recommendations.

The major change: USPSTF proposed reducing the recommended start age for routine screening mammograms from age 50 to age 40. The latest recommendation, which carries a B grade, also calls for screening every other year and sets a cutoff age of 74.

The task force’s A and B ratings indicate strong confidence in the evidence for benefit, meaning that clinicians should encourage their patients to get these services as appropriate.

The influential federal advisory panel last updated these recommendations in 2016. At the time, USPSTF recommended routine screening mammograms starting at age 50, and gave a C grade to starting before that.

In the 2016 recommendations, “we felt a woman could start screening in her 40s depending on how she feels about the harms and benefits in an individualized personal decision,” USPSTF member John Wong, MD, chief of clinical decision making and a primary care physician at Tufts Medical Center in Boston, said in an interview. “In this draft recommendation, we now recommend that all women get screened starting at age 40.”

Two major factors prompted the change, explained Dr. Wong. One is that more women are being diagnosed with breast cancer in their 40s. The other is that a growing body of evidence showing that Black women get breast cancer younger, are more likely to die of breast cancer, and would benefit from earlier screening.

“It is now clear that screening every other year starting at age 40 has the potential to save about 20% more lives among all women and there is even greater potential benefit for Black women, who are much more likely to die from breast cancer,” Dr. Wong said.

The American Cancer Society (ACS) called the draft recommendations a “significant positive change,” while noting that the task force recommendations only apply to women at average risk for breast cancer.

The American College of Radiology (ACR) already recommends yearly mammograms for average risk women starting at age 40. Its latest guidelines on mammography call for women at higher-than-average risk for breast cancer to undergo a risk assessment by age 25 to determine if screening before age 40 is needed.

When asked about the differing views, Debra Monticciolo, MD, division chief for breast imaging at Massachusetts General Hospital, said annual screenings that follow ACR recommendations would save more lives than the every-other-year approach backed by the task force. Dr. Monticciolo also highlighted that the available scientific evidence supports earlier assessment as well as augmented and earlier-than-age-40 screening of many women – particularly Black women.

“These evidence-based updates should spur more-informed doctor–patient conversations and help providers save more lives,” Dr. Monticciolo said in a press release.
 

Insurance access

Typically, upgrading a USPSTF recommendation from C to B leads to better access and insurance coverage for patients. The Affordable Care Act (ACA) of 2010 requires insurers to cover the cost of services that get A and B recommendations from the USPSTF without charging copays – a mandate intended to promote greater use for highly regarded services.

But Congress created a special workaround that effectively makes the ACA mandate apply to the 2002 task force recommendations on mammography. In those recommendations, the task force gave a B grade to screening mammograms every 1 or 2 years starting at age 40 without an age limit. 

Federal lawmakers have sought to provide copay-free access to mammograms for this entire population even when the USPSTF recommendations in 2009 and 2016 gave a C grade to routine screening for women under 50.

Still, “it is important to note that our recommendation is based solely on the science of what works to prevent breast cancer and it is not a recommendation for or against insurance coverage,” the task force acknowledged when unveiling the new draft update. “Coverage decisions involve considerations beyond the evidence about clinical benefit, and in the end, these decisions are the responsibility of payors, regulators, and legislators.”
 

Uncertainties persist

The new draft recommendations also highlight the persistent gaps in knowledge about the uses of mammography, despite years of widespread use of this screening tool.

The updated draft recommendations emphasize the lack of sufficient evidence to address major areas of concern related to screening and treating Black women, older women, women with dense breasts, and those with ductal carcinoma in situ (DCIS).

The task force called for more research addressing the underlying causes of elevated breast cancer mortality rates among Black women.

The USPSTF also issued an ‘I’ statement for providing women with dense breasts additional screening with breast ultrasound or MRI and for screening women older than 75 for breast cancer. Such statements indicate that the available evidence is lacking, poor quality, or conflicting, and thus the USPSTF can’t assess the benefits and harms or make a recommendation for or against providing the preventive service.

“Nearly half of all women have dense breasts, which increases their risk for breast cancer and means that mammograms may not work as well for them. We need to know more about whether and how additional screening might help women with dense breasts stay healthy,” the task force explained.

The task force also called for more research on approaches to reduce the risk for overdiagnosis and overtreatment for breast lesions, such as DCIS, which are identified through screening.

One analysis – the COMET study – is currently underway to assess whether women could be spared surgery for DCIS and opt for watchful waiting instead.

“If we can find that monitoring them carefully, either with or without some sort of endocrine therapy, is just as effective in keeping patients free of invasive cancer as surgery, then I think we could help to de-escalate treatment for this very low-risk group of patients,” Shelley Hwang, MD, MPH, principal investigator of the COMET study, told this news organization in December.

The task force will accept comments from the public on this draft update through June 5.

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

The U.S. Preventive Services Task Force (USPSTF) on May 9 released a draft recommendation statement and evidence review that provides critical updates to its breast cancer screening recommendations.

The major change: USPSTF proposed reducing the recommended start age for routine screening mammograms from age 50 to age 40. The latest recommendation, which carries a B grade, also calls for screening every other year and sets a cutoff age of 74.

The task force’s A and B ratings indicate strong confidence in the evidence for benefit, meaning that clinicians should encourage their patients to get these services as appropriate.

The influential federal advisory panel last updated these recommendations in 2016. At the time, USPSTF recommended routine screening mammograms starting at age 50, and gave a C grade to starting before that.

In the 2016 recommendations, “we felt a woman could start screening in her 40s depending on how she feels about the harms and benefits in an individualized personal decision,” USPSTF member John Wong, MD, chief of clinical decision making and a primary care physician at Tufts Medical Center in Boston, said in an interview. “In this draft recommendation, we now recommend that all women get screened starting at age 40.”

Two major factors prompted the change, explained Dr. Wong. One is that more women are being diagnosed with breast cancer in their 40s. The other is that a growing body of evidence showing that Black women get breast cancer younger, are more likely to die of breast cancer, and would benefit from earlier screening.

“It is now clear that screening every other year starting at age 40 has the potential to save about 20% more lives among all women and there is even greater potential benefit for Black women, who are much more likely to die from breast cancer,” Dr. Wong said.

The American Cancer Society (ACS) called the draft recommendations a “significant positive change,” while noting that the task force recommendations only apply to women at average risk for breast cancer.

The American College of Radiology (ACR) already recommends yearly mammograms for average risk women starting at age 40. Its latest guidelines on mammography call for women at higher-than-average risk for breast cancer to undergo a risk assessment by age 25 to determine if screening before age 40 is needed.

When asked about the differing views, Debra Monticciolo, MD, division chief for breast imaging at Massachusetts General Hospital, said annual screenings that follow ACR recommendations would save more lives than the every-other-year approach backed by the task force. Dr. Monticciolo also highlighted that the available scientific evidence supports earlier assessment as well as augmented and earlier-than-age-40 screening of many women – particularly Black women.

“These evidence-based updates should spur more-informed doctor–patient conversations and help providers save more lives,” Dr. Monticciolo said in a press release.
 

Insurance access

Typically, upgrading a USPSTF recommendation from C to B leads to better access and insurance coverage for patients. The Affordable Care Act (ACA) of 2010 requires insurers to cover the cost of services that get A and B recommendations from the USPSTF without charging copays – a mandate intended to promote greater use for highly regarded services.

But Congress created a special workaround that effectively makes the ACA mandate apply to the 2002 task force recommendations on mammography. In those recommendations, the task force gave a B grade to screening mammograms every 1 or 2 years starting at age 40 without an age limit. 

Federal lawmakers have sought to provide copay-free access to mammograms for this entire population even when the USPSTF recommendations in 2009 and 2016 gave a C grade to routine screening for women under 50.

Still, “it is important to note that our recommendation is based solely on the science of what works to prevent breast cancer and it is not a recommendation for or against insurance coverage,” the task force acknowledged when unveiling the new draft update. “Coverage decisions involve considerations beyond the evidence about clinical benefit, and in the end, these decisions are the responsibility of payors, regulators, and legislators.”
 

Uncertainties persist

The new draft recommendations also highlight the persistent gaps in knowledge about the uses of mammography, despite years of widespread use of this screening tool.

The updated draft recommendations emphasize the lack of sufficient evidence to address major areas of concern related to screening and treating Black women, older women, women with dense breasts, and those with ductal carcinoma in situ (DCIS).

The task force called for more research addressing the underlying causes of elevated breast cancer mortality rates among Black women.

The USPSTF also issued an ‘I’ statement for providing women with dense breasts additional screening with breast ultrasound or MRI and for screening women older than 75 for breast cancer. Such statements indicate that the available evidence is lacking, poor quality, or conflicting, and thus the USPSTF can’t assess the benefits and harms or make a recommendation for or against providing the preventive service.

“Nearly half of all women have dense breasts, which increases their risk for breast cancer and means that mammograms may not work as well for them. We need to know more about whether and how additional screening might help women with dense breasts stay healthy,” the task force explained.

The task force also called for more research on approaches to reduce the risk for overdiagnosis and overtreatment for breast lesions, such as DCIS, which are identified through screening.

One analysis – the COMET study – is currently underway to assess whether women could be spared surgery for DCIS and opt for watchful waiting instead.

“If we can find that monitoring them carefully, either with or without some sort of endocrine therapy, is just as effective in keeping patients free of invasive cancer as surgery, then I think we could help to de-escalate treatment for this very low-risk group of patients,” Shelley Hwang, MD, MPH, principal investigator of the COMET study, told this news organization in December.

The task force will accept comments from the public on this draft update through June 5.

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

The Food and Drug Administration has expanded the indication of dapagliflozin (Farxiga, AstraZeneca) to include treatment of heart failure across the full spectrum of left ventricular ejection fraction (LVEF) – including HF with mildly reduced ejection fraction (HFmrEF) and with preserved ejection fraction (HFpEF).

The sodium-glucose cotransporter 2 (SGLT2) inhibitor was previously approved in the United States for adults with heart failure with reduced ejection fraction (HFrEF).

The expanded indication is based on data from the phase 3 DELIVER trial, which showed clear clinical benefits of the SGLT2 inhibitor for patients with HF regardless of left ventricular function.

In the trial, which included more than 6,200 patients, dapagliflozin led to a statistically significant and clinically meaningful early reduction in the primary composite endpoint of cardiovascular (CV) death or worsening HF for patients with HFmrEF or HFpEFF.

In addition, results of a pooled analysis of the DAPA-HF and DELIVER phase 3 trials showed a consistent benefit from dapagliflozin treatment in significantly reducing the combined endpoint of CV death or HF hospitalization across the range of LVEF.

The European Commission expanded the indication for dapagliflozin (Forxiga) to include HF across the full spectrum of LVEF in February.

The SGLT2 inhibitor is also approved for use by patients with chronic kidney disease. It was first approved in 2014 to improve glycemic control for patients with diabetes mellitus.

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

The Food and Drug Administration has expanded the indication of dapagliflozin (Farxiga, AstraZeneca) to include treatment of heart failure across the full spectrum of left ventricular ejection fraction (LVEF) – including HF with mildly reduced ejection fraction (HFmrEF) and with preserved ejection fraction (HFpEF).

The sodium-glucose cotransporter 2 (SGLT2) inhibitor was previously approved in the United States for adults with heart failure with reduced ejection fraction (HFrEF).

The expanded indication is based on data from the phase 3 DELIVER trial, which showed clear clinical benefits of the SGLT2 inhibitor for patients with HF regardless of left ventricular function.

In the trial, which included more than 6,200 patients, dapagliflozin led to a statistically significant and clinically meaningful early reduction in the primary composite endpoint of cardiovascular (CV) death or worsening HF for patients with HFmrEF or HFpEFF.

In addition, results of a pooled analysis of the DAPA-HF and DELIVER phase 3 trials showed a consistent benefit from dapagliflozin treatment in significantly reducing the combined endpoint of CV death or HF hospitalization across the range of LVEF.

The European Commission expanded the indication for dapagliflozin (Forxiga) to include HF across the full spectrum of LVEF in February.

The SGLT2 inhibitor is also approved for use by patients with chronic kidney disease. It was first approved in 2014 to improve glycemic control for patients with diabetes mellitus.

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

The Food and Drug Administration has expanded the indication of dapagliflozin (Farxiga, AstraZeneca) to include treatment of heart failure across the full spectrum of left ventricular ejection fraction (LVEF) – including HF with mildly reduced ejection fraction (HFmrEF) and with preserved ejection fraction (HFpEF).

The sodium-glucose cotransporter 2 (SGLT2) inhibitor was previously approved in the United States for adults with heart failure with reduced ejection fraction (HFrEF).

The expanded indication is based on data from the phase 3 DELIVER trial, which showed clear clinical benefits of the SGLT2 inhibitor for patients with HF regardless of left ventricular function.

In the trial, which included more than 6,200 patients, dapagliflozin led to a statistically significant and clinically meaningful early reduction in the primary composite endpoint of cardiovascular (CV) death or worsening HF for patients with HFmrEF or HFpEFF.

In addition, results of a pooled analysis of the DAPA-HF and DELIVER phase 3 trials showed a consistent benefit from dapagliflozin treatment in significantly reducing the combined endpoint of CV death or HF hospitalization across the range of LVEF.

The European Commission expanded the indication for dapagliflozin (Forxiga) to include HF across the full spectrum of LVEF in February.

The SGLT2 inhibitor is also approved for use by patients with chronic kidney disease. It was first approved in 2014 to improve glycemic control for patients with diabetes mellitus.

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