Commentary

Later this month, the U.S. Supreme Court is anticipated to announce its decision in Kennedy vs. Braidwood Management, a case that could significantly impact the no-cost coverage of preventive healthcare services under the Patient Protection and Affordable Care Act (ACA). At the center of the case is whether the structure of the U.S. Preventive Services Task Force (USPSTF) – an independent body convened by the federal government that makes recommendations for preventive services that nearly all private insurances must cover without cost sharing under provisions of the ACA (specifically, Grade A and B recommendations) – violates the Appointments Clause of the U.S. Constitution. This clause states that “officers of the United States” may only be appointed by the president with the Senate’s approval.

The case, initiated in 2022 by a self-insured, Christian-owned business, specifically targeted the coverage of pre-exposure prophylaxis (PrEP) for preventing HIV in high-risk individuals. However, the decision could broadly affect the coverage of other preventive services, including colorectal cancer screening tests. In June 2024, the 5th Circuit Court of Appeals upheld a district court’s ruling that the ACA’s requirement to cover without cost-sharing services recommended by USPSTF is unconstitutional, paving the way for the current Supreme Court showdown.

The consequences of this ruling could be significant. If the Court rules in favor of Braidwood, private health insurers would no longer be required to cover, without cost-sharing, preventive services recommended by USPSTF after March 2010 when the ACA was enacted. This would likely reverse the progress we have made in increasing colorectal cancer screening rates by reducing financial barriers to care. Interestingly, despite a new administration, the federal government continues to advocate for upholding the law, asserting that USPSTF members are “inferior officers” such that the Secretary of Health and Human Services can dismiss individual members and oversee or veto the Task Force’s recommendations at will, potentially threatening scientific independence. Though it’s often challenging to predict the Supreme Court’s final decision, the tone of questioning during oral arguments in April hinted at a possible win for the ACA and preventive care. Stay tuned, as the decision to be released later this month has seismic clinical implications.

Megan A. Adams, MD, JD, MSc

Editor in Chief

Later this month, the U.S. Supreme Court is anticipated to announce its decision in Kennedy vs. Braidwood Management, a case that could significantly impact the no-cost coverage of preventive healthcare services under the Patient Protection and Affordable Care Act (ACA). At the center of the case is whether the structure of the U.S. Preventive Services Task Force (USPSTF) – an independent body convened by the federal government that makes recommendations for preventive services that nearly all private insurances must cover without cost sharing under provisions of the ACA (specifically, Grade A and B recommendations) – violates the Appointments Clause of the U.S. Constitution. This clause states that “officers of the United States” may only be appointed by the president with the Senate’s approval.

The case, initiated in 2022 by a self-insured, Christian-owned business, specifically targeted the coverage of pre-exposure prophylaxis (PrEP) for preventing HIV in high-risk individuals. However, the decision could broadly affect the coverage of other preventive services, including colorectal cancer screening tests. In June 2024, the 5th Circuit Court of Appeals upheld a district court’s ruling that the ACA’s requirement to cover without cost-sharing services recommended by USPSTF is unconstitutional, paving the way for the current Supreme Court showdown.

The consequences of this ruling could be significant. If the Court rules in favor of Braidwood, private health insurers would no longer be required to cover, without cost-sharing, preventive services recommended by USPSTF after March 2010 when the ACA was enacted. This would likely reverse the progress we have made in increasing colorectal cancer screening rates by reducing financial barriers to care. Interestingly, despite a new administration, the federal government continues to advocate for upholding the law, asserting that USPSTF members are “inferior officers” such that the Secretary of Health and Human Services can dismiss individual members and oversee or veto the Task Force’s recommendations at will, potentially threatening scientific independence. Though it’s often challenging to predict the Supreme Court’s final decision, the tone of questioning during oral arguments in April hinted at a possible win for the ACA and preventive care. Stay tuned, as the decision to be released later this month has seismic clinical implications.

Megan A. Adams, MD, JD, MSc

Editor in Chief

Later this month, the U.S. Supreme Court is anticipated to announce its decision in Kennedy vs. Braidwood Management, a case that could significantly impact the no-cost coverage of preventive healthcare services under the Patient Protection and Affordable Care Act (ACA). At the center of the case is whether the structure of the U.S. Preventive Services Task Force (USPSTF) – an independent body convened by the federal government that makes recommendations for preventive services that nearly all private insurances must cover without cost sharing under provisions of the ACA (specifically, Grade A and B recommendations) – violates the Appointments Clause of the U.S. Constitution. This clause states that “officers of the United States” may only be appointed by the president with the Senate’s approval.

The case, initiated in 2022 by a self-insured, Christian-owned business, specifically targeted the coverage of pre-exposure prophylaxis (PrEP) for preventing HIV in high-risk individuals. However, the decision could broadly affect the coverage of other preventive services, including colorectal cancer screening tests. In June 2024, the 5th Circuit Court of Appeals upheld a district court’s ruling that the ACA’s requirement to cover without cost-sharing services recommended by USPSTF is unconstitutional, paving the way for the current Supreme Court showdown.

The consequences of this ruling could be significant. If the Court rules in favor of Braidwood, private health insurers would no longer be required to cover, without cost-sharing, preventive services recommended by USPSTF after March 2010 when the ACA was enacted. This would likely reverse the progress we have made in increasing colorectal cancer screening rates by reducing financial barriers to care. Interestingly, despite a new administration, the federal government continues to advocate for upholding the law, asserting that USPSTF members are “inferior officers” such that the Secretary of Health and Human Services can dismiss individual members and oversee or veto the Task Force’s recommendations at will, potentially threatening scientific independence. Though it’s often challenging to predict the Supreme Court’s final decision, the tone of questioning during oral arguments in April hinted at a possible win for the ACA and preventive care. Stay tuned, as the decision to be released later this month has seismic clinical implications.

Megan A. Adams, MD, JD, MSc

Editor in Chief

Artificial intelligence (AI) is rapidly evolving, with large language models (LLMs) marking a significant milestone in processing and generating human-like responses to natural language prompts. However, this advancement only signals the beginning of a more profound transformation in AI capabilities. The development of AI agents represents a new paradigm at the forefront of this evolution.

BACKGROUND

AI agents represent a leap forward from traditional LLM applications. While definitions may vary slightly among technology developers, the core concept remains: these agents are autonomous software entities designed to interact with their environment, make independent decisions, and execute tasks based on predefined goals.^1-3 What sets AI agents apart is their combination of sophisticated components within structured architectures. At their core, AI agents incorporate an LLM for response generation, which is augmented by a suite of tools to optimize workflow and complete tasks, memory capabilities for personalized interactions, and autonomous reasoning. This combination allows AI agents to plan, create subtasks, gather information, and learn iteratively from their own experiences or other AI agents.

The true potential of this technology becomes apparent when multiple AI agents collaborate within multiagent AI systems. This concept introduces a new level of flexibility and capability in tackling complex tasks. Autogen, CrewAI, and LangChain offer various agent network configurations, including hierarchical, sequential, conditional, or even parallel task execution.^4-6 This adaptability opens up a world of possibilities across various industries, but perhaps nowhere is the potential impact more exciting and profound than in health care.

AI agents in health care present an opportunity to revolutionize patient care, streamline administrative processes, and support complex clinical decision-making. This review examines 3 scenarios that illustrate the impact of AI agents in health care: a hypothetical sepsis management system, chronic disease management, and hospital patient flow optimization. This article will provide a detailed look at the technical implementation challenges, including the integration with existing health care IT systems, data privacy considerations, and the crucial role of explainable AI in maintaining trust and transparency.

It is challenging to implement AI agents in health care. Concerns include ensuring data quality and mitigating bias, seamlessly integrating these systems into existing clinical workflows, and navigating the complex ethical considerations that arise when deploying autonomous systems in health care. The integration with Internet of Things (IoT) devices for real-time patient data monitoring and the development of more sophisticated natural language interfaces to enhance future human-AI collaboration.

The adoption of AI agents in health care is only beginning, and it promises to be transformative. As AI continues to evolve, a comprehensive understanding of its applications, limitations, and ethical considerations is essential. This report provides a comprehensive overview of the current state, potential applications, and future directions of AI agents in health care, offering insights valuable to researchers, clinicians, and policymakers.

MultiAgent AI architecture

Sepsis Management

Despite advancements in broad-spectrum antibiotics, imaging, and life support systems, mortality rates associated with sepsis remain high. The complexity of optimizing care in clinical settings has hindered progress in managing sepsis. Previous attempts to develop predictive sepsis models have proven challenging.⁷ This report proposes a multiagent AI system designed to enhance comprehensive patient monitoring and care through coordinated AI-driven interventions.

Data Collection and Integration Agent. Powered by a controlled vocabulary to specify all data, the primary function for the data collection and integration agent is to clean, transform, and organize patient data from structured and unstructured sources. This agent prepares succinct summaries of consultant notes and formats data for human and machine consumption. All numerical data are presented graphically, including relevant historical data trends. The agent also digitally captures all orders in a structured format using a specified controlled vocabulary. This structured data feed supports the output of other agents, including documentation, treatment planning, and risk stratification, while also supplying the data structures for future training.

Diagnostic Agent. Critical illness is characterized by multiple abnormalities across a wide array of tests, ranging from plain chest X-ray, computed tomography (CT), blood cell composition, plasma chemistry, and microscopic evaluation of specimens. Additionally, life support parameters provide insights into disease severity and can inform management recommendations. These data offer a wide array of visual and numerical data to be used as input for computation, recommendation, and further training. For example, to evaluate fluid overload on chest X-rays or tissue histopathology slides, an AI agent can leverage deep learning models such as convolutional neural networks and vision transformers to analyze images like radiographs and histopathology slides.^8,9 Recurrent neural networks or transformer models process sequential data like time-series vital signs. The agent also implements ensemble methods that combine multiple machine learning algorithms to enhance diagnostic accuracy.

Risk Stratification Agent. This assesses severity and predicts potential outcomes. Morbidity and mortality risks are calculated using an established scoring system and individualized based on the history of other agents’ conditional patients. These are presented graphically, with major risk factors highlighted for explainability. 

Treatment Recommendation Agent. Using a reinforcement learning framework supplemented by up-to-date clinical guidelines, this system leverages historical data structured with standardized vocabulary to analyze patients with similar clinical features. Training is also conducted on the patient’s physiological data. All recommendations are presented via a dedicated user interface in a readable format, along with recommendations for editable, orderable items, references, and full-text snippets from previous research. Stop rules end computing if confidence in recommendations is too broad or no clear pathway can be computed with certainty, prompting human mitigation.

Resource Management Agent. This agent coordinates hospital resources using constraint programming techniques for optimal resource allocation, uses queueing theory models to predict and manage patient flow, and implements genetic algorithms for complex scheduling problems.^10,11

Monitoring and Alert Agent. By tracking patients’ progress and alerting staff to changes, this agent uses anomaly detection algorithms to identify unusual patterns in patient data and implement time-series forecasting models, such as autoregressive integrated moving average and prophet, to predict future patient states. The agent also uses stream-processing techniques for real-time data analysis.^12,13

Documentation and Reporting Agent. This agent maintains comprehensive medical records and generates reports. It employs advanced natural language processing techniques for automated report generation, uses advanced LLMs fine-tuned on medical corpora for narrative creation, and implements information-retrieval techniques to efficiently query patient records.

CLINICAL CASE STUDIES

To illustrate the functionality of a multiagent system, this report examines its application for managing sepsis. The data collection and integration agent continuously aggregates patient data from various sources, normalizing and timestamping it for consistent processing. The diagnostic agent analyzes this integrated data in real time, applying sepsis criteria and utilizing a deep learning model trained on a large sepsis dataset to detect subtle patterns.

The risk stratification agent calculates severity scores, such as the Sepsis-related Organ Failure Assessment (SOFA), quick SOFA (qSOFA), and Acute Physiology and Chronic Health Evaluation II, upon detecting a possible sepsis case.¹⁴ It predicts the likelihood of specific outcomes and estimates the potential trajectory of the patient’s condition for the next 24 to 48 hours. Based on this assessment, the treatment recommendation agent suggests an initial treatment plan, including appropriate antibiotics, fluid resuscitation protocols, and vasopressor recommendations, recommendations when indicated.

Concurrently, the resource management agent checks the availability of necessary resources and prioritizes allocation based on the severity. The monitoring agent tracks the patient’s response to interventions in real time, alerting the care team to any concerning changes or lack of expected improvement. Throughout this process, the documentation agent ensures that all actions, responses, and outcomes are meticulously recorded in a structured format and generates real-time updates for the patient’s electronic health record (EHR) and preparing summary reports for handoffs between care teams.

Administrative Workflow Support

Modern health care operations are resource-intensive, requiring coordination of advanced imaging, procedures, laboratory testing, and professional consultations.¹⁵ AI-powered health care administrative workflow systems are revolutionizing how medical facilities coordinate patient care. For patients with chronic cough, these systems seamlessly integrate scheduling, imaging, diagnostics, and follow-up care into a cohesive process that reduces administrative burden while improving patient outcomes. Through an intuitive interface and automated assistance, health care practitioners (HCPs) can track patient progress from initial consultation through diagnosis and treatment.

The process begins when an HCP enters a patient into the system, which triggers an automated CT scan scheduling system. The system considers factors like urgency, facility availability, and patient preferences to suggest optimal appointment times. Once imaging is complete, AI agents analyze the radiology reports, extract key findings, and generate structured summaries that highlight critical information such as “mild bronchial wall thickening with patchy ground-glass opacities” or “findings consistent with chronic bronchitis.”

Based on these findings, the system automatically generates evidence-based recommendations for follow-up care, such as pulmonology consultations or follow-up imaging in 3 months. These recommendations are presented to the ordering clinician, along with suggested appointment slots for specialist consultations. The system then manages the coordination of multiple appointments, ensuring each step in the patient’s care plan is properly sequenced and scheduled.

The entire process is monitored through a comprehensive dashboard that provides real-time updates on patient status, appointment schedules, and clinical recommendations. HCPs can track which patients require immediate attention, view upcoming appointments, and monitor the progress of ongoing care plans.

Multiagent AI Operation Optimization

Hospitals are complex entities that must function at different scales and respond in an agile, timely manner at all hours, deploying staff at various positions.¹⁶ A system of AI agents can receive signals from sensors monitoring foot traffic in the emergency department and trauma unit, as well as the availability of operating room staff, equipment, and intensive care unit beds. Smart sensors enable this monitoring through IoT networks. These networks benefit from advances in adaptive and consensus networking algorithms, along with recent advances in bioengineering and biocomputing.¹⁷

For example, in the case of imaging for suspected abdominal obstruction, an AI agent tasked with scheduling CTs could time the patient’s arrival based on acuity. Another AI agent could alert staff transporting the patient to the CT appointment, with the next location contingent on a clinical decision to proceed to the operating room. Yet another AI agent could summarize radiology interpretations and alert the surgery and anesthesia teams to a potential case, while others could notify operating room staff of equipment needs or reserve a bed. In this paradigm, AI agents facilitate more precise and timely communication between multiple staff members.

TECHNICAL IMPLEMENTATION

Large Language Models

Each agent uses a different LLM optimized for its specific task. For example, the diagnostic agent uses an LLM pretrained on a large corpus of biomedical literature and fine-tuned on a dataset of confirmed sepsis cases and their presentations.¹⁸ It implements few-shot learning techniques to adapt to rare or atypical presentations. The treatment recommendation agent also uses an LLM, employing a retrieval-augmented generation approach to access the latest clinical guidelines during inference. The documentation agent uses another advanced language model, fine-tuned on a large corpus of high-quality medical documentation, implementing controlled text generation techniques and utilizing a separate smaller model for real-time error checking and correction.

Interagent Quality Control

Agents learn from their own experience and the experience of other agents. They are equipped with user-defined rule-based and model-based systems for quality assurance, with clear stopping rules for human involvement and mitigation.

Sophisticated quality control measures bolster the system’s reliability, including ensemble techniques for result comparison, redundancy for critical tasks, and automatic human review for disagreements above a certain threshold. Each agent provides a calibrated confidence score with its output, used to weigh inputs in downstream tasks and trigger additional checks for low-confidence outputs.

A dedicated quality control agent monitors output from all agents, employing both supervised and unsupervised anomaly detection techniques. Feedback loops allow agents to evaluate the quality and utility of information received from other agents. The system implements a multiarmed bandit approach to dynamically adjust the influence of different agents based on their performance and periodically retrains agent models using federated learning techniques.¹⁹

Electronic Health Record Integration

Seamless EHR integration is crucial for practical implementation. The system has secure application programming interface access to various EHR platforms, implements OAuth 2.0 for authentication, and use HTTPS with perfect forward secrecy for all communications.²⁰ It works with HL7 FHIR to ensure interoperability and uses SNOMED CT for clinical terminology to ensure semantic interoperability across different EHRs.^21,22

The system implements a multilevel approval system for write-backs to EHRs, with different thresholds based on the information’s criticality. It uses digital signatures to ensure the integrity and nonrepudiation of AI-generated entries and implements blockchain technology to create an immutable and distributed ledger of all AI system actions.²³

Decision Transparency

To ensure transparency in decision-making processes, the system applies techniques (eg, local interpretable model-agnostic explanations and Shapley additive explanations) to provide insights into agent decision-making processes.^24-26 It provides customized visualizations for different stakeholders and allows users to explore alternative decision paths through what-if scenario modeling.²⁷

The system provides calibrated confidence indicators for each recommendation or decision, implementing a novel confidence calibration agent that continuously monitors and adjusts confidence scores based on observed outcomes.

Continuous Learning and Adaptation

The system employs several techniques to remain current with evolving medical knowledge. Federated learning includes information from diverse datasets across multiple institutions without compromising patient privacy.²⁸ A/B testing is used to safely deploy and compare new agent versions in controlled settings, implementing multiarmed bandit algorithms to efficiently explore new models while minimizing potential negative impacts. Human-in-the-loop learning and active learning techniques are used to incorporate feedback from HCPs and efficiently solicit expert input on the most informative data.²⁹

CLINICAL IMPLICATIONS

The implementation of multiagent AI systems in health care has several potential benefits: enhanced diagnostic accuracy, personalized treatment, improved efficiency, continuous monitoring, and resource optimization. A recent review of AI sepsis predictive models exhibited superior results to standard clinical scoring methods like qSOFA.³⁰ In oncology, such systems can result in more tailored treatments, enhancing outcomes.³¹ The implementation of an ambient dictation system can improve workflow and prevent HCP burnout.³²

ETHICAL CONSIDERATIONS AND AI OVERSIGHT

Integrating AI agents into health care raises significant ethical considerations that must be carefully addressed to ensure equitable and effective care delivery. One primary concern involves cultural and linguistic competency, as AI systems may struggle with cultural nuances, idioms, and context-specific communication patterns. This becomes particularly challenging in regions with diverse ethnic populations or immigrant communities, where medical terminology may not have direct translations and cultural beliefs significantly influence health care decisions. AI systems also may inherit and amplify existing biases in health care delivery, whether through HCP bias reflected in training data, patient bias affecting acceptance of AI-assisted care, or demographic underrepresentation during system development.

AI agents present unique opportunities for improving health care access and outcomes through community engagement, though such initiatives require thoughtful implementation. Predictive analytics can identify high-risk individuals within communities who may benefit from preventive care, while analysis of social determinants of health can enable more targeted interventions. However, these capabilities must be balanced with privacy concerns and the risk of surveillance, particularly in communities that distrust health care institutions. The potential for AI to bridge health care gaps must be weighed against the need to maintain cultural sensitivity and community trust.

The governance and oversight of health care AI systems requires a multistakeholder approach with clear lines of responsibility and accountability. This includes involvement from government health care agencies, professional medical associations, ethics boards, and independent auditors, all working together to establish and enforce standards while monitoring system performance and addressing potential biases. Health care organizations must maintain transparent policies about AI use, implement regular monitoring and evaluation protocols, and establish precise mechanisms for patient feedback and grievance resolution. Ongoing assessment and adjustment of these systems, informed by community feedback and outcomes data, will be crucial for their ethical implementation, ensuring that AI agents complement, rather than replace, human judgment and cultural sensitivity.

FUTURE DIRECTIONS

Despite the potential benefits, implementing multiagent AI systems in health care faces significant challenges that require careful consideration. Beyond the fundamental issues such as data quality and bias mitigation, health care organizations struggle with fragmented systems, inconsistent data formats, and varying quality. Technical infrastructure requirements are substantial, particularly in rural or underserved areas that lack robust networks and cybersecurity. HCPs already face significant cognitive load and time pressures, making integrating AI agents into existing workflows particularly challenging. There is also the critical issue of transparency and interpretability, as health care decisions require clear reasoning and accountability that many black-box AI systems struggle to provide.

The legal landscape introduces another layer of complexity, particularly regarding liability, consent, and privacy questions. When AI agents contribute to medical decisions, establishing clear lines of responsibility becomes crucial. There are also serious concerns about algorithmic fairness and the potential for AI systems to perpetuate or amplify existing inequities. The cost of implementation remains a significant barrier, requiring substantial investment in technology, training, and ongoing maintenance while ensuring resources are not diverted from direct patient care. Moreover, HCPs may resist adoption due to concerns about job security, loss of autonomy, or skepticism about AI capabilities while paradoxically facing risks of overreliance on AI systems that could lead to the degradation of human clinical skills.

Addressing these challenges requires a multifaceted approach that combines technical solutions with organizational and policy changes. Health care organizations must implement rigorous data validation processes and interoperability standards while developing hybrid models that balance sophisticated AI capabilities with interpretable techniques. Extensive research and iterative design processes, with direct input from HCPs, are essential for successful integration. Establishing independent ethics boards to oversee system development and deployment, conducting multicenter randomized controlled trials, and creating clear regulatory frameworks will ensure safe and effective implementation. Success will ultimately depend on ongoing collaboration between technology developers, HCPs, policymakers, and patients, maintaining a steady focus on improving patient care and outcomes while carefully navigating the complex challenges of AI integration in health care.^33-35

As multiagent AI systems in health care evolve, several exciting directions emerge. These include the integration of IoT and wearable devices, the development of more sophisticated natural language interfaces, and applying these systems to predictive maintenance of medical equipment.

CONCLUSIONS

The advent of multiagent AI systems in health care represents a paradigm shift in the approach to patient care, clinical decision making, and health care management. While these systems offer immense potential to transform health care delivery, their development and implementation must be guided by rigorous scientific validation, ethical considerations, and a patient-centered approach. The ultimate goal remains clear: harnessing the power of AI to improve patient outcomes, enhance the efficiency of health care delivery, and ultimately advance the health and well-being of patients.

Artificial intelligence (AI) is rapidly evolving, with large language models (LLMs) marking a significant milestone in processing and generating human-like responses to natural language prompts. However, this advancement only signals the beginning of a more profound transformation in AI capabilities. The development of AI agents represents a new paradigm at the forefront of this evolution.

BACKGROUND

AI agents represent a leap forward from traditional LLM applications. While definitions may vary slightly among technology developers, the core concept remains: these agents are autonomous software entities designed to interact with their environment, make independent decisions, and execute tasks based on predefined goals.^1-3 What sets AI agents apart is their combination of sophisticated components within structured architectures. At their core, AI agents incorporate an LLM for response generation, which is augmented by a suite of tools to optimize workflow and complete tasks, memory capabilities for personalized interactions, and autonomous reasoning. This combination allows AI agents to plan, create subtasks, gather information, and learn iteratively from their own experiences or other AI agents.

The true potential of this technology becomes apparent when multiple AI agents collaborate within multiagent AI systems. This concept introduces a new level of flexibility and capability in tackling complex tasks. Autogen, CrewAI, and LangChain offer various agent network configurations, including hierarchical, sequential, conditional, or even parallel task execution.^4-6 This adaptability opens up a world of possibilities across various industries, but perhaps nowhere is the potential impact more exciting and profound than in health care.

AI agents in health care present an opportunity to revolutionize patient care, streamline administrative processes, and support complex clinical decision-making. This review examines 3 scenarios that illustrate the impact of AI agents in health care: a hypothetical sepsis management system, chronic disease management, and hospital patient flow optimization. This article will provide a detailed look at the technical implementation challenges, including the integration with existing health care IT systems, data privacy considerations, and the crucial role of explainable AI in maintaining trust and transparency.

It is challenging to implement AI agents in health care. Concerns include ensuring data quality and mitigating bias, seamlessly integrating these systems into existing clinical workflows, and navigating the complex ethical considerations that arise when deploying autonomous systems in health care. The integration with Internet of Things (IoT) devices for real-time patient data monitoring and the development of more sophisticated natural language interfaces to enhance future human-AI collaboration.

The adoption of AI agents in health care is only beginning, and it promises to be transformative. As AI continues to evolve, a comprehensive understanding of its applications, limitations, and ethical considerations is essential. This report provides a comprehensive overview of the current state, potential applications, and future directions of AI agents in health care, offering insights valuable to researchers, clinicians, and policymakers.

MultiAgent AI architecture

Sepsis Management

Despite advancements in broad-spectrum antibiotics, imaging, and life support systems, mortality rates associated with sepsis remain high. The complexity of optimizing care in clinical settings has hindered progress in managing sepsis. Previous attempts to develop predictive sepsis models have proven challenging.⁷ This report proposes a multiagent AI system designed to enhance comprehensive patient monitoring and care through coordinated AI-driven interventions.

Data Collection and Integration Agent. Powered by a controlled vocabulary to specify all data, the primary function for the data collection and integration agent is to clean, transform, and organize patient data from structured and unstructured sources. This agent prepares succinct summaries of consultant notes and formats data for human and machine consumption. All numerical data are presented graphically, including relevant historical data trends. The agent also digitally captures all orders in a structured format using a specified controlled vocabulary. This structured data feed supports the output of other agents, including documentation, treatment planning, and risk stratification, while also supplying the data structures for future training.

Diagnostic Agent. Critical illness is characterized by multiple abnormalities across a wide array of tests, ranging from plain chest X-ray, computed tomography (CT), blood cell composition, plasma chemistry, and microscopic evaluation of specimens. Additionally, life support parameters provide insights into disease severity and can inform management recommendations. These data offer a wide array of visual and numerical data to be used as input for computation, recommendation, and further training. For example, to evaluate fluid overload on chest X-rays or tissue histopathology slides, an AI agent can leverage deep learning models such as convolutional neural networks and vision transformers to analyze images like radiographs and histopathology slides.^8,9 Recurrent neural networks or transformer models process sequential data like time-series vital signs. The agent also implements ensemble methods that combine multiple machine learning algorithms to enhance diagnostic accuracy.

Risk Stratification Agent. This assesses severity and predicts potential outcomes. Morbidity and mortality risks are calculated using an established scoring system and individualized based on the history of other agents’ conditional patients. These are presented graphically, with major risk factors highlighted for explainability. 

Treatment Recommendation Agent. Using a reinforcement learning framework supplemented by up-to-date clinical guidelines, this system leverages historical data structured with standardized vocabulary to analyze patients with similar clinical features. Training is also conducted on the patient’s physiological data. All recommendations are presented via a dedicated user interface in a readable format, along with recommendations for editable, orderable items, references, and full-text snippets from previous research. Stop rules end computing if confidence in recommendations is too broad or no clear pathway can be computed with certainty, prompting human mitigation.

Resource Management Agent. This agent coordinates hospital resources using constraint programming techniques for optimal resource allocation, uses queueing theory models to predict and manage patient flow, and implements genetic algorithms for complex scheduling problems.^10,11

Monitoring and Alert Agent. By tracking patients’ progress and alerting staff to changes, this agent uses anomaly detection algorithms to identify unusual patterns in patient data and implement time-series forecasting models, such as autoregressive integrated moving average and prophet, to predict future patient states. The agent also uses stream-processing techniques for real-time data analysis.^12,13

Documentation and Reporting Agent. This agent maintains comprehensive medical records and generates reports. It employs advanced natural language processing techniques for automated report generation, uses advanced LLMs fine-tuned on medical corpora for narrative creation, and implements information-retrieval techniques to efficiently query patient records.

CLINICAL CASE STUDIES

To illustrate the functionality of a multiagent system, this report examines its application for managing sepsis. The data collection and integration agent continuously aggregates patient data from various sources, normalizing and timestamping it for consistent processing. The diagnostic agent analyzes this integrated data in real time, applying sepsis criteria and utilizing a deep learning model trained on a large sepsis dataset to detect subtle patterns.

The risk stratification agent calculates severity scores, such as the Sepsis-related Organ Failure Assessment (SOFA), quick SOFA (qSOFA), and Acute Physiology and Chronic Health Evaluation II, upon detecting a possible sepsis case.¹⁴ It predicts the likelihood of specific outcomes and estimates the potential trajectory of the patient’s condition for the next 24 to 48 hours. Based on this assessment, the treatment recommendation agent suggests an initial treatment plan, including appropriate antibiotics, fluid resuscitation protocols, and vasopressor recommendations, recommendations when indicated.

Concurrently, the resource management agent checks the availability of necessary resources and prioritizes allocation based on the severity. The monitoring agent tracks the patient’s response to interventions in real time, alerting the care team to any concerning changes or lack of expected improvement. Throughout this process, the documentation agent ensures that all actions, responses, and outcomes are meticulously recorded in a structured format and generates real-time updates for the patient’s electronic health record (EHR) and preparing summary reports for handoffs between care teams.

Administrative Workflow Support

Modern health care operations are resource-intensive, requiring coordination of advanced imaging, procedures, laboratory testing, and professional consultations.¹⁵ AI-powered health care administrative workflow systems are revolutionizing how medical facilities coordinate patient care. For patients with chronic cough, these systems seamlessly integrate scheduling, imaging, diagnostics, and follow-up care into a cohesive process that reduces administrative burden while improving patient outcomes. Through an intuitive interface and automated assistance, health care practitioners (HCPs) can track patient progress from initial consultation through diagnosis and treatment.

The process begins when an HCP enters a patient into the system, which triggers an automated CT scan scheduling system. The system considers factors like urgency, facility availability, and patient preferences to suggest optimal appointment times. Once imaging is complete, AI agents analyze the radiology reports, extract key findings, and generate structured summaries that highlight critical information such as “mild bronchial wall thickening with patchy ground-glass opacities” or “findings consistent with chronic bronchitis.”

Based on these findings, the system automatically generates evidence-based recommendations for follow-up care, such as pulmonology consultations or follow-up imaging in 3 months. These recommendations are presented to the ordering clinician, along with suggested appointment slots for specialist consultations. The system then manages the coordination of multiple appointments, ensuring each step in the patient’s care plan is properly sequenced and scheduled.

The entire process is monitored through a comprehensive dashboard that provides real-time updates on patient status, appointment schedules, and clinical recommendations. HCPs can track which patients require immediate attention, view upcoming appointments, and monitor the progress of ongoing care plans.

Multiagent AI Operation Optimization

Hospitals are complex entities that must function at different scales and respond in an agile, timely manner at all hours, deploying staff at various positions.¹⁶ A system of AI agents can receive signals from sensors monitoring foot traffic in the emergency department and trauma unit, as well as the availability of operating room staff, equipment, and intensive care unit beds. Smart sensors enable this monitoring through IoT networks. These networks benefit from advances in adaptive and consensus networking algorithms, along with recent advances in bioengineering and biocomputing.¹⁷

For example, in the case of imaging for suspected abdominal obstruction, an AI agent tasked with scheduling CTs could time the patient’s arrival based on acuity. Another AI agent could alert staff transporting the patient to the CT appointment, with the next location contingent on a clinical decision to proceed to the operating room. Yet another AI agent could summarize radiology interpretations and alert the surgery and anesthesia teams to a potential case, while others could notify operating room staff of equipment needs or reserve a bed. In this paradigm, AI agents facilitate more precise and timely communication between multiple staff members.

TECHNICAL IMPLEMENTATION

Large Language Models

Each agent uses a different LLM optimized for its specific task. For example, the diagnostic agent uses an LLM pretrained on a large corpus of biomedical literature and fine-tuned on a dataset of confirmed sepsis cases and their presentations.¹⁸ It implements few-shot learning techniques to adapt to rare or atypical presentations. The treatment recommendation agent also uses an LLM, employing a retrieval-augmented generation approach to access the latest clinical guidelines during inference. The documentation agent uses another advanced language model, fine-tuned on a large corpus of high-quality medical documentation, implementing controlled text generation techniques and utilizing a separate smaller model for real-time error checking and correction.

Interagent Quality Control

Agents learn from their own experience and the experience of other agents. They are equipped with user-defined rule-based and model-based systems for quality assurance, with clear stopping rules for human involvement and mitigation.

Sophisticated quality control measures bolster the system’s reliability, including ensemble techniques for result comparison, redundancy for critical tasks, and automatic human review for disagreements above a certain threshold. Each agent provides a calibrated confidence score with its output, used to weigh inputs in downstream tasks and trigger additional checks for low-confidence outputs.

A dedicated quality control agent monitors output from all agents, employing both supervised and unsupervised anomaly detection techniques. Feedback loops allow agents to evaluate the quality and utility of information received from other agents. The system implements a multiarmed bandit approach to dynamically adjust the influence of different agents based on their performance and periodically retrains agent models using federated learning techniques.¹⁹

Electronic Health Record Integration

Seamless EHR integration is crucial for practical implementation. The system has secure application programming interface access to various EHR platforms, implements OAuth 2.0 for authentication, and use HTTPS with perfect forward secrecy for all communications.²⁰ It works with HL7 FHIR to ensure interoperability and uses SNOMED CT for clinical terminology to ensure semantic interoperability across different EHRs.^21,22

The system implements a multilevel approval system for write-backs to EHRs, with different thresholds based on the information’s criticality. It uses digital signatures to ensure the integrity and nonrepudiation of AI-generated entries and implements blockchain technology to create an immutable and distributed ledger of all AI system actions.²³

Decision Transparency

To ensure transparency in decision-making processes, the system applies techniques (eg, local interpretable model-agnostic explanations and Shapley additive explanations) to provide insights into agent decision-making processes.^24-26 It provides customized visualizations for different stakeholders and allows users to explore alternative decision paths through what-if scenario modeling.²⁷

The system provides calibrated confidence indicators for each recommendation or decision, implementing a novel confidence calibration agent that continuously monitors and adjusts confidence scores based on observed outcomes.

Continuous Learning and Adaptation

The system employs several techniques to remain current with evolving medical knowledge. Federated learning includes information from diverse datasets across multiple institutions without compromising patient privacy.²⁸ A/B testing is used to safely deploy and compare new agent versions in controlled settings, implementing multiarmed bandit algorithms to efficiently explore new models while minimizing potential negative impacts. Human-in-the-loop learning and active learning techniques are used to incorporate feedback from HCPs and efficiently solicit expert input on the most informative data.²⁹

CLINICAL IMPLICATIONS

The implementation of multiagent AI systems in health care has several potential benefits: enhanced diagnostic accuracy, personalized treatment, improved efficiency, continuous monitoring, and resource optimization. A recent review of AI sepsis predictive models exhibited superior results to standard clinical scoring methods like qSOFA.³⁰ In oncology, such systems can result in more tailored treatments, enhancing outcomes.³¹ The implementation of an ambient dictation system can improve workflow and prevent HCP burnout.³²

ETHICAL CONSIDERATIONS AND AI OVERSIGHT

Integrating AI agents into health care raises significant ethical considerations that must be carefully addressed to ensure equitable and effective care delivery. One primary concern involves cultural and linguistic competency, as AI systems may struggle with cultural nuances, idioms, and context-specific communication patterns. This becomes particularly challenging in regions with diverse ethnic populations or immigrant communities, where medical terminology may not have direct translations and cultural beliefs significantly influence health care decisions. AI systems also may inherit and amplify existing biases in health care delivery, whether through HCP bias reflected in training data, patient bias affecting acceptance of AI-assisted care, or demographic underrepresentation during system development.

AI agents present unique opportunities for improving health care access and outcomes through community engagement, though such initiatives require thoughtful implementation. Predictive analytics can identify high-risk individuals within communities who may benefit from preventive care, while analysis of social determinants of health can enable more targeted interventions. However, these capabilities must be balanced with privacy concerns and the risk of surveillance, particularly in communities that distrust health care institutions. The potential for AI to bridge health care gaps must be weighed against the need to maintain cultural sensitivity and community trust.

The governance and oversight of health care AI systems requires a multistakeholder approach with clear lines of responsibility and accountability. This includes involvement from government health care agencies, professional medical associations, ethics boards, and independent auditors, all working together to establish and enforce standards while monitoring system performance and addressing potential biases. Health care organizations must maintain transparent policies about AI use, implement regular monitoring and evaluation protocols, and establish precise mechanisms for patient feedback and grievance resolution. Ongoing assessment and adjustment of these systems, informed by community feedback and outcomes data, will be crucial for their ethical implementation, ensuring that AI agents complement, rather than replace, human judgment and cultural sensitivity.

FUTURE DIRECTIONS

Despite the potential benefits, implementing multiagent AI systems in health care faces significant challenges that require careful consideration. Beyond the fundamental issues such as data quality and bias mitigation, health care organizations struggle with fragmented systems, inconsistent data formats, and varying quality. Technical infrastructure requirements are substantial, particularly in rural or underserved areas that lack robust networks and cybersecurity. HCPs already face significant cognitive load and time pressures, making integrating AI agents into existing workflows particularly challenging. There is also the critical issue of transparency and interpretability, as health care decisions require clear reasoning and accountability that many black-box AI systems struggle to provide.

The legal landscape introduces another layer of complexity, particularly regarding liability, consent, and privacy questions. When AI agents contribute to medical decisions, establishing clear lines of responsibility becomes crucial. There are also serious concerns about algorithmic fairness and the potential for AI systems to perpetuate or amplify existing inequities. The cost of implementation remains a significant barrier, requiring substantial investment in technology, training, and ongoing maintenance while ensuring resources are not diverted from direct patient care. Moreover, HCPs may resist adoption due to concerns about job security, loss of autonomy, or skepticism about AI capabilities while paradoxically facing risks of overreliance on AI systems that could lead to the degradation of human clinical skills.

Addressing these challenges requires a multifaceted approach that combines technical solutions with organizational and policy changes. Health care organizations must implement rigorous data validation processes and interoperability standards while developing hybrid models that balance sophisticated AI capabilities with interpretable techniques. Extensive research and iterative design processes, with direct input from HCPs, are essential for successful integration. Establishing independent ethics boards to oversee system development and deployment, conducting multicenter randomized controlled trials, and creating clear regulatory frameworks will ensure safe and effective implementation. Success will ultimately depend on ongoing collaboration between technology developers, HCPs, policymakers, and patients, maintaining a steady focus on improving patient care and outcomes while carefully navigating the complex challenges of AI integration in health care.^33-35

As multiagent AI systems in health care evolve, several exciting directions emerge. These include the integration of IoT and wearable devices, the development of more sophisticated natural language interfaces, and applying these systems to predictive maintenance of medical equipment.

CONCLUSIONS

The advent of multiagent AI systems in health care represents a paradigm shift in the approach to patient care, clinical decision making, and health care management. While these systems offer immense potential to transform health care delivery, their development and implementation must be guided by rigorous scientific validation, ethical considerations, and a patient-centered approach. The ultimate goal remains clear: harnessing the power of AI to improve patient outcomes, enhance the efficiency of health care delivery, and ultimately advance the health and well-being of patients.

Artificial intelligence (AI) is rapidly evolving, with large language models (LLMs) marking a significant milestone in processing and generating human-like responses to natural language prompts. However, this advancement only signals the beginning of a more profound transformation in AI capabilities. The development of AI agents represents a new paradigm at the forefront of this evolution.

BACKGROUND

AI agents represent a leap forward from traditional LLM applications. While definitions may vary slightly among technology developers, the core concept remains: these agents are autonomous software entities designed to interact with their environment, make independent decisions, and execute tasks based on predefined goals.^1-3 What sets AI agents apart is their combination of sophisticated components within structured architectures. At their core, AI agents incorporate an LLM for response generation, which is augmented by a suite of tools to optimize workflow and complete tasks, memory capabilities for personalized interactions, and autonomous reasoning. This combination allows AI agents to plan, create subtasks, gather information, and learn iteratively from their own experiences or other AI agents.

The true potential of this technology becomes apparent when multiple AI agents collaborate within multiagent AI systems. This concept introduces a new level of flexibility and capability in tackling complex tasks. Autogen, CrewAI, and LangChain offer various agent network configurations, including hierarchical, sequential, conditional, or even parallel task execution.^4-6 This adaptability opens up a world of possibilities across various industries, but perhaps nowhere is the potential impact more exciting and profound than in health care.

AI agents in health care present an opportunity to revolutionize patient care, streamline administrative processes, and support complex clinical decision-making. This review examines 3 scenarios that illustrate the impact of AI agents in health care: a hypothetical sepsis management system, chronic disease management, and hospital patient flow optimization. This article will provide a detailed look at the technical implementation challenges, including the integration with existing health care IT systems, data privacy considerations, and the crucial role of explainable AI in maintaining trust and transparency.

It is challenging to implement AI agents in health care. Concerns include ensuring data quality and mitigating bias, seamlessly integrating these systems into existing clinical workflows, and navigating the complex ethical considerations that arise when deploying autonomous systems in health care. The integration with Internet of Things (IoT) devices for real-time patient data monitoring and the development of more sophisticated natural language interfaces to enhance future human-AI collaboration.

The adoption of AI agents in health care is only beginning, and it promises to be transformative. As AI continues to evolve, a comprehensive understanding of its applications, limitations, and ethical considerations is essential. This report provides a comprehensive overview of the current state, potential applications, and future directions of AI agents in health care, offering insights valuable to researchers, clinicians, and policymakers.

MultiAgent AI architecture

Sepsis Management

Despite advancements in broad-spectrum antibiotics, imaging, and life support systems, mortality rates associated with sepsis remain high. The complexity of optimizing care in clinical settings has hindered progress in managing sepsis. Previous attempts to develop predictive sepsis models have proven challenging.⁷ This report proposes a multiagent AI system designed to enhance comprehensive patient monitoring and care through coordinated AI-driven interventions.

Data Collection and Integration Agent. Powered by a controlled vocabulary to specify all data, the primary function for the data collection and integration agent is to clean, transform, and organize patient data from structured and unstructured sources. This agent prepares succinct summaries of consultant notes and formats data for human and machine consumption. All numerical data are presented graphically, including relevant historical data trends. The agent also digitally captures all orders in a structured format using a specified controlled vocabulary. This structured data feed supports the output of other agents, including documentation, treatment planning, and risk stratification, while also supplying the data structures for future training.

Diagnostic Agent. Critical illness is characterized by multiple abnormalities across a wide array of tests, ranging from plain chest X-ray, computed tomography (CT), blood cell composition, plasma chemistry, and microscopic evaluation of specimens. Additionally, life support parameters provide insights into disease severity and can inform management recommendations. These data offer a wide array of visual and numerical data to be used as input for computation, recommendation, and further training. For example, to evaluate fluid overload on chest X-rays or tissue histopathology slides, an AI agent can leverage deep learning models such as convolutional neural networks and vision transformers to analyze images like radiographs and histopathology slides.^8,9 Recurrent neural networks or transformer models process sequential data like time-series vital signs. The agent also implements ensemble methods that combine multiple machine learning algorithms to enhance diagnostic accuracy.

Risk Stratification Agent. This assesses severity and predicts potential outcomes. Morbidity and mortality risks are calculated using an established scoring system and individualized based on the history of other agents’ conditional patients. These are presented graphically, with major risk factors highlighted for explainability. 

Treatment Recommendation Agent. Using a reinforcement learning framework supplemented by up-to-date clinical guidelines, this system leverages historical data structured with standardized vocabulary to analyze patients with similar clinical features. Training is also conducted on the patient’s physiological data. All recommendations are presented via a dedicated user interface in a readable format, along with recommendations for editable, orderable items, references, and full-text snippets from previous research. Stop rules end computing if confidence in recommendations is too broad or no clear pathway can be computed with certainty, prompting human mitigation.

Resource Management Agent. This agent coordinates hospital resources using constraint programming techniques for optimal resource allocation, uses queueing theory models to predict and manage patient flow, and implements genetic algorithms for complex scheduling problems.^10,11

Monitoring and Alert Agent. By tracking patients’ progress and alerting staff to changes, this agent uses anomaly detection algorithms to identify unusual patterns in patient data and implement time-series forecasting models, such as autoregressive integrated moving average and prophet, to predict future patient states. The agent also uses stream-processing techniques for real-time data analysis.^12,13

Documentation and Reporting Agent. This agent maintains comprehensive medical records and generates reports. It employs advanced natural language processing techniques for automated report generation, uses advanced LLMs fine-tuned on medical corpora for narrative creation, and implements information-retrieval techniques to efficiently query patient records.

CLINICAL CASE STUDIES

To illustrate the functionality of a multiagent system, this report examines its application for managing sepsis. The data collection and integration agent continuously aggregates patient data from various sources, normalizing and timestamping it for consistent processing. The diagnostic agent analyzes this integrated data in real time, applying sepsis criteria and utilizing a deep learning model trained on a large sepsis dataset to detect subtle patterns.

The risk stratification agent calculates severity scores, such as the Sepsis-related Organ Failure Assessment (SOFA), quick SOFA (qSOFA), and Acute Physiology and Chronic Health Evaluation II, upon detecting a possible sepsis case.¹⁴ It predicts the likelihood of specific outcomes and estimates the potential trajectory of the patient’s condition for the next 24 to 48 hours. Based on this assessment, the treatment recommendation agent suggests an initial treatment plan, including appropriate antibiotics, fluid resuscitation protocols, and vasopressor recommendations, recommendations when indicated.

Concurrently, the resource management agent checks the availability of necessary resources and prioritizes allocation based on the severity. The monitoring agent tracks the patient’s response to interventions in real time, alerting the care team to any concerning changes or lack of expected improvement. Throughout this process, the documentation agent ensures that all actions, responses, and outcomes are meticulously recorded in a structured format and generates real-time updates for the patient’s electronic health record (EHR) and preparing summary reports for handoffs between care teams.

Administrative Workflow Support

Modern health care operations are resource-intensive, requiring coordination of advanced imaging, procedures, laboratory testing, and professional consultations.¹⁵ AI-powered health care administrative workflow systems are revolutionizing how medical facilities coordinate patient care. For patients with chronic cough, these systems seamlessly integrate scheduling, imaging, diagnostics, and follow-up care into a cohesive process that reduces administrative burden while improving patient outcomes. Through an intuitive interface and automated assistance, health care practitioners (HCPs) can track patient progress from initial consultation through diagnosis and treatment.

The process begins when an HCP enters a patient into the system, which triggers an automated CT scan scheduling system. The system considers factors like urgency, facility availability, and patient preferences to suggest optimal appointment times. Once imaging is complete, AI agents analyze the radiology reports, extract key findings, and generate structured summaries that highlight critical information such as “mild bronchial wall thickening with patchy ground-glass opacities” or “findings consistent with chronic bronchitis.”

Based on these findings, the system automatically generates evidence-based recommendations for follow-up care, such as pulmonology consultations or follow-up imaging in 3 months. These recommendations are presented to the ordering clinician, along with suggested appointment slots for specialist consultations. The system then manages the coordination of multiple appointments, ensuring each step in the patient’s care plan is properly sequenced and scheduled.

The entire process is monitored through a comprehensive dashboard that provides real-time updates on patient status, appointment schedules, and clinical recommendations. HCPs can track which patients require immediate attention, view upcoming appointments, and monitor the progress of ongoing care plans.

Multiagent AI Operation Optimization

Hospitals are complex entities that must function at different scales and respond in an agile, timely manner at all hours, deploying staff at various positions.¹⁶ A system of AI agents can receive signals from sensors monitoring foot traffic in the emergency department and trauma unit, as well as the availability of operating room staff, equipment, and intensive care unit beds. Smart sensors enable this monitoring through IoT networks. These networks benefit from advances in adaptive and consensus networking algorithms, along with recent advances in bioengineering and biocomputing.¹⁷

For example, in the case of imaging for suspected abdominal obstruction, an AI agent tasked with scheduling CTs could time the patient’s arrival based on acuity. Another AI agent could alert staff transporting the patient to the CT appointment, with the next location contingent on a clinical decision to proceed to the operating room. Yet another AI agent could summarize radiology interpretations and alert the surgery and anesthesia teams to a potential case, while others could notify operating room staff of equipment needs or reserve a bed. In this paradigm, AI agents facilitate more precise and timely communication between multiple staff members.

TECHNICAL IMPLEMENTATION

Large Language Models

Each agent uses a different LLM optimized for its specific task. For example, the diagnostic agent uses an LLM pretrained on a large corpus of biomedical literature and fine-tuned on a dataset of confirmed sepsis cases and their presentations.¹⁸ It implements few-shot learning techniques to adapt to rare or atypical presentations. The treatment recommendation agent also uses an LLM, employing a retrieval-augmented generation approach to access the latest clinical guidelines during inference. The documentation agent uses another advanced language model, fine-tuned on a large corpus of high-quality medical documentation, implementing controlled text generation techniques and utilizing a separate smaller model for real-time error checking and correction.

Interagent Quality Control

Agents learn from their own experience and the experience of other agents. They are equipped with user-defined rule-based and model-based systems for quality assurance, with clear stopping rules for human involvement and mitigation.

Sophisticated quality control measures bolster the system’s reliability, including ensemble techniques for result comparison, redundancy for critical tasks, and automatic human review for disagreements above a certain threshold. Each agent provides a calibrated confidence score with its output, used to weigh inputs in downstream tasks and trigger additional checks for low-confidence outputs.

A dedicated quality control agent monitors output from all agents, employing both supervised and unsupervised anomaly detection techniques. Feedback loops allow agents to evaluate the quality and utility of information received from other agents. The system implements a multiarmed bandit approach to dynamically adjust the influence of different agents based on their performance and periodically retrains agent models using federated learning techniques.¹⁹

Electronic Health Record Integration

Seamless EHR integration is crucial for practical implementation. The system has secure application programming interface access to various EHR platforms, implements OAuth 2.0 for authentication, and use HTTPS with perfect forward secrecy for all communications.²⁰ It works with HL7 FHIR to ensure interoperability and uses SNOMED CT for clinical terminology to ensure semantic interoperability across different EHRs.^21,22

The system implements a multilevel approval system for write-backs to EHRs, with different thresholds based on the information’s criticality. It uses digital signatures to ensure the integrity and nonrepudiation of AI-generated entries and implements blockchain technology to create an immutable and distributed ledger of all AI system actions.²³

Decision Transparency

To ensure transparency in decision-making processes, the system applies techniques (eg, local interpretable model-agnostic explanations and Shapley additive explanations) to provide insights into agent decision-making processes.^24-26 It provides customized visualizations for different stakeholders and allows users to explore alternative decision paths through what-if scenario modeling.²⁷

The system provides calibrated confidence indicators for each recommendation or decision, implementing a novel confidence calibration agent that continuously monitors and adjusts confidence scores based on observed outcomes.

Continuous Learning and Adaptation

The system employs several techniques to remain current with evolving medical knowledge. Federated learning includes information from diverse datasets across multiple institutions without compromising patient privacy.²⁸ A/B testing is used to safely deploy and compare new agent versions in controlled settings, implementing multiarmed bandit algorithms to efficiently explore new models while minimizing potential negative impacts. Human-in-the-loop learning and active learning techniques are used to incorporate feedback from HCPs and efficiently solicit expert input on the most informative data.²⁹

CLINICAL IMPLICATIONS

The implementation of multiagent AI systems in health care has several potential benefits: enhanced diagnostic accuracy, personalized treatment, improved efficiency, continuous monitoring, and resource optimization. A recent review of AI sepsis predictive models exhibited superior results to standard clinical scoring methods like qSOFA.³⁰ In oncology, such systems can result in more tailored treatments, enhancing outcomes.³¹ The implementation of an ambient dictation system can improve workflow and prevent HCP burnout.³²

ETHICAL CONSIDERATIONS AND AI OVERSIGHT

Integrating AI agents into health care raises significant ethical considerations that must be carefully addressed to ensure equitable and effective care delivery. One primary concern involves cultural and linguistic competency, as AI systems may struggle with cultural nuances, idioms, and context-specific communication patterns. This becomes particularly challenging in regions with diverse ethnic populations or immigrant communities, where medical terminology may not have direct translations and cultural beliefs significantly influence health care decisions. AI systems also may inherit and amplify existing biases in health care delivery, whether through HCP bias reflected in training data, patient bias affecting acceptance of AI-assisted care, or demographic underrepresentation during system development.

AI agents present unique opportunities for improving health care access and outcomes through community engagement, though such initiatives require thoughtful implementation. Predictive analytics can identify high-risk individuals within communities who may benefit from preventive care, while analysis of social determinants of health can enable more targeted interventions. However, these capabilities must be balanced with privacy concerns and the risk of surveillance, particularly in communities that distrust health care institutions. The potential for AI to bridge health care gaps must be weighed against the need to maintain cultural sensitivity and community trust.

The governance and oversight of health care AI systems requires a multistakeholder approach with clear lines of responsibility and accountability. This includes involvement from government health care agencies, professional medical associations, ethics boards, and independent auditors, all working together to establish and enforce standards while monitoring system performance and addressing potential biases. Health care organizations must maintain transparent policies about AI use, implement regular monitoring and evaluation protocols, and establish precise mechanisms for patient feedback and grievance resolution. Ongoing assessment and adjustment of these systems, informed by community feedback and outcomes data, will be crucial for their ethical implementation, ensuring that AI agents complement, rather than replace, human judgment and cultural sensitivity.

FUTURE DIRECTIONS

Despite the potential benefits, implementing multiagent AI systems in health care faces significant challenges that require careful consideration. Beyond the fundamental issues such as data quality and bias mitigation, health care organizations struggle with fragmented systems, inconsistent data formats, and varying quality. Technical infrastructure requirements are substantial, particularly in rural or underserved areas that lack robust networks and cybersecurity. HCPs already face significant cognitive load and time pressures, making integrating AI agents into existing workflows particularly challenging. There is also the critical issue of transparency and interpretability, as health care decisions require clear reasoning and accountability that many black-box AI systems struggle to provide.

The legal landscape introduces another layer of complexity, particularly regarding liability, consent, and privacy questions. When AI agents contribute to medical decisions, establishing clear lines of responsibility becomes crucial. There are also serious concerns about algorithmic fairness and the potential for AI systems to perpetuate or amplify existing inequities. The cost of implementation remains a significant barrier, requiring substantial investment in technology, training, and ongoing maintenance while ensuring resources are not diverted from direct patient care. Moreover, HCPs may resist adoption due to concerns about job security, loss of autonomy, or skepticism about AI capabilities while paradoxically facing risks of overreliance on AI systems that could lead to the degradation of human clinical skills.

Addressing these challenges requires a multifaceted approach that combines technical solutions with organizational and policy changes. Health care organizations must implement rigorous data validation processes and interoperability standards while developing hybrid models that balance sophisticated AI capabilities with interpretable techniques. Extensive research and iterative design processes, with direct input from HCPs, are essential for successful integration. Establishing independent ethics boards to oversee system development and deployment, conducting multicenter randomized controlled trials, and creating clear regulatory frameworks will ensure safe and effective implementation. Success will ultimately depend on ongoing collaboration between technology developers, HCPs, policymakers, and patients, maintaining a steady focus on improving patient care and outcomes while carefully navigating the complex challenges of AI integration in health care.^33-35

As multiagent AI systems in health care evolve, several exciting directions emerge. These include the integration of IoT and wearable devices, the development of more sophisticated natural language interfaces, and applying these systems to predictive maintenance of medical equipment.

CONCLUSIONS

The advent of multiagent AI systems in health care represents a paradigm shift in the approach to patient care, clinical decision making, and health care management. While these systems offer immense potential to transform health care delivery, their development and implementation must be guided by rigorous scientific validation, ethical considerations, and a patient-centered approach. The ultimate goal remains clear: harnessing the power of AI to improve patient outcomes, enhance the efficiency of health care delivery, and ultimately advance the health and well-being of patients.

Worldwide, it is estimated that up to 1 in 5 individuals will experience a dermatophyte infection (commonly called ringworm or tinea infection) in their lifetime.¹ Historically, dermatophyte infections have been considered relatively minor conditions usually treated with short courses of topical antifungals.² Oral antifungals historically were needed only for patients with nail or hair shaft infections or extensive cutaneous fungal infections, which typically occurred in immunosuppressed patients.² However, the landscape is changing rapidly due to the global emergence of severe dermatophyte infections that frequently are resistant to first-line antifungal medications.^3-5 In this article, we aimed to review the epidemiology of emerging dermatophyte infections and provide dermatologists with information needed for effective diagnosis and management.

Emergence of Trichophyton indotineae

In recent decades, public health officials and dermatologists have noted with concern the spread of the recently emerged dermatophyte species Trichophyton indotineae in South Asia.^3,6 This species (previously known as Trichophyton mentagrophytes genotype VIII) usually is transmitted from person to person, either through direct skin-to-skin contact or by fomites.^4,6 Potential sexual transmission of T indotineae infections also has been reported,⁷ and it is possible that animals may serve as reservoirs for this pathogen, although there are no known reports of direct spread from animals to humans.^8,9 Major outbreaks of T indotineae are ongoing in South Asia, and cases have been documented in 6 continents.^10-12 In the United States, most but not all cases have occurred in immigrants from or recently returned travelers to South Asia.^6,13 The emergence and spread of T indotineae is hypothesized to be promoted by the misuse and overuse of topical antifungal products, particularly those containing combinations of potent corticosteroids with other antimicrobial drugs.^14,15

Cutaneous manifestations of T indotineae infections tend to cover large body surface areas, recur frequently, and pose substantial treatment challenges.^6,13,16 Several clinical presentations have been documented, including erythematous, scaly concentric plaques; papulosquamous lesions; pustular forms; and corticosteroid-modified disease (Figure 1).^6,16 Affected patients seldom are immunocompromised and often have a history of multiple failed courses of topical or oral antifungals, including oral terbinafine.¹³ Many also have been prescribed topical corticosteroids or have used over-the-counter topical corticosteroids, which worsen the rash.¹⁷

Direct microscopy with potassium hydroxide could be used to confirm the diagnosis of dermatophyte infection, but it does not distinguish T indotineae from other dermatophyte species.^2,6 Importantly, culture-based testing usually will misidentify T indotineae as other Trichophyton species such as the more common T mentagrophytes or Trichophyton interdigitale. Definitive identification of T indotineae requires advanced molecular techniques that are available only at select laboratories.⁶ Unfortunately, availability of such testing is limited (Table), and results may take several weeks; therefore, it is suggested that dermatologists who suspect T indotineae infections based on the patient’s history and clinical presentation begin antifungal treatment after confirmation of dermatophyte infection but not wait for definitive confirmation of the causative organism.¹⁶

Itraconazole is considered the first-line therapy for T indotineae infection, as terbinafine usually is ineffective due to mutations in the squalene epoxidase gene.¹⁶ Dermatologists should be aware that itraconazole is available in different formulations that can affect absorption. The oral solution has greater bioavailability and should be taken on an empty stomach, whereas the capsules are required to be taken with food for effective absorption; the capsules also should be taken with an acidic beverage such as orange juice. Dermatologists should carefully assess for drug-drug interactions when prescribing itraconazole, given its extensive interaction profile with numerous other medications. Patients may require treatment with itraconazole (100 mg/d or 200 mg/d) for a minimum of 6 to 8 weeks until complete clearance has been achieved and ideally a negative potassium hydroxide preparation of skin scrapings has been obtained. A longer treatment period (eg, ≥3 months) frequently is needed, and relapses are common.^6,16,18 Regular follow-up is needed to monitor for infection clearance and recurrences. It is important to note that cases of itraconazole resistance have been reported, although this currently appears to be uncommon.^19,20

Other Emerging Dermatophytes to Watch

Trichophyton rubrum is the most common cause of dermatophyte infections among humans,²¹ and cases of terbinafine-resistant T rubrum infections have been reported increasingly in the United States and Canada.^5,22-24 Onychomycosis caused by terbinafine-resistant T rubrum has been documented, and patients may have infections that do not respond to terbinafine given at the standard dose and duration.^22,23 Case reports have indicated successful treatment using itraconazole 200 mg/d and posaconazole 300 mg/d.^5,23

Trichophyton mentagrophytes genotype VII (TMVII) is an emerging dermatophyte that recently has been reported as a cause of sexually transmitted dermatophyte infections in Europe and the United States primarily affecting men who have sex with men.^25-27 Patients may present with pruritic, annular, scaly patches and plaques involving the trunk, groin, genital region, or face (Figure 2). Although closely related to T indotineae, TMVII differs in that it more often affects the genital region, generally is susceptible to terbinafine, and in the United States and Europe usually is not related to travel or immigration involving South Asia.²⁶ Although TMVII has not been associated with antifungal resistance, awareness among dermatologists is important because patients may experience inflamed, painful, and persistent rashes that can lead to secondary bacterial infection or scarring, and physicians might mistake it for mimics including eczema or psoriasis.^25,26

Importance of Judicious Antifungal Use

Optimizing the use of antifungals is critical to improving patient outcomes and preserving available treatment options.^28,29 A retrospective analysis of commercial health insurance data estimated that topical antifungal prescriptions were potentially unnecessary for more than half of the more than 560,000 patients who were prescribed these medications in 2023. In this study, it also was observed that only 16% of patients prescribed a topical antifungal had received diagnostic testing, with low rates across specialties.³⁰ This is concerning because even among board-certified dermatologists, incorrect diagnosis of suspected fungal skin infections can occur; in one survey-based study of board-certified dermatologists who were presented with dermatomycosis images, respondents categorized cases with greater than 75% accuracy in only 31% (4/13) of instances.³¹ Clotrimazole-betamethasone is among the most commonly prescribed topical antifungals in the United States,^14,32 and 2 recent retrospective analyses highlighted that the majority of patients prescribed this medication did not receive any fungal diagnostic testing.^33,34

Final Thoughts

In an era of emerging antifungal-resistant dermatophyte infections, it is important for dermatologists to educate nondermatologists about the importance of using diagnostic testing for suspected dermatophyte infections.^14,28 Dermatologists also can educate nondermatologist colleagues on the importance of avoiding the use of topical combination antifungal/corticosteroid medications and referring for dermatologic evaluation when diagnoses are uncertain.^33,34 Strategies for education by dermatologists could include giving workshops, creating educational materials, and fostering open communication about optimal treatment practices and referral parameters for suspected dermatophyte infections.

Worldwide, it is estimated that up to 1 in 5 individuals will experience a dermatophyte infection (commonly called ringworm or tinea infection) in their lifetime.¹ Historically, dermatophyte infections have been considered relatively minor conditions usually treated with short courses of topical antifungals.² Oral antifungals historically were needed only for patients with nail or hair shaft infections or extensive cutaneous fungal infections, which typically occurred in immunosuppressed patients.² However, the landscape is changing rapidly due to the global emergence of severe dermatophyte infections that frequently are resistant to first-line antifungal medications.^3-5 In this article, we aimed to review the epidemiology of emerging dermatophyte infections and provide dermatologists with information needed for effective diagnosis and management.

Emergence of Trichophyton indotineae

In recent decades, public health officials and dermatologists have noted with concern the spread of the recently emerged dermatophyte species Trichophyton indotineae in South Asia.^3,6 This species (previously known as Trichophyton mentagrophytes genotype VIII) usually is transmitted from person to person, either through direct skin-to-skin contact or by fomites.^4,6 Potential sexual transmission of T indotineae infections also has been reported,⁷ and it is possible that animals may serve as reservoirs for this pathogen, although there are no known reports of direct spread from animals to humans.^8,9 Major outbreaks of T indotineae are ongoing in South Asia, and cases have been documented in 6 continents.^10-12 In the United States, most but not all cases have occurred in immigrants from or recently returned travelers to South Asia.^6,13 The emergence and spread of T indotineae is hypothesized to be promoted by the misuse and overuse of topical antifungal products, particularly those containing combinations of potent corticosteroids with other antimicrobial drugs.^14,15

Cutaneous manifestations of T indotineae infections tend to cover large body surface areas, recur frequently, and pose substantial treatment challenges.^6,13,16 Several clinical presentations have been documented, including erythematous, scaly concentric plaques; papulosquamous lesions; pustular forms; and corticosteroid-modified disease (Figure 1).^6,16 Affected patients seldom are immunocompromised and often have a history of multiple failed courses of topical or oral antifungals, including oral terbinafine.¹³ Many also have been prescribed topical corticosteroids or have used over-the-counter topical corticosteroids, which worsen the rash.¹⁷

Direct microscopy with potassium hydroxide could be used to confirm the diagnosis of dermatophyte infection, but it does not distinguish T indotineae from other dermatophyte species.^2,6 Importantly, culture-based testing usually will misidentify T indotineae as other Trichophyton species such as the more common T mentagrophytes or Trichophyton interdigitale. Definitive identification of T indotineae requires advanced molecular techniques that are available only at select laboratories.⁶ Unfortunately, availability of such testing is limited (Table), and results may take several weeks; therefore, it is suggested that dermatologists who suspect T indotineae infections based on the patient’s history and clinical presentation begin antifungal treatment after confirmation of dermatophyte infection but not wait for definitive confirmation of the causative organism.¹⁶

Itraconazole is considered the first-line therapy for T indotineae infection, as terbinafine usually is ineffective due to mutations in the squalene epoxidase gene.¹⁶ Dermatologists should be aware that itraconazole is available in different formulations that can affect absorption. The oral solution has greater bioavailability and should be taken on an empty stomach, whereas the capsules are required to be taken with food for effective absorption; the capsules also should be taken with an acidic beverage such as orange juice. Dermatologists should carefully assess for drug-drug interactions when prescribing itraconazole, given its extensive interaction profile with numerous other medications. Patients may require treatment with itraconazole (100 mg/d or 200 mg/d) for a minimum of 6 to 8 weeks until complete clearance has been achieved and ideally a negative potassium hydroxide preparation of skin scrapings has been obtained. A longer treatment period (eg, ≥3 months) frequently is needed, and relapses are common.^6,16,18 Regular follow-up is needed to monitor for infection clearance and recurrences. It is important to note that cases of itraconazole resistance have been reported, although this currently appears to be uncommon.^19,20

Other Emerging Dermatophytes to Watch

Trichophyton rubrum is the most common cause of dermatophyte infections among humans,²¹ and cases of terbinafine-resistant T rubrum infections have been reported increasingly in the United States and Canada.^5,22-24 Onychomycosis caused by terbinafine-resistant T rubrum has been documented, and patients may have infections that do not respond to terbinafine given at the standard dose and duration.^22,23 Case reports have indicated successful treatment using itraconazole 200 mg/d and posaconazole 300 mg/d.^5,23

Trichophyton mentagrophytes genotype VII (TMVII) is an emerging dermatophyte that recently has been reported as a cause of sexually transmitted dermatophyte infections in Europe and the United States primarily affecting men who have sex with men.^25-27 Patients may present with pruritic, annular, scaly patches and plaques involving the trunk, groin, genital region, or face (Figure 2). Although closely related to T indotineae, TMVII differs in that it more often affects the genital region, generally is susceptible to terbinafine, and in the United States and Europe usually is not related to travel or immigration involving South Asia.²⁶ Although TMVII has not been associated with antifungal resistance, awareness among dermatologists is important because patients may experience inflamed, painful, and persistent rashes that can lead to secondary bacterial infection or scarring, and physicians might mistake it for mimics including eczema or psoriasis.^25,26

Importance of Judicious Antifungal Use

Optimizing the use of antifungals is critical to improving patient outcomes and preserving available treatment options.^28,29 A retrospective analysis of commercial health insurance data estimated that topical antifungal prescriptions were potentially unnecessary for more than half of the more than 560,000 patients who were prescribed these medications in 2023. In this study, it also was observed that only 16% of patients prescribed a topical antifungal had received diagnostic testing, with low rates across specialties.³⁰ This is concerning because even among board-certified dermatologists, incorrect diagnosis of suspected fungal skin infections can occur; in one survey-based study of board-certified dermatologists who were presented with dermatomycosis images, respondents categorized cases with greater than 75% accuracy in only 31% (4/13) of instances.³¹ Clotrimazole-betamethasone is among the most commonly prescribed topical antifungals in the United States,^14,32 and 2 recent retrospective analyses highlighted that the majority of patients prescribed this medication did not receive any fungal diagnostic testing.^33,34

Final Thoughts

In an era of emerging antifungal-resistant dermatophyte infections, it is important for dermatologists to educate nondermatologists about the importance of using diagnostic testing for suspected dermatophyte infections.^14,28 Dermatologists also can educate nondermatologist colleagues on the importance of avoiding the use of topical combination antifungal/corticosteroid medications and referring for dermatologic evaluation when diagnoses are uncertain.^33,34 Strategies for education by dermatologists could include giving workshops, creating educational materials, and fostering open communication about optimal treatment practices and referral parameters for suspected dermatophyte infections.

Worldwide, it is estimated that up to 1 in 5 individuals will experience a dermatophyte infection (commonly called ringworm or tinea infection) in their lifetime.¹ Historically, dermatophyte infections have been considered relatively minor conditions usually treated with short courses of topical antifungals.² Oral antifungals historically were needed only for patients with nail or hair shaft infections or extensive cutaneous fungal infections, which typically occurred in immunosuppressed patients.² However, the landscape is changing rapidly due to the global emergence of severe dermatophyte infections that frequently are resistant to first-line antifungal medications.^3-5 In this article, we aimed to review the epidemiology of emerging dermatophyte infections and provide dermatologists with information needed for effective diagnosis and management.

Emergence of Trichophyton indotineae

In recent decades, public health officials and dermatologists have noted with concern the spread of the recently emerged dermatophyte species Trichophyton indotineae in South Asia.^3,6 This species (previously known as Trichophyton mentagrophytes genotype VIII) usually is transmitted from person to person, either through direct skin-to-skin contact or by fomites.^4,6 Potential sexual transmission of T indotineae infections also has been reported,⁷ and it is possible that animals may serve as reservoirs for this pathogen, although there are no known reports of direct spread from animals to humans.^8,9 Major outbreaks of T indotineae are ongoing in South Asia, and cases have been documented in 6 continents.^10-12 In the United States, most but not all cases have occurred in immigrants from or recently returned travelers to South Asia.^6,13 The emergence and spread of T indotineae is hypothesized to be promoted by the misuse and overuse of topical antifungal products, particularly those containing combinations of potent corticosteroids with other antimicrobial drugs.^14,15

Cutaneous manifestations of T indotineae infections tend to cover large body surface areas, recur frequently, and pose substantial treatment challenges.^6,13,16 Several clinical presentations have been documented, including erythematous, scaly concentric plaques; papulosquamous lesions; pustular forms; and corticosteroid-modified disease (Figure 1).^6,16 Affected patients seldom are immunocompromised and often have a history of multiple failed courses of topical or oral antifungals, including oral terbinafine.¹³ Many also have been prescribed topical corticosteroids or have used over-the-counter topical corticosteroids, which worsen the rash.¹⁷

Direct microscopy with potassium hydroxide could be used to confirm the diagnosis of dermatophyte infection, but it does not distinguish T indotineae from other dermatophyte species.^2,6 Importantly, culture-based testing usually will misidentify T indotineae as other Trichophyton species such as the more common T mentagrophytes or Trichophyton interdigitale. Definitive identification of T indotineae requires advanced molecular techniques that are available only at select laboratories.⁶ Unfortunately, availability of such testing is limited (Table), and results may take several weeks; therefore, it is suggested that dermatologists who suspect T indotineae infections based on the patient’s history and clinical presentation begin antifungal treatment after confirmation of dermatophyte infection but not wait for definitive confirmation of the causative organism.¹⁶

Itraconazole is considered the first-line therapy for T indotineae infection, as terbinafine usually is ineffective due to mutations in the squalene epoxidase gene.¹⁶ Dermatologists should be aware that itraconazole is available in different formulations that can affect absorption. The oral solution has greater bioavailability and should be taken on an empty stomach, whereas the capsules are required to be taken with food for effective absorption; the capsules also should be taken with an acidic beverage such as orange juice. Dermatologists should carefully assess for drug-drug interactions when prescribing itraconazole, given its extensive interaction profile with numerous other medications. Patients may require treatment with itraconazole (100 mg/d or 200 mg/d) for a minimum of 6 to 8 weeks until complete clearance has been achieved and ideally a negative potassium hydroxide preparation of skin scrapings has been obtained. A longer treatment period (eg, ≥3 months) frequently is needed, and relapses are common.^6,16,18 Regular follow-up is needed to monitor for infection clearance and recurrences. It is important to note that cases of itraconazole resistance have been reported, although this currently appears to be uncommon.^19,20

Other Emerging Dermatophytes to Watch

Trichophyton rubrum is the most common cause of dermatophyte infections among humans,²¹ and cases of terbinafine-resistant T rubrum infections have been reported increasingly in the United States and Canada.^5,22-24 Onychomycosis caused by terbinafine-resistant T rubrum has been documented, and patients may have infections that do not respond to terbinafine given at the standard dose and duration.^22,23 Case reports have indicated successful treatment using itraconazole 200 mg/d and posaconazole 300 mg/d.^5,23

Trichophyton mentagrophytes genotype VII (TMVII) is an emerging dermatophyte that recently has been reported as a cause of sexually transmitted dermatophyte infections in Europe and the United States primarily affecting men who have sex with men.^25-27 Patients may present with pruritic, annular, scaly patches and plaques involving the trunk, groin, genital region, or face (Figure 2). Although closely related to T indotineae, TMVII differs in that it more often affects the genital region, generally is susceptible to terbinafine, and in the United States and Europe usually is not related to travel or immigration involving South Asia.²⁶ Although TMVII has not been associated with antifungal resistance, awareness among dermatologists is important because patients may experience inflamed, painful, and persistent rashes that can lead to secondary bacterial infection or scarring, and physicians might mistake it for mimics including eczema or psoriasis.^25,26

Importance of Judicious Antifungal Use

Optimizing the use of antifungals is critical to improving patient outcomes and preserving available treatment options.^28,29 A retrospective analysis of commercial health insurance data estimated that topical antifungal prescriptions were potentially unnecessary for more than half of the more than 560,000 patients who were prescribed these medications in 2023. In this study, it also was observed that only 16% of patients prescribed a topical antifungal had received diagnostic testing, with low rates across specialties.³⁰ This is concerning because even among board-certified dermatologists, incorrect diagnosis of suspected fungal skin infections can occur; in one survey-based study of board-certified dermatologists who were presented with dermatomycosis images, respondents categorized cases with greater than 75% accuracy in only 31% (4/13) of instances.³¹ Clotrimazole-betamethasone is among the most commonly prescribed topical antifungals in the United States,^14,32 and 2 recent retrospective analyses highlighted that the majority of patients prescribed this medication did not receive any fungal diagnostic testing.^33,34

Final Thoughts

In an era of emerging antifungal-resistant dermatophyte infections, it is important for dermatologists to educate nondermatologists about the importance of using diagnostic testing for suspected dermatophyte infections.^14,28 Dermatologists also can educate nondermatologist colleagues on the importance of avoiding the use of topical combination antifungal/corticosteroid medications and referring for dermatologic evaluation when diagnoses are uncertain.^33,34 Strategies for education by dermatologists could include giving workshops, creating educational materials, and fostering open communication about optimal treatment practices and referral parameters for suspected dermatophyte infections.

Lifeguards play a crucial role in ensuring water safety, but they also are uniquely positioned to promote skin cancer prevention and proper sunscreen use.^1,2 There are several benefits and challenges to offering skin cancer prevention training for lifeguards.³ We examine the advantages of training, highlight the role lifeguards can play in larger public skin cancer prevention efforts, and address practical techniques for developing lifeguardfocused skin cancer education programs. By providing this knowledge to lifeguards, we can improve community health outcomes and encourage sun-safe behaviors in high-risk outdoor locations.

Benefits of Skin Cancer Prevention Training for Lifeguards

Research has shown that lifeguards are at an elevated risk for basal cell carcinoma, squamous cell carcinoma, and melanoma due to frequent prolonged occupational sun exposure.^1,2,4-6 Therefore, comprehensive education on skin cancer prevention—including instruction on proper sunscreen application techniques and the importance of regular reapplication as well as how to recognize suspicious skin lesions—should be incorporated into lifeguard certification programs. One study evaluating the effectiveness of a skin cancer prevention program for lifeguards found that many of the participants lacked a thorough understanding of the different types of skin cancer.⁵ Another study found that lifeguards at pools in areas where societal norms supporting sun safety are stronger exhibited noticeably more sun protection practices, with regression estimates of 0.22 (95% CI, 0.17-0.26).⁷ Empowering lifeguards with valuable health knowledge during their regular training could potentially reduce their risk for skin cancer,⁴ as they may be more inclined to use sunscreen appropriately and reach out to a dermatologist for regular skin checks and evaluation of suspicious lesions.

Role of Lifeguards in Public Skin Cancer Prevention Efforts

Once trained on skin cancer prevention, lifeguards also can play a pivotal role in promoting sunscreen use among the public. Despite the widespread availability of high-quality sunscreens, many swimmers and beachgoers neglect to regularly apply or reapply sunscreen, especially on commonly exposed areas such as the back, shoulders, and face.⁸ Educating lifeguards on skin cancer prevention could enhance health outcomes by increasing early detection rates and promoting sun-safe behaviors among the general public.⁹ However, additional training requirements might increase the cost and time commitment for lifeguard certification, potentially leading to staffing shortages.^3,7 There also is a risk of lifeguards overstepping their role and providing inaccurate medical advice, which could cause distress or even lead to liability issues.⁷ Balancing these factors will be crucial in developing effective and sustainable skin cancer prevention programs for lifeguards.

Implementing Lifeguard Skin Cancer Training

Implementing skin cancer prevention training programs for lifeguards requires strategic collaboration between dermatologists, and lifeguard training organizations to ensure that the participants receive consistent and comprehensive training.¹⁰ Additionally, public health campaigns can support these efforts by raising awareness about the importance of sun safety and regular skin checks.⁶ Tailored training modules/materials, ongoing technical assistance, and active, multicomponent approaches that account for both individual and environmental factors can increase program implementation in a variety of community settings.

Final Thoughts

Through effective education, lifeguards can potentially have a substantial impact on skin cancer prevention, both among lifeguards themselves and the general public. By promoting proper sunscreen use, lifeguards can help reduce the incidence and mortality associated with skin cancers. Future studies should focus on developing and implementing targeted education initiatives for lifeguards, fostering collaboration between relevant stakeholders, and raising public awareness about the importance of sun safety and early skin cancer detection. These efforts ultimately could lead to improved public health outcomes and reduced skin cancer rates, particularly in high-risk populations that frequently are exposed to UV radiation.

Lifeguards play a crucial role in ensuring water safety, but they also are uniquely positioned to promote skin cancer prevention and proper sunscreen use.^1,2 There are several benefits and challenges to offering skin cancer prevention training for lifeguards.³ We examine the advantages of training, highlight the role lifeguards can play in larger public skin cancer prevention efforts, and address practical techniques for developing lifeguardfocused skin cancer education programs. By providing this knowledge to lifeguards, we can improve community health outcomes and encourage sun-safe behaviors in high-risk outdoor locations.

Benefits of Skin Cancer Prevention Training for Lifeguards

Research has shown that lifeguards are at an elevated risk for basal cell carcinoma, squamous cell carcinoma, and melanoma due to frequent prolonged occupational sun exposure.^1,2,4-6 Therefore, comprehensive education on skin cancer prevention—including instruction on proper sunscreen application techniques and the importance of regular reapplication as well as how to recognize suspicious skin lesions—should be incorporated into lifeguard certification programs. One study evaluating the effectiveness of a skin cancer prevention program for lifeguards found that many of the participants lacked a thorough understanding of the different types of skin cancer.⁵ Another study found that lifeguards at pools in areas where societal norms supporting sun safety are stronger exhibited noticeably more sun protection practices, with regression estimates of 0.22 (95% CI, 0.17-0.26).⁷ Empowering lifeguards with valuable health knowledge during their regular training could potentially reduce their risk for skin cancer,⁴ as they may be more inclined to use sunscreen appropriately and reach out to a dermatologist for regular skin checks and evaluation of suspicious lesions.

Role of Lifeguards in Public Skin Cancer Prevention Efforts

Once trained on skin cancer prevention, lifeguards also can play a pivotal role in promoting sunscreen use among the public. Despite the widespread availability of high-quality sunscreens, many swimmers and beachgoers neglect to regularly apply or reapply sunscreen, especially on commonly exposed areas such as the back, shoulders, and face.⁸ Educating lifeguards on skin cancer prevention could enhance health outcomes by increasing early detection rates and promoting sun-safe behaviors among the general public.⁹ However, additional training requirements might increase the cost and time commitment for lifeguard certification, potentially leading to staffing shortages.^3,7 There also is a risk of lifeguards overstepping their role and providing inaccurate medical advice, which could cause distress or even lead to liability issues.⁷ Balancing these factors will be crucial in developing effective and sustainable skin cancer prevention programs for lifeguards.

Implementing Lifeguard Skin Cancer Training

Implementing skin cancer prevention training programs for lifeguards requires strategic collaboration between dermatologists, and lifeguard training organizations to ensure that the participants receive consistent and comprehensive training.¹⁰ Additionally, public health campaigns can support these efforts by raising awareness about the importance of sun safety and regular skin checks.⁶ Tailored training modules/materials, ongoing technical assistance, and active, multicomponent approaches that account for both individual and environmental factors can increase program implementation in a variety of community settings.

Final Thoughts

Through effective education, lifeguards can potentially have a substantial impact on skin cancer prevention, both among lifeguards themselves and the general public. By promoting proper sunscreen use, lifeguards can help reduce the incidence and mortality associated with skin cancers. Future studies should focus on developing and implementing targeted education initiatives for lifeguards, fostering collaboration between relevant stakeholders, and raising public awareness about the importance of sun safety and early skin cancer detection. These efforts ultimately could lead to improved public health outcomes and reduced skin cancer rates, particularly in high-risk populations that frequently are exposed to UV radiation.

Lifeguards play a crucial role in ensuring water safety, but they also are uniquely positioned to promote skin cancer prevention and proper sunscreen use.^1,2 There are several benefits and challenges to offering skin cancer prevention training for lifeguards.³ We examine the advantages of training, highlight the role lifeguards can play in larger public skin cancer prevention efforts, and address practical techniques for developing lifeguardfocused skin cancer education programs. By providing this knowledge to lifeguards, we can improve community health outcomes and encourage sun-safe behaviors in high-risk outdoor locations.

Benefits of Skin Cancer Prevention Training for Lifeguards

Research has shown that lifeguards are at an elevated risk for basal cell carcinoma, squamous cell carcinoma, and melanoma due to frequent prolonged occupational sun exposure.^1,2,4-6 Therefore, comprehensive education on skin cancer prevention—including instruction on proper sunscreen application techniques and the importance of regular reapplication as well as how to recognize suspicious skin lesions—should be incorporated into lifeguard certification programs. One study evaluating the effectiveness of a skin cancer prevention program for lifeguards found that many of the participants lacked a thorough understanding of the different types of skin cancer.⁵ Another study found that lifeguards at pools in areas where societal norms supporting sun safety are stronger exhibited noticeably more sun protection practices, with regression estimates of 0.22 (95% CI, 0.17-0.26).⁷ Empowering lifeguards with valuable health knowledge during their regular training could potentially reduce their risk for skin cancer,⁴ as they may be more inclined to use sunscreen appropriately and reach out to a dermatologist for regular skin checks and evaluation of suspicious lesions.

Role of Lifeguards in Public Skin Cancer Prevention Efforts

Once trained on skin cancer prevention, lifeguards also can play a pivotal role in promoting sunscreen use among the public. Despite the widespread availability of high-quality sunscreens, many swimmers and beachgoers neglect to regularly apply or reapply sunscreen, especially on commonly exposed areas such as the back, shoulders, and face.⁸ Educating lifeguards on skin cancer prevention could enhance health outcomes by increasing early detection rates and promoting sun-safe behaviors among the general public.⁹ However, additional training requirements might increase the cost and time commitment for lifeguard certification, potentially leading to staffing shortages.^3,7 There also is a risk of lifeguards overstepping their role and providing inaccurate medical advice, which could cause distress or even lead to liability issues.⁷ Balancing these factors will be crucial in developing effective and sustainable skin cancer prevention programs for lifeguards.

Implementing Lifeguard Skin Cancer Training

Implementing skin cancer prevention training programs for lifeguards requires strategic collaboration between dermatologists, and lifeguard training organizations to ensure that the participants receive consistent and comprehensive training.¹⁰ Additionally, public health campaigns can support these efforts by raising awareness about the importance of sun safety and regular skin checks.⁶ Tailored training modules/materials, ongoing technical assistance, and active, multicomponent approaches that account for both individual and environmental factors can increase program implementation in a variety of community settings.

Final Thoughts

Through effective education, lifeguards can potentially have a substantial impact on skin cancer prevention, both among lifeguards themselves and the general public. By promoting proper sunscreen use, lifeguards can help reduce the incidence and mortality associated with skin cancers. Future studies should focus on developing and implementing targeted education initiatives for lifeguards, fostering collaboration between relevant stakeholders, and raising public awareness about the importance of sun safety and early skin cancer detection. These efforts ultimately could lead to improved public health outcomes and reduced skin cancer rates, particularly in high-risk populations that frequently are exposed to UV radiation.

Eosinophilic esophagitis (EoE) can be considered a “young” disease, with initial case series reported only about 30 years ago. Since that time, it has become a commonly encountered condition in both emergency and clinic settings. The most recent prevalence study estimates that 1 in 700 people in the U.S. have EoE,¹ the volume of EoE-associated ED visits tripped between 2009 and 2019 and is projected to double again by 2030,² and “new” gastroenterologists undoubtedly have learned about and seen this condition. As a chronic disease, EoE necessitates longitudinal follow-up and optimization of care to prevent complications. With increasing diagnostic delay, EoE progresses in most, but not all, patients from an inflammatory- to fibrostenotic-predominant condition.³This article will review a practical approach to diagnosing EoE, including common scenarios where it can be picked-up, as well as treatment and monitoring approaches.

Diagnosis of EoE

The most likely area that you will encounter EoE is during an emergent middle-of-the-night endoscopy for food impaction. If called in for this, EoE will be the cause in more than 50% of patients.⁴ However, the diagnosis can only be made if esophageal biopsies are obtained at the time of the procedure. This is a critical time to decrease diagnostic delay, as half of patients are lost to follow-up after a food impaction.⁵ Unfortunately, although taking biopsies during index food impaction is guideline-recommended, a quality metric, and safe to obtain after the food bolus is cleared, this is infrequently done in practice.^{6, 7}

The next most likely area for EoE detection is in the endoscopy suite where 15-23% of patients with dysphagia and 5-7% of patients undergoing upper endoscopy for any indication will have EoE.⁴ Sometimes EoE will be detected “incidentally” during an open-access case (for example, in a patient with diarrhea undergoing evaluation for celiac). In these cases, it is important to perform a careful history (as noted below) as subtle EoE symptoms can frequently be identified. Finally, when patients are seen in clinic for solid food dysphagia, EoE is clearly on the differential. A few percent of patients with refractory heartburn or chest pain will have EoE causing the symptoms rather than reflux,⁴ and all patients under consideration for antireflux surgery should have an endoscopy to assess for EoE.

When talking to patients with known or suspected EoE, the history must go beyond general questions about dysphagia or trouble swallowing. Many patients with EoE have overtly or subconsciously modified their eating behaviors over many years to minimize symptoms, may have adapted to chronic dysphagia, and will answer “no” when asked if they have trouble swallowing. Instead, use the acronym “IMPACT” to delve deeper into possible symptoms.⁸ Do they “Imbibe” fluids or liquids between each bite to help get food down? Do they “Modify” the way they eat (cut food into small bites; puree foods)? Do they “Prolong” mealtimes? Do they “Avoid” certain foods that stick? Do they “Chew’ until their food is a mush to get it down? And do they “Turn away” tablets or pills? Pill dysphagia is often a subtle symptom, and sometimes the only symptom elicited.

Additionally, it may be important to ask a partner or family member (if present) about their observations. They may provide insight (e.g. “yes – he chokes with every bite but never says it bothers him”) that the patient might not otherwise provide. The suspicion for EoE should also be increased in patients with concomitant atopic diseases and in those with a family history of dysphagia or who have family members needing esophageal dilation. It is important to remember that EoE can be seen across all ages, sexes, and races/ethnicities.

Diagnosis of EoE is based on the AGREE consensus,⁹ which is also echoed in the recently updated American College of Gastroenterology (ACG) guidelines.¹⁰ Diagnosis requires three steps. First, symptoms of esophageal dysfunction must be present. This will most typically be dysphagia in adolescents and adults, but symptoms are non-specific in children (e.g. poor growth and feeding, abdominal pain, vomiting, regurgitation, heartburn).

Second, at least 15 eosinophils per high-power field (eos/hpf) are required on esophageal biopsy, which implies that an endoscopy be performed. A high-quality endoscopic exam in EoE is of the utmost importance. The approach has been described elsewhere,¹¹ but enough time on insertion should be taken to fully insufflate and examine the esophagus, including the areas of the gastroesophageal junction and upper esophageal sphincter where strictures can be missed, to gently wash debris, and to assess the endoscopic findings of EoE. Endoscopic findings should be reported using the validated EoE Endoscopy Reference Score (EREFS),¹² which grades five key features. EREFS is reproducible, is responsive to treatment, and is guideline-recommended (see Figure 1).^{6, 10} The features are edema (present=1), rings (mild=1; moderate=2; severe=3), exudates (mild=1; severe=2), furrows (mild=1; severe=2), and stricture (present=1; also estimate diameter in mm) and are incorporated into many endoscopic reporting programs. Additionally, diffuse luminal narrowing and mucosal fragility (“crepe-paper” mucosa) should be assessed.

After this, biopsies should be obtained with at least 6 biopsy fragments from different locations in the esophagus. Any visible endoscopic abnormalities should be targeted (the highest yield is in exudates and furrows). The rationale is that EoE is patchy and at least 6 biopsies will maximize diagnostic yield.¹⁰ Ideally the initial endoscopy for EoE should be done off of treatments (like PPI or diet restriction) as these could mask the diagnosis. If a patient with suspected EoE has an endoscopy while on PPI, and the endoscopy is normal, a diagnosis of EoE cannot be made. In this case, consideration should be given as to stopping the PPI, allowing a wash out period (at least 1-2 months), and then repeating the endoscopy to confirm the diagnosis. This is important as EoE is a chronic condition necessitating life-long treatment and monitoring, so a definitive diagnosis is critical.

The third and final step in diagnosis is assessing for other conditions that could cause esophageal eosinophilia.⁹ The most common differential diagnosis is gastroesophageal reflux disease (GERD). In some cases, EoE and GERD overlap or can have a complex relationship.¹³ Unfortunately the location of the eosinophilia (i.e. distal only) and the level of the eosinophil counts are not useful in making this distinction, so all clinical features (symptoms, presence of erosive esophagitis, or a hiatal hernia endoscopically), and ancillary reflex testing when indicated may be required prior to a formal EoE diagnosis. After the diagnosis is established, there should be direct communication with the patient to review the diagnosis and select treatments. While it is possible to convey results electronically in a messaging portal or with a letter, a more formal interaction, such as a clinic visit, is recommended because this is a new diagnosis of a chronic condition. Similarly, a new diagnosis of inflammatory bowel disease would never be made in a pathology follow-up letter alone. 

 

Treatment of EoE

When it comes to treatment, the new guidelines emphasize several points.¹⁰ First, there is the concept that anti-inflammatory treatment should be paired with assessment of fibrostenosis and esophageal dilation; to do either in isolation is incomplete treatment. It is safe to perform dilation both prior to anti-inflammatory treatment (for example, with a critical stricture in a patient with dysphagia) and after anti-inflammatory treatment has been prescribed (for example, during an endoscopy to assess treatment response).

Second, proton pump inhibitors (PPIs), swallowed topical corticosteroids (tCS), or dietary elimination are all acceptable first-line treatment options for EoE. A shared decision-making framework should be used for this discussion. If dietary elimination is selected,¹⁴ based on new clinical trial data, guidelines recommend using empiric elimination and starting with a less restrictive diet (either a one-food elimination diet with dairy alone or a two-food elimination with dairy and wheat elimination). If PPIs are selected, the dose should be double the standard reflux dose. Data are mixed as to whether to use twice daily dosing (i.e., omeprazole 20 mg twice daily) or once a day dosing (i.e., omeprazole 40 mg daily), but total dose and adherence may be more important than frequency.¹⁰

For tCS use, either budesonide or fluticasone can be selected, but budesonide oral suspension is the only FDA-approved tCS for EoE.¹⁵ Initial treatment length is usually 6-8 weeks for diet elimination and, 12 weeks for PPI and tCS. In general, it is best to pick a single treatment to start, and reserve combining therapies for patients who do not have a complete response to a single modality as there are few data to support combination therapy.

After initial treatment, it is critical to assess for treatment response.¹⁶ Goals of EoE treatment include improvement in symptoms, but also improvement in endoscopic and histologic features to prevent complications. Symptoms in EoE do not always correlate with underlying biologic disease activity: patients can minimize symptoms with careful eating; they may perceive no difference in symptoms despite histologic improvement if a stricture persists; and they may have minimal symptoms after esophageal dilation despite ongoing inflammation. Because of this, performing a follow-up endoscopy after initial treatment is guideline-recommended.^{10, 17} This allows assessing for endoscopic improvement, re-assessing for fibrostenosis and performing dilation if indicated, and obtaining esophageal biopsies. If there is non-response, options include switching between other first line treatments or considering “stepping-up” to dupilumab which is also an FDA-approved option for EoE that is recommended in the guidelines.^{10, 18} In some cases where patients have multiple severe atopic conditions such as asthma or eczema that would warrant dupilumab use, or if patients are intolerant to PPIs or tCS, dupilumab could be considered as an earlier treatment for EoE.

 

Long-Term Maintenance

If a patient has a good response (for example, improved symptoms, improved endoscopic features, and <15 eos/hpf on biopsy), treatment can be maintained long-term. In almost all cases, if treatment is stopped, EoE disease activity recurs.¹⁹ Patients could be seen back in clinic in 6-12 months, and then a discussion can be conducted about a follow-up endoscopy, with timing to be determined based on their individual disease features and severity.¹⁷

Patients with more severe strictures, however, may have to be seen in endoscopy for serial dilations. Continued follow-up is essential for optimal care. Just as patients can progress in their disease course with diagnostic delay, there are data that show they can also progress after diagnosis when there are gaps in care without regular follow-up.²⁰ Unlike other chronic esophageal disorders such as GERD and Barrett’s esophagus and other chronic GI inflammatory conditions like inflammatory bowel disease, however, EoE is not associated with an increased risk of esophageal cancer.^{21, 22}

Given its increasing frequency, EoE will be commonly encountered by gastroenterologists both new and established. Having a systematic approach for diagnosis, understanding how to elicit subtle symptoms, implementing a shared decision-making framework for treatment with a structured algorithm for assessing response, performing follow-up, maintaining treatment, and monitoring patients long-term will allow the large majority of EoE patients to be successfully managed.

Dr. Dellon is based at the Center for Esophageal Diseases and Swallowing, Center for Gastrointestinal Biology and Disease, Division of Gastroenterology and Hepatology, University of North Carolina School of Medicine, Chapel Hill. He disclosed research funding, consultant fees, and educational grants from multiple companies.

References

1. Thel HL, et al. Prevalence and Costs of Eosinophilic Esophagitis in the United States. Clin Gastroenterol Hepatol. 2025 Feb. doi: 10.1016/j.cgh.2024.09.031.

2. Lam AY, et al. Epidemiologic Burden and Projections for Eosinophilic Esophagitis-Associated Emergency Department Visits in the United States: 2009-2030. Clin Gastroenterol Hepatol. 2023 Nov. doi: 10.1016/j.cgh.2023.04.028.

3. Schoepfer AM, et al. Delay in diagnosis of eosinophilic esophagitis increases risk for stricture formation in a time-dependent manner. Gastroenterology. 2013 Dec. doi: 10.1053/j.gastro.2013.08.015.

4. Dellon ES, Hirano I. Epidemiology and Natural History of Eosinophilic Esophagitis. Gastroenterology. 2018 Jan. doi: 10.1053/j.gastro.2017.06.067.

5. Chang JW, et al. Loss to follow-up after food impaction among patients with and without eosinophilic esophagitis. Dis Esophagus. 2019 Dec. doi: 10.1093/dote/doz056.

6. Aceves SS, et al. Endoscopic approach to eosinophilic esophagitis: American Society for Gastrointestinal Endoscopy Consensus Conference. Gastrointest Endosc. 2022 Aug. doi: 10.1016/j.gie.2022.05.013.

7. Leiman DA, et al. Quality Indicators for the Diagnosis and Management of Eosinophilic Esophagitis. Am J Gastroenterol. 2023 Jun. doi: 10.14309/ajg.0000000000002138.

8. Hirano I, Furuta GT. Approaches and Challenges to Management of Pediatric and Adult Patients With Eosinophilic Esophagitis. Gastroenterology. 2020 Mar. doi: 10.1053/j.gastro.2019.09.052.

9. Dellon ES, et al. Updated international consensus diagnostic criteria for eosinophilic esophagitis: Proceedings of the AGREE conference. Gastroenterology. 2018 Oct. doi: 10.1053/j.gastro.2018.07.009.

10. Dellon ES, et al. ACG Clinical Guideline: Diagnosis and Management of Eosinophilic Esophagitis. Am J Gastroenterol. 2025 Jan. doi: 10.14309/ajg.0000000000003194.

11. Dellon ES. Optimizing the Endoscopic Examination in Eosinophilic Esophagitis. Clin Gastroenterol Hepatol. 2021 Dec. doi: 10.1016/j.cgh.2021.07.011.

12. Hirano I, et al. Endoscopic assessment of the oesophageal features of eosinophilic oesophagitis: validation of a novel classification and grading system. Gut. 2012 May. doi: 10.1136/gutjnl-2011-301817.

13. Spechler SJ, et al. Thoughts on the complex relationship between gastroesophageal reflux disease and eosinophilic esophagitis. Am J Gastroenterol. 2007 Jun. doi: 10.1111/j.1572-0241.2007.01179.x.

14. Chang JW, et al. Development of a Practical Guide to Implement and Monitor Diet Therapy for Eosinophilic Esophagitis. Clin Gastroenterol Hepatol. 2023 Jul. doi: 10.1016/j.cgh.2023.03.006.

15. Hirano I, et al. Budesonide Oral Suspension Improves Outcomes in Patients With Eosinophilic Esophagitis: Results from a Phase 3 Trial. Clin Gastroenterol Hepatol. 2022 Mar. doi: 10.1016/j.cgh.2021.04.022.

16. Dellon ES, Gupta SK. A conceptual approach to understanding treatment response in eosinophilic esophagitis. Clin Gastroenterol Hepatol. 2019 Oct. doi: 10.1016/j.cgh.2019.01.030.

17. von Arnim U, et al. Monitoring Patients With Eosinophilic Esophagitis in Routine Clinical Practice - International Expert Recommendations. Clin Gastroenterol Hepatol. 2023 Sep. doi: 10.1016/j.cgh.2022.12.018.

18. Dellon ES, et al. Dupilumab in Adults and Adolescents with Eosinophilic Esophagitis. N Engl J Med. 2022 Dec. doi: 10.1056/NEJMoa220598.

19. Dellon ES, et al. Rapid Recurrence of Eosinophilic Esophagitis Activity After Successful Treatment in the Observation Phase of a Randomized, Double-Blind, Double-Dummy Trial. Clin Gastroenterol Hepatol. 2020 Jun. doi: 10.1016/j.cgh.2019.08.050.

20. Chang NC, et al. A Gap in Care Leads to Progression of Fibrosis in Eosinophilic Esophagitis Patients. Clin Gastroenterol Hepatol. 2022 Aug. doi: 10.1016/j.cgh.2021.10.028.

21. Syed A, et al. The relationship between eosinophilic esophagitis and esophageal cancer. Dis Esophagus. 2017 Jul. doi: 10.1093/dote/dox050.

22. Albaneze N, et al. No Association Between Eosinophilic Oesophagitis and Oesophageal Cancer in US Adults: A Case-Control Study. Aliment Pharmacol Ther. 2025 Jan. doi: 10.1111/apt.18431.







 

Eosinophilic esophagitis (EoE) can be considered a “young” disease, with initial case series reported only about 30 years ago. Since that time, it has become a commonly encountered condition in both emergency and clinic settings. The most recent prevalence study estimates that 1 in 700 people in the U.S. have EoE,¹ the volume of EoE-associated ED visits tripped between 2009 and 2019 and is projected to double again by 2030,² and “new” gastroenterologists undoubtedly have learned about and seen this condition. As a chronic disease, EoE necessitates longitudinal follow-up and optimization of care to prevent complications. With increasing diagnostic delay, EoE progresses in most, but not all, patients from an inflammatory- to fibrostenotic-predominant condition.³This article will review a practical approach to diagnosing EoE, including common scenarios where it can be picked-up, as well as treatment and monitoring approaches.

Diagnosis of EoE

The most likely area that you will encounter EoE is during an emergent middle-of-the-night endoscopy for food impaction. If called in for this, EoE will be the cause in more than 50% of patients.⁴ However, the diagnosis can only be made if esophageal biopsies are obtained at the time of the procedure. This is a critical time to decrease diagnostic delay, as half of patients are lost to follow-up after a food impaction.⁵ Unfortunately, although taking biopsies during index food impaction is guideline-recommended, a quality metric, and safe to obtain after the food bolus is cleared, this is infrequently done in practice.^{6, 7}

The next most likely area for EoE detection is in the endoscopy suite where 15-23% of patients with dysphagia and 5-7% of patients undergoing upper endoscopy for any indication will have EoE.⁴ Sometimes EoE will be detected “incidentally” during an open-access case (for example, in a patient with diarrhea undergoing evaluation for celiac). In these cases, it is important to perform a careful history (as noted below) as subtle EoE symptoms can frequently be identified. Finally, when patients are seen in clinic for solid food dysphagia, EoE is clearly on the differential. A few percent of patients with refractory heartburn or chest pain will have EoE causing the symptoms rather than reflux,⁴ and all patients under consideration for antireflux surgery should have an endoscopy to assess for EoE.

When talking to patients with known or suspected EoE, the history must go beyond general questions about dysphagia or trouble swallowing. Many patients with EoE have overtly or subconsciously modified their eating behaviors over many years to minimize symptoms, may have adapted to chronic dysphagia, and will answer “no” when asked if they have trouble swallowing. Instead, use the acronym “IMPACT” to delve deeper into possible symptoms.⁸ Do they “Imbibe” fluids or liquids between each bite to help get food down? Do they “Modify” the way they eat (cut food into small bites; puree foods)? Do they “Prolong” mealtimes? Do they “Avoid” certain foods that stick? Do they “Chew’ until their food is a mush to get it down? And do they “Turn away” tablets or pills? Pill dysphagia is often a subtle symptom, and sometimes the only symptom elicited.

Additionally, it may be important to ask a partner or family member (if present) about their observations. They may provide insight (e.g. “yes – he chokes with every bite but never says it bothers him”) that the patient might not otherwise provide. The suspicion for EoE should also be increased in patients with concomitant atopic diseases and in those with a family history of dysphagia or who have family members needing esophageal dilation. It is important to remember that EoE can be seen across all ages, sexes, and races/ethnicities.

Diagnosis of EoE is based on the AGREE consensus,⁹ which is also echoed in the recently updated American College of Gastroenterology (ACG) guidelines.¹⁰ Diagnosis requires three steps. First, symptoms of esophageal dysfunction must be present. This will most typically be dysphagia in adolescents and adults, but symptoms are non-specific in children (e.g. poor growth and feeding, abdominal pain, vomiting, regurgitation, heartburn).

Second, at least 15 eosinophils per high-power field (eos/hpf) are required on esophageal biopsy, which implies that an endoscopy be performed. A high-quality endoscopic exam in EoE is of the utmost importance. The approach has been described elsewhere,¹¹ but enough time on insertion should be taken to fully insufflate and examine the esophagus, including the areas of the gastroesophageal junction and upper esophageal sphincter where strictures can be missed, to gently wash debris, and to assess the endoscopic findings of EoE. Endoscopic findings should be reported using the validated EoE Endoscopy Reference Score (EREFS),¹² which grades five key features. EREFS is reproducible, is responsive to treatment, and is guideline-recommended (see Figure 1).^{6, 10} The features are edema (present=1), rings (mild=1; moderate=2; severe=3), exudates (mild=1; severe=2), furrows (mild=1; severe=2), and stricture (present=1; also estimate diameter in mm) and are incorporated into many endoscopic reporting programs. Additionally, diffuse luminal narrowing and mucosal fragility (“crepe-paper” mucosa) should be assessed.

After this, biopsies should be obtained with at least 6 biopsy fragments from different locations in the esophagus. Any visible endoscopic abnormalities should be targeted (the highest yield is in exudates and furrows). The rationale is that EoE is patchy and at least 6 biopsies will maximize diagnostic yield.¹⁰ Ideally the initial endoscopy for EoE should be done off of treatments (like PPI or diet restriction) as these could mask the diagnosis. If a patient with suspected EoE has an endoscopy while on PPI, and the endoscopy is normal, a diagnosis of EoE cannot be made. In this case, consideration should be given as to stopping the PPI, allowing a wash out period (at least 1-2 months), and then repeating the endoscopy to confirm the diagnosis. This is important as EoE is a chronic condition necessitating life-long treatment and monitoring, so a definitive diagnosis is critical.

The third and final step in diagnosis is assessing for other conditions that could cause esophageal eosinophilia.⁹ The most common differential diagnosis is gastroesophageal reflux disease (GERD). In some cases, EoE and GERD overlap or can have a complex relationship.¹³ Unfortunately the location of the eosinophilia (i.e. distal only) and the level of the eosinophil counts are not useful in making this distinction, so all clinical features (symptoms, presence of erosive esophagitis, or a hiatal hernia endoscopically), and ancillary reflex testing when indicated may be required prior to a formal EoE diagnosis. After the diagnosis is established, there should be direct communication with the patient to review the diagnosis and select treatments. While it is possible to convey results electronically in a messaging portal or with a letter, a more formal interaction, such as a clinic visit, is recommended because this is a new diagnosis of a chronic condition. Similarly, a new diagnosis of inflammatory bowel disease would never be made in a pathology follow-up letter alone. 

 

Treatment of EoE

When it comes to treatment, the new guidelines emphasize several points.¹⁰ First, there is the concept that anti-inflammatory treatment should be paired with assessment of fibrostenosis and esophageal dilation; to do either in isolation is incomplete treatment. It is safe to perform dilation both prior to anti-inflammatory treatment (for example, with a critical stricture in a patient with dysphagia) and after anti-inflammatory treatment has been prescribed (for example, during an endoscopy to assess treatment response).

Second, proton pump inhibitors (PPIs), swallowed topical corticosteroids (tCS), or dietary elimination are all acceptable first-line treatment options for EoE. A shared decision-making framework should be used for this discussion. If dietary elimination is selected,¹⁴ based on new clinical trial data, guidelines recommend using empiric elimination and starting with a less restrictive diet (either a one-food elimination diet with dairy alone or a two-food elimination with dairy and wheat elimination). If PPIs are selected, the dose should be double the standard reflux dose. Data are mixed as to whether to use twice daily dosing (i.e., omeprazole 20 mg twice daily) or once a day dosing (i.e., omeprazole 40 mg daily), but total dose and adherence may be more important than frequency.¹⁰

For tCS use, either budesonide or fluticasone can be selected, but budesonide oral suspension is the only FDA-approved tCS for EoE.¹⁵ Initial treatment length is usually 6-8 weeks for diet elimination and, 12 weeks for PPI and tCS. In general, it is best to pick a single treatment to start, and reserve combining therapies for patients who do not have a complete response to a single modality as there are few data to support combination therapy.

After initial treatment, it is critical to assess for treatment response.¹⁶ Goals of EoE treatment include improvement in symptoms, but also improvement in endoscopic and histologic features to prevent complications. Symptoms in EoE do not always correlate with underlying biologic disease activity: patients can minimize symptoms with careful eating; they may perceive no difference in symptoms despite histologic improvement if a stricture persists; and they may have minimal symptoms after esophageal dilation despite ongoing inflammation. Because of this, performing a follow-up endoscopy after initial treatment is guideline-recommended.^{10, 17} This allows assessing for endoscopic improvement, re-assessing for fibrostenosis and performing dilation if indicated, and obtaining esophageal biopsies. If there is non-response, options include switching between other first line treatments or considering “stepping-up” to dupilumab which is also an FDA-approved option for EoE that is recommended in the guidelines.^{10, 18} In some cases where patients have multiple severe atopic conditions such as asthma or eczema that would warrant dupilumab use, or if patients are intolerant to PPIs or tCS, dupilumab could be considered as an earlier treatment for EoE.

 

Long-Term Maintenance

If a patient has a good response (for example, improved symptoms, improved endoscopic features, and <15 eos/hpf on biopsy), treatment can be maintained long-term. In almost all cases, if treatment is stopped, EoE disease activity recurs.¹⁹ Patients could be seen back in clinic in 6-12 months, and then a discussion can be conducted about a follow-up endoscopy, with timing to be determined based on their individual disease features and severity.¹⁷

Patients with more severe strictures, however, may have to be seen in endoscopy for serial dilations. Continued follow-up is essential for optimal care. Just as patients can progress in their disease course with diagnostic delay, there are data that show they can also progress after diagnosis when there are gaps in care without regular follow-up.²⁰ Unlike other chronic esophageal disorders such as GERD and Barrett’s esophagus and other chronic GI inflammatory conditions like inflammatory bowel disease, however, EoE is not associated with an increased risk of esophageal cancer.^{21, 22}

Given its increasing frequency, EoE will be commonly encountered by gastroenterologists both new and established. Having a systematic approach for diagnosis, understanding how to elicit subtle symptoms, implementing a shared decision-making framework for treatment with a structured algorithm for assessing response, performing follow-up, maintaining treatment, and monitoring patients long-term will allow the large majority of EoE patients to be successfully managed.

Dr. Dellon is based at the Center for Esophageal Diseases and Swallowing, Center for Gastrointestinal Biology and Disease, Division of Gastroenterology and Hepatology, University of North Carolina School of Medicine, Chapel Hill. He disclosed research funding, consultant fees, and educational grants from multiple companies.

References

1. Thel HL, et al. Prevalence and Costs of Eosinophilic Esophagitis in the United States. Clin Gastroenterol Hepatol. 2025 Feb. doi: 10.1016/j.cgh.2024.09.031.

2. Lam AY, et al. Epidemiologic Burden and Projections for Eosinophilic Esophagitis-Associated Emergency Department Visits in the United States: 2009-2030. Clin Gastroenterol Hepatol. 2023 Nov. doi: 10.1016/j.cgh.2023.04.028.

3. Schoepfer AM, et al. Delay in diagnosis of eosinophilic esophagitis increases risk for stricture formation in a time-dependent manner. Gastroenterology. 2013 Dec. doi: 10.1053/j.gastro.2013.08.015.

4. Dellon ES, Hirano I. Epidemiology and Natural History of Eosinophilic Esophagitis. Gastroenterology. 2018 Jan. doi: 10.1053/j.gastro.2017.06.067.

5. Chang JW, et al. Loss to follow-up after food impaction among patients with and without eosinophilic esophagitis. Dis Esophagus. 2019 Dec. doi: 10.1093/dote/doz056.

6. Aceves SS, et al. Endoscopic approach to eosinophilic esophagitis: American Society for Gastrointestinal Endoscopy Consensus Conference. Gastrointest Endosc. 2022 Aug. doi: 10.1016/j.gie.2022.05.013.

7. Leiman DA, et al. Quality Indicators for the Diagnosis and Management of Eosinophilic Esophagitis. Am J Gastroenterol. 2023 Jun. doi: 10.14309/ajg.0000000000002138.

8. Hirano I, Furuta GT. Approaches and Challenges to Management of Pediatric and Adult Patients With Eosinophilic Esophagitis. Gastroenterology. 2020 Mar. doi: 10.1053/j.gastro.2019.09.052.

9. Dellon ES, et al. Updated international consensus diagnostic criteria for eosinophilic esophagitis: Proceedings of the AGREE conference. Gastroenterology. 2018 Oct. doi: 10.1053/j.gastro.2018.07.009.

10. Dellon ES, et al. ACG Clinical Guideline: Diagnosis and Management of Eosinophilic Esophagitis. Am J Gastroenterol. 2025 Jan. doi: 10.14309/ajg.0000000000003194.

11. Dellon ES. Optimizing the Endoscopic Examination in Eosinophilic Esophagitis. Clin Gastroenterol Hepatol. 2021 Dec. doi: 10.1016/j.cgh.2021.07.011.

12. Hirano I, et al. Endoscopic assessment of the oesophageal features of eosinophilic oesophagitis: validation of a novel classification and grading system. Gut. 2012 May. doi: 10.1136/gutjnl-2011-301817.

13. Spechler SJ, et al. Thoughts on the complex relationship between gastroesophageal reflux disease and eosinophilic esophagitis. Am J Gastroenterol. 2007 Jun. doi: 10.1111/j.1572-0241.2007.01179.x.

14. Chang JW, et al. Development of a Practical Guide to Implement and Monitor Diet Therapy for Eosinophilic Esophagitis. Clin Gastroenterol Hepatol. 2023 Jul. doi: 10.1016/j.cgh.2023.03.006.

15. Hirano I, et al. Budesonide Oral Suspension Improves Outcomes in Patients With Eosinophilic Esophagitis: Results from a Phase 3 Trial. Clin Gastroenterol Hepatol. 2022 Mar. doi: 10.1016/j.cgh.2021.04.022.

16. Dellon ES, Gupta SK. A conceptual approach to understanding treatment response in eosinophilic esophagitis. Clin Gastroenterol Hepatol. 2019 Oct. doi: 10.1016/j.cgh.2019.01.030.

17. von Arnim U, et al. Monitoring Patients With Eosinophilic Esophagitis in Routine Clinical Practice - International Expert Recommendations. Clin Gastroenterol Hepatol. 2023 Sep. doi: 10.1016/j.cgh.2022.12.018.

18. Dellon ES, et al. Dupilumab in Adults and Adolescents with Eosinophilic Esophagitis. N Engl J Med. 2022 Dec. doi: 10.1056/NEJMoa220598.

19. Dellon ES, et al. Rapid Recurrence of Eosinophilic Esophagitis Activity After Successful Treatment in the Observation Phase of a Randomized, Double-Blind, Double-Dummy Trial. Clin Gastroenterol Hepatol. 2020 Jun. doi: 10.1016/j.cgh.2019.08.050.

20. Chang NC, et al. A Gap in Care Leads to Progression of Fibrosis in Eosinophilic Esophagitis Patients. Clin Gastroenterol Hepatol. 2022 Aug. doi: 10.1016/j.cgh.2021.10.028.

21. Syed A, et al. The relationship between eosinophilic esophagitis and esophageal cancer. Dis Esophagus. 2017 Jul. doi: 10.1093/dote/dox050.

22. Albaneze N, et al. No Association Between Eosinophilic Oesophagitis and Oesophageal Cancer in US Adults: A Case-Control Study. Aliment Pharmacol Ther. 2025 Jan. doi: 10.1111/apt.18431.







 

Eosinophilic esophagitis (EoE) can be considered a “young” disease, with initial case series reported only about 30 years ago. Since that time, it has become a commonly encountered condition in both emergency and clinic settings. The most recent prevalence study estimates that 1 in 700 people in the U.S. have EoE,¹ the volume of EoE-associated ED visits tripped between 2009 and 2019 and is projected to double again by 2030,² and “new” gastroenterologists undoubtedly have learned about and seen this condition. As a chronic disease, EoE necessitates longitudinal follow-up and optimization of care to prevent complications. With increasing diagnostic delay, EoE progresses in most, but not all, patients from an inflammatory- to fibrostenotic-predominant condition.³This article will review a practical approach to diagnosing EoE, including common scenarios where it can be picked-up, as well as treatment and monitoring approaches.

Diagnosis of EoE

The most likely area that you will encounter EoE is during an emergent middle-of-the-night endoscopy for food impaction. If called in for this, EoE will be the cause in more than 50% of patients.⁴ However, the diagnosis can only be made if esophageal biopsies are obtained at the time of the procedure. This is a critical time to decrease diagnostic delay, as half of patients are lost to follow-up after a food impaction.⁵ Unfortunately, although taking biopsies during index food impaction is guideline-recommended, a quality metric, and safe to obtain after the food bolus is cleared, this is infrequently done in practice.^{6, 7}

The next most likely area for EoE detection is in the endoscopy suite where 15-23% of patients with dysphagia and 5-7% of patients undergoing upper endoscopy for any indication will have EoE.⁴ Sometimes EoE will be detected “incidentally” during an open-access case (for example, in a patient with diarrhea undergoing evaluation for celiac). In these cases, it is important to perform a careful history (as noted below) as subtle EoE symptoms can frequently be identified. Finally, when patients are seen in clinic for solid food dysphagia, EoE is clearly on the differential. A few percent of patients with refractory heartburn or chest pain will have EoE causing the symptoms rather than reflux,⁴ and all patients under consideration for antireflux surgery should have an endoscopy to assess for EoE.

When talking to patients with known or suspected EoE, the history must go beyond general questions about dysphagia or trouble swallowing. Many patients with EoE have overtly or subconsciously modified their eating behaviors over many years to minimize symptoms, may have adapted to chronic dysphagia, and will answer “no” when asked if they have trouble swallowing. Instead, use the acronym “IMPACT” to delve deeper into possible symptoms.⁸ Do they “Imbibe” fluids or liquids between each bite to help get food down? Do they “Modify” the way they eat (cut food into small bites; puree foods)? Do they “Prolong” mealtimes? Do they “Avoid” certain foods that stick? Do they “Chew’ until their food is a mush to get it down? And do they “Turn away” tablets or pills? Pill dysphagia is often a subtle symptom, and sometimes the only symptom elicited.

Additionally, it may be important to ask a partner or family member (if present) about their observations. They may provide insight (e.g. “yes – he chokes with every bite but never says it bothers him”) that the patient might not otherwise provide. The suspicion for EoE should also be increased in patients with concomitant atopic diseases and in those with a family history of dysphagia or who have family members needing esophageal dilation. It is important to remember that EoE can be seen across all ages, sexes, and races/ethnicities.

Diagnosis of EoE is based on the AGREE consensus,⁹ which is also echoed in the recently updated American College of Gastroenterology (ACG) guidelines.¹⁰ Diagnosis requires three steps. First, symptoms of esophageal dysfunction must be present. This will most typically be dysphagia in adolescents and adults, but symptoms are non-specific in children (e.g. poor growth and feeding, abdominal pain, vomiting, regurgitation, heartburn).

Second, at least 15 eosinophils per high-power field (eos/hpf) are required on esophageal biopsy, which implies that an endoscopy be performed. A high-quality endoscopic exam in EoE is of the utmost importance. The approach has been described elsewhere,¹¹ but enough time on insertion should be taken to fully insufflate and examine the esophagus, including the areas of the gastroesophageal junction and upper esophageal sphincter where strictures can be missed, to gently wash debris, and to assess the endoscopic findings of EoE. Endoscopic findings should be reported using the validated EoE Endoscopy Reference Score (EREFS),¹² which grades five key features. EREFS is reproducible, is responsive to treatment, and is guideline-recommended (see Figure 1).^{6, 10} The features are edema (present=1), rings (mild=1; moderate=2; severe=3), exudates (mild=1; severe=2), furrows (mild=1; severe=2), and stricture (present=1; also estimate diameter in mm) and are incorporated into many endoscopic reporting programs. Additionally, diffuse luminal narrowing and mucosal fragility (“crepe-paper” mucosa) should be assessed.

After this, biopsies should be obtained with at least 6 biopsy fragments from different locations in the esophagus. Any visible endoscopic abnormalities should be targeted (the highest yield is in exudates and furrows). The rationale is that EoE is patchy and at least 6 biopsies will maximize diagnostic yield.¹⁰ Ideally the initial endoscopy for EoE should be done off of treatments (like PPI or diet restriction) as these could mask the diagnosis. If a patient with suspected EoE has an endoscopy while on PPI, and the endoscopy is normal, a diagnosis of EoE cannot be made. In this case, consideration should be given as to stopping the PPI, allowing a wash out period (at least 1-2 months), and then repeating the endoscopy to confirm the diagnosis. This is important as EoE is a chronic condition necessitating life-long treatment and monitoring, so a definitive diagnosis is critical.

The third and final step in diagnosis is assessing for other conditions that could cause esophageal eosinophilia.⁹ The most common differential diagnosis is gastroesophageal reflux disease (GERD). In some cases, EoE and GERD overlap or can have a complex relationship.¹³ Unfortunately the location of the eosinophilia (i.e. distal only) and the level of the eosinophil counts are not useful in making this distinction, so all clinical features (symptoms, presence of erosive esophagitis, or a hiatal hernia endoscopically), and ancillary reflex testing when indicated may be required prior to a formal EoE diagnosis. After the diagnosis is established, there should be direct communication with the patient to review the diagnosis and select treatments. While it is possible to convey results electronically in a messaging portal or with a letter, a more formal interaction, such as a clinic visit, is recommended because this is a new diagnosis of a chronic condition. Similarly, a new diagnosis of inflammatory bowel disease would never be made in a pathology follow-up letter alone. 

 

Treatment of EoE

When it comes to treatment, the new guidelines emphasize several points.¹⁰ First, there is the concept that anti-inflammatory treatment should be paired with assessment of fibrostenosis and esophageal dilation; to do either in isolation is incomplete treatment. It is safe to perform dilation both prior to anti-inflammatory treatment (for example, with a critical stricture in a patient with dysphagia) and after anti-inflammatory treatment has been prescribed (for example, during an endoscopy to assess treatment response).

Second, proton pump inhibitors (PPIs), swallowed topical corticosteroids (tCS), or dietary elimination are all acceptable first-line treatment options for EoE. A shared decision-making framework should be used for this discussion. If dietary elimination is selected,¹⁴ based on new clinical trial data, guidelines recommend using empiric elimination and starting with a less restrictive diet (either a one-food elimination diet with dairy alone or a two-food elimination with dairy and wheat elimination). If PPIs are selected, the dose should be double the standard reflux dose. Data are mixed as to whether to use twice daily dosing (i.e., omeprazole 20 mg twice daily) or once a day dosing (i.e., omeprazole 40 mg daily), but total dose and adherence may be more important than frequency.¹⁰

For tCS use, either budesonide or fluticasone can be selected, but budesonide oral suspension is the only FDA-approved tCS for EoE.¹⁵ Initial treatment length is usually 6-8 weeks for diet elimination and, 12 weeks for PPI and tCS. In general, it is best to pick a single treatment to start, and reserve combining therapies for patients who do not have a complete response to a single modality as there are few data to support combination therapy.

After initial treatment, it is critical to assess for treatment response.¹⁶ Goals of EoE treatment include improvement in symptoms, but also improvement in endoscopic and histologic features to prevent complications. Symptoms in EoE do not always correlate with underlying biologic disease activity: patients can minimize symptoms with careful eating; they may perceive no difference in symptoms despite histologic improvement if a stricture persists; and they may have minimal symptoms after esophageal dilation despite ongoing inflammation. Because of this, performing a follow-up endoscopy after initial treatment is guideline-recommended.^{10, 17} This allows assessing for endoscopic improvement, re-assessing for fibrostenosis and performing dilation if indicated, and obtaining esophageal biopsies. If there is non-response, options include switching between other first line treatments or considering “stepping-up” to dupilumab which is also an FDA-approved option for EoE that is recommended in the guidelines.^{10, 18} In some cases where patients have multiple severe atopic conditions such as asthma or eczema that would warrant dupilumab use, or if patients are intolerant to PPIs or tCS, dupilumab could be considered as an earlier treatment for EoE.

 

Long-Term Maintenance

If a patient has a good response (for example, improved symptoms, improved endoscopic features, and <15 eos/hpf on biopsy), treatment can be maintained long-term. In almost all cases, if treatment is stopped, EoE disease activity recurs.¹⁹ Patients could be seen back in clinic in 6-12 months, and then a discussion can be conducted about a follow-up endoscopy, with timing to be determined based on their individual disease features and severity.¹⁷

Patients with more severe strictures, however, may have to be seen in endoscopy for serial dilations. Continued follow-up is essential for optimal care. Just as patients can progress in their disease course with diagnostic delay, there are data that show they can also progress after diagnosis when there are gaps in care without regular follow-up.²⁰ Unlike other chronic esophageal disorders such as GERD and Barrett’s esophagus and other chronic GI inflammatory conditions like inflammatory bowel disease, however, EoE is not associated with an increased risk of esophageal cancer.^{21, 22}

Given its increasing frequency, EoE will be commonly encountered by gastroenterologists both new and established. Having a systematic approach for diagnosis, understanding how to elicit subtle symptoms, implementing a shared decision-making framework for treatment with a structured algorithm for assessing response, performing follow-up, maintaining treatment, and monitoring patients long-term will allow the large majority of EoE patients to be successfully managed.

Dr. Dellon is based at the Center for Esophageal Diseases and Swallowing, Center for Gastrointestinal Biology and Disease, Division of Gastroenterology and Hepatology, University of North Carolina School of Medicine, Chapel Hill. He disclosed research funding, consultant fees, and educational grants from multiple companies.

References

1. Thel HL, et al. Prevalence and Costs of Eosinophilic Esophagitis in the United States. Clin Gastroenterol Hepatol. 2025 Feb. doi: 10.1016/j.cgh.2024.09.031.

2. Lam AY, et al. Epidemiologic Burden and Projections for Eosinophilic Esophagitis-Associated Emergency Department Visits in the United States: 2009-2030. Clin Gastroenterol Hepatol. 2023 Nov. doi: 10.1016/j.cgh.2023.04.028.

3. Schoepfer AM, et al. Delay in diagnosis of eosinophilic esophagitis increases risk for stricture formation in a time-dependent manner. Gastroenterology. 2013 Dec. doi: 10.1053/j.gastro.2013.08.015.

4. Dellon ES, Hirano I. Epidemiology and Natural History of Eosinophilic Esophagitis. Gastroenterology. 2018 Jan. doi: 10.1053/j.gastro.2017.06.067.

5. Chang JW, et al. Loss to follow-up after food impaction among patients with and without eosinophilic esophagitis. Dis Esophagus. 2019 Dec. doi: 10.1093/dote/doz056.

6. Aceves SS, et al. Endoscopic approach to eosinophilic esophagitis: American Society for Gastrointestinal Endoscopy Consensus Conference. Gastrointest Endosc. 2022 Aug. doi: 10.1016/j.gie.2022.05.013.

7. Leiman DA, et al. Quality Indicators for the Diagnosis and Management of Eosinophilic Esophagitis. Am J Gastroenterol. 2023 Jun. doi: 10.14309/ajg.0000000000002138.

8. Hirano I, Furuta GT. Approaches and Challenges to Management of Pediatric and Adult Patients With Eosinophilic Esophagitis. Gastroenterology. 2020 Mar. doi: 10.1053/j.gastro.2019.09.052.

9. Dellon ES, et al. Updated international consensus diagnostic criteria for eosinophilic esophagitis: Proceedings of the AGREE conference. Gastroenterology. 2018 Oct. doi: 10.1053/j.gastro.2018.07.009.

10. Dellon ES, et al. ACG Clinical Guideline: Diagnosis and Management of Eosinophilic Esophagitis. Am J Gastroenterol. 2025 Jan. doi: 10.14309/ajg.0000000000003194.

11. Dellon ES. Optimizing the Endoscopic Examination in Eosinophilic Esophagitis. Clin Gastroenterol Hepatol. 2021 Dec. doi: 10.1016/j.cgh.2021.07.011.

12. Hirano I, et al. Endoscopic assessment of the oesophageal features of eosinophilic oesophagitis: validation of a novel classification and grading system. Gut. 2012 May. doi: 10.1136/gutjnl-2011-301817.

13. Spechler SJ, et al. Thoughts on the complex relationship between gastroesophageal reflux disease and eosinophilic esophagitis. Am J Gastroenterol. 2007 Jun. doi: 10.1111/j.1572-0241.2007.01179.x.

14. Chang JW, et al. Development of a Practical Guide to Implement and Monitor Diet Therapy for Eosinophilic Esophagitis. Clin Gastroenterol Hepatol. 2023 Jul. doi: 10.1016/j.cgh.2023.03.006.

15. Hirano I, et al. Budesonide Oral Suspension Improves Outcomes in Patients With Eosinophilic Esophagitis: Results from a Phase 3 Trial. Clin Gastroenterol Hepatol. 2022 Mar. doi: 10.1016/j.cgh.2021.04.022.

16. Dellon ES, Gupta SK. A conceptual approach to understanding treatment response in eosinophilic esophagitis. Clin Gastroenterol Hepatol. 2019 Oct. doi: 10.1016/j.cgh.2019.01.030.

17. von Arnim U, et al. Monitoring Patients With Eosinophilic Esophagitis in Routine Clinical Practice - International Expert Recommendations. Clin Gastroenterol Hepatol. 2023 Sep. doi: 10.1016/j.cgh.2022.12.018.

18. Dellon ES, et al. Dupilumab in Adults and Adolescents with Eosinophilic Esophagitis. N Engl J Med. 2022 Dec. doi: 10.1056/NEJMoa220598.

19. Dellon ES, et al. Rapid Recurrence of Eosinophilic Esophagitis Activity After Successful Treatment in the Observation Phase of a Randomized, Double-Blind, Double-Dummy Trial. Clin Gastroenterol Hepatol. 2020 Jun. doi: 10.1016/j.cgh.2019.08.050.

20. Chang NC, et al. A Gap in Care Leads to Progression of Fibrosis in Eosinophilic Esophagitis Patients. Clin Gastroenterol Hepatol. 2022 Aug. doi: 10.1016/j.cgh.2021.10.028.

21. Syed A, et al. The relationship between eosinophilic esophagitis and esophageal cancer. Dis Esophagus. 2017 Jul. doi: 10.1093/dote/dox050.

22. Albaneze N, et al. No Association Between Eosinophilic Oesophagitis and Oesophageal Cancer in US Adults: A Case-Control Study. Aliment Pharmacol Ther. 2025 Jan. doi: 10.1111/apt.18431.







 

In this video, Lisa Mathew, MD, of South Denver Gastroenterology in Denver, Colorado, and Raja Taunk, MD, of Anne Arundel Gastroenterology Associates, in Annapolis, Maryland, share insights on private practice gastroenterology and offer tips on building your practice – specifically improving your referral base.

In this video, Lisa Mathew, MD, of South Denver Gastroenterology in Denver, Colorado, and Raja Taunk, MD, of Anne Arundel Gastroenterology Associates, in Annapolis, Maryland, share insights on private practice gastroenterology and offer tips on building your practice – specifically improving your referral base.

In this video, Lisa Mathew, MD, of South Denver Gastroenterology in Denver, Colorado, and Raja Taunk, MD, of Anne Arundel Gastroenterology Associates, in Annapolis, Maryland, share insights on private practice gastroenterology and offer tips on building your practice – specifically improving your referral base.

The United States boasts one of the premier health care systems for medical education in the world. Indeed, institutions such as Johns Hopkins, Harvard, and the Mayo Clinic have storied reputations and are recognized names the world over. The United States also stands as a country of remarkable discovery in medicine with an abundance of enormously talented and productive medical scientists. This reputation draws physicians from every corner of the world who dream of studying medicine in our country.

Unfortunately, many US medical institutions, particularly the most prestigious medical centers, lean heavily toward preferential acceptance of US medical school graduates as an indicator of the highest-quality trainees. This historical bias is being further compounded by our current government’s pejorative view of immigrants in general. Will this affect the pool of tomorrow’s stars who will change the course of American medicine?

 

A glance at the list of recent AGA Presidents may yield some insight; over the past 10 years, three of our presidents trained internationally at universities in Malta, Libya, and Germany. This is a small snapshot of the multitude of international graduates in gastroenterology and hepatology who have served as division chiefs, AGA award winners, and journal editors, all now US citizens. This is not to mention the influence of varied insights and talents native to international study and culture that enhance our practice of medicine and biomedical research. 

We live in time when “immigrant” has been assigned a negative and almost subhuman connotation, and diversity has become something to be demonized rather than celebrated. Yet, intuitively, should a top US medical graduate be any more intelligent or driven than a top graduate from the United Kingdom, India, China, or Syria? As American medical physicians, we place the utmost value on our traditions and high standards. We boast an unmatched depth of medical talent spread across our GI divisions and practices and take pride in the way we teach medicine, like no other nation. Now, more than ever, is a time to attract the best and brightest international graduates not to compete with but to complement our remarkable US students. American medicine benefits from their talent and they inspire us to remember and care for diseases in our field that affect the world’s population, not just ours. 

Over 100 years ago, Dr. William Mayo stated “American practice is too broad to be national. It had the scientific spirit, and science knows no country.” Dr. Mayo also said, “Democracy is safe only so long as culture is in the ascendancy.” These lessons apply more than ever today.

David Katzka, MD

Associate Editor

The United States boasts one of the premier health care systems for medical education in the world. Indeed, institutions such as Johns Hopkins, Harvard, and the Mayo Clinic have storied reputations and are recognized names the world over. The United States also stands as a country of remarkable discovery in medicine with an abundance of enormously talented and productive medical scientists. This reputation draws physicians from every corner of the world who dream of studying medicine in our country.

Unfortunately, many US medical institutions, particularly the most prestigious medical centers, lean heavily toward preferential acceptance of US medical school graduates as an indicator of the highest-quality trainees. This historical bias is being further compounded by our current government’s pejorative view of immigrants in general. Will this affect the pool of tomorrow’s stars who will change the course of American medicine?

 

A glance at the list of recent AGA Presidents may yield some insight; over the past 10 years, three of our presidents trained internationally at universities in Malta, Libya, and Germany. This is a small snapshot of the multitude of international graduates in gastroenterology and hepatology who have served as division chiefs, AGA award winners, and journal editors, all now US citizens. This is not to mention the influence of varied insights and talents native to international study and culture that enhance our practice of medicine and biomedical research. 

We live in time when “immigrant” has been assigned a negative and almost subhuman connotation, and diversity has become something to be demonized rather than celebrated. Yet, intuitively, should a top US medical graduate be any more intelligent or driven than a top graduate from the United Kingdom, India, China, or Syria? As American medical physicians, we place the utmost value on our traditions and high standards. We boast an unmatched depth of medical talent spread across our GI divisions and practices and take pride in the way we teach medicine, like no other nation. Now, more than ever, is a time to attract the best and brightest international graduates not to compete with but to complement our remarkable US students. American medicine benefits from their talent and they inspire us to remember and care for diseases in our field that affect the world’s population, not just ours. 

Over 100 years ago, Dr. William Mayo stated “American practice is too broad to be national. It had the scientific spirit, and science knows no country.” Dr. Mayo also said, “Democracy is safe only so long as culture is in the ascendancy.” These lessons apply more than ever today.

David Katzka, MD

Associate Editor

The United States boasts one of the premier health care systems for medical education in the world. Indeed, institutions such as Johns Hopkins, Harvard, and the Mayo Clinic have storied reputations and are recognized names the world over. The United States also stands as a country of remarkable discovery in medicine with an abundance of enormously talented and productive medical scientists. This reputation draws physicians from every corner of the world who dream of studying medicine in our country.

Unfortunately, many US medical institutions, particularly the most prestigious medical centers, lean heavily toward preferential acceptance of US medical school graduates as an indicator of the highest-quality trainees. This historical bias is being further compounded by our current government’s pejorative view of immigrants in general. Will this affect the pool of tomorrow’s stars who will change the course of American medicine?

 

A glance at the list of recent AGA Presidents may yield some insight; over the past 10 years, three of our presidents trained internationally at universities in Malta, Libya, and Germany. This is a small snapshot of the multitude of international graduates in gastroenterology and hepatology who have served as division chiefs, AGA award winners, and journal editors, all now US citizens. This is not to mention the influence of varied insights and talents native to international study and culture that enhance our practice of medicine and biomedical research. 

We live in time when “immigrant” has been assigned a negative and almost subhuman connotation, and diversity has become something to be demonized rather than celebrated. Yet, intuitively, should a top US medical graduate be any more intelligent or driven than a top graduate from the United Kingdom, India, China, or Syria? As American medical physicians, we place the utmost value on our traditions and high standards. We boast an unmatched depth of medical talent spread across our GI divisions and practices and take pride in the way we teach medicine, like no other nation. Now, more than ever, is a time to attract the best and brightest international graduates not to compete with but to complement our remarkable US students. American medicine benefits from their talent and they inspire us to remember and care for diseases in our field that affect the world’s population, not just ours. 

Over 100 years ago, Dr. William Mayo stated “American practice is too broad to be national. It had the scientific spirit, and science knows no country.” Dr. Mayo also said, “Democracy is safe only so long as culture is in the ascendancy.” These lessons apply more than ever today.

David Katzka, MD

Associate Editor

Worldwide, health care is becoming increasingly complex as a result of greater clinical workforce demands, expanded roles and responsibilities, health care system mergers, stakeholder calls for new capabilities, and digital transformation. ^1,2These increasing demands has prompted many health care institutions to place greater focus on the psychological safety of their workforce, particularly in high reliability organizations (HROs). Building a robust foundation for high reliability in health care requires the presence of psychological safety—that is, staff members at all levels of the organization must feel comfortable speaking up when they have questions or concerns.^3,4 Psychological safety can improve the safety and quality of patient care but has not reached its full potential in health care.^5,6 However, there are strategies that promote the widespread implementation of psychological safety in health care organizations.^3-6

PSYCHOLOGICAL SAFETY

The concept of psychological safety in organizational behavior originated in 1965 when Edgar Schein and Warren Bennis, leaders in organizational psychology and management, published their reflections on the importance of psychological safety in helping individuals feel secure in the work environment.^5-7 Psychological safety in the workplace is foundational to staff members feeling comfortable asking questions or expressing concerns without fear of negative consequences.^8,9 It supports both individual and team efforts to raise safety concerns and report near misses and adverse events so that similar events can be averted in the future.⁹ Patients aren’t the only ones who benefit; psychological safety has also been found to promote job satisfaction and employee well-being.¹⁰

THE VETERANS HEALTH ADMINISTRATION JOURNEY

Achieving psychological safety is by no means an easy or comfortable process. As with any organizational change, a multipronged approach offers the best chance of success.^6,9 When the Veterans Health Administration (VHA) began its incremental, enterprise-wide journey to high reliability in 2019, 3 cohorts were identified. In February 2019, 18 US Department of Veterans Affairs (VA) medical centers (VAMCs) (cohort 1) began the process of becoming HROs. Cohort 2 followed in October 2020 and included 54 VAMC. Finally, in October 2021, 67 additional VAMCs (cohort 3) started the process.² During cohort 2, the VA Providence Healthcare System (VAPHCS) decided to emphasize psychological safety at the start of the journey to becoming an HRO. This system is part of the VA New England Healthcare System (VISN 1), which includes VAMCs and clinics in Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont.¹¹ Soon thereafter, the VA Bedford Healthcare System and the VA Connecticut Healthcare System adopted similar strategies. Since then, other VAMCs have also adopted this approach. These collective experiences identified 4 useful strategies for achieving psychological safety: leadership engagement, open communication, education and training, and accountability.

Leadership Engagement

Health care organization leaders play a critical role in making psychological safety happen—especially in complex and constantly changing environments, such as HROs.⁴ Leaders behaviors are consistently linked to the perception of psychological safety at the individual, team, and organizational levels.⁸ It is especially important to have leaders who recognize the views of individuals and team members and encourage staff participation in discussions to gain additional perspectives.^7,8,12 Psychological safety can also be facilitated when leaders are visible, approachable, and communicative.^4,7-9

Organizational practices, policies, and processes (eg, reporting adverse events without the fear of negative consequences) are also important ways that leaders can establish and sustain psychological safety. On a more granular level, leaders can enhance psychological safety by promoting and acknowledging individuals who speak up, regularly asking staff about safety concerns, highlighting “good catches” when harm is avoided, and using staff feedback to initiate improvements.^4,7,13Finally, in the authors’ experience, psychological safety requires clear commitment from leaders at all levels of an organization. Communication should be bidirectional, and leaders should close the proverbial “loop” with feedback and timely follow-up. This encourages and reinforces staff engagement and speaking up behaviors.^2,4,7,13

Open Communication

Promoting an environment of open communication, where all individuals and teams feel empowered to speak up with questions, concerns, and recommendations—regardless of position within the organization—is critical to psychological safety.^4,6,9 Open communication is especially critical when processes and systems are constantly changing and advancing as a result of new information and technology.⁹ Promoting open, bidirectional communication during the delivery of patient care can be accomplished with huddles, tiered safety huddles, leader rounding for high reliability, and time-outs.^2,4,6 These opportunities allow team members to discuss concerns, identify resources that support safe, high-quality care; reflect on successes and opportunities for improvement; and circle back on concerns.^2,6 Open communication in psychologically safe environments empowers staff to raise patient care concerns and is instrumental for improving patient safety, increasing staff job satisfaction, and decreasing turnover.^6,14

Education and Training

Education and training for all staff—from the frontline to the executive level—are essential to successfully implementing the principles and practices of psychological safety.^5-7 VHA training covers many topics, including the origins, benefits, and implementation strategies of psychological safety (Table). Role-playing simulation is an effective teaching format, providing staff with opportunities to practice techniques for raising concerns or share feedback in a controlled environment.⁶ In addition, education should be ongoing; it helps leaders and staff members feel competent and confident when implementing psychological safety across the health care organization.^6,10

Accountability

The final critical strategy for achieving psychological safety is accountability. It is the responsibility of all leadership—from senior leaders to clinical and nonclinical managers—to create a culture of shared accountability.⁵ But first, expectations must be set. Leadership must establish well-defined behavioral expectations that align with the organization’s values. Understanding behavioral expectations will help to ensure that employees know what achievement looks like, as well as how they are being held accountable for their individual actions.^4,5,7 In practical terms, this means ensuring that staff members have the skills and resources to achieve goals and expectations, providing performance feedback in a timely manner, and including expectations in annual performance evaluations (as they are in the VHA).

Consistency is key. Accountability should be the expectation across all levels and services of the health care organization. No staff member should be exempt from promoting a psychologically safe work environment. Compliance with behavioral expectations should be monitored and if a person’s actions are not consistent with expectations, the situation will need to be addressed. Interventions will depend on the type, severity, and frequency of the problematic behaviors. Depending on an organization’s policies and practices, courses of action can range from feedback counseling to employment termination.⁵

A practical matter in ensuring accountability is implementing a psychologically safe process for reporting concerns. Staff members must feel comfortable reporting behavioral concerns without fear of retaliation, negative judgment, or consequences from peers and supervisors. One method for doing this is to create a confidential, centralized process for reporting concerns.⁵

First-Hand Results

VAPHCS has seen the results of implementing the strategies outlined here. For example, VAPHCS has observed a 45% increase in the use of the patient safety reporting system that logs medical errors and near-misses. In addition, there have been improvements in levels of psychological safety and patient safety reported in the annual VHA All Employee Survey, which is conducted annually to gauge workplace satisfaction, culture, climate, turnover, supervisory behaviors, and general workplace perceptions. VAPHCS has shown consistent improvements in 12 patient safety elements scored on a 5-point scale (1, very dissatisfied; 5, very satisfied) (Figure). Notably, employee ratings of error prevention discussed increased from 4.0 in 2022 to 4.3 in 2024. Data collection and analysis are ongoing; more comprehensive findings will be published in the future.

CONCLUSIONS

Health care organizations are increasingly recognizing the importance of psychologically safe workplaces in order to provide safe, high-quality patient care. Psychological safety is a critical tool for empowering staff to raise concerns, ask tough questions, challenge the status quo, and share new ideas for providing health care services. While psychological safety has been slowly adopted in health care, it’s clear that evidence-based strategies can make psychological safety a reality.

Worldwide, health care is becoming increasingly complex as a result of greater clinical workforce demands, expanded roles and responsibilities, health care system mergers, stakeholder calls for new capabilities, and digital transformation. ^1,2These increasing demands has prompted many health care institutions to place greater focus on the psychological safety of their workforce, particularly in high reliability organizations (HROs). Building a robust foundation for high reliability in health care requires the presence of psychological safety—that is, staff members at all levels of the organization must feel comfortable speaking up when they have questions or concerns.^3,4 Psychological safety can improve the safety and quality of patient care but has not reached its full potential in health care.^5,6 However, there are strategies that promote the widespread implementation of psychological safety in health care organizations.^3-6

PSYCHOLOGICAL SAFETY

The concept of psychological safety in organizational behavior originated in 1965 when Edgar Schein and Warren Bennis, leaders in organizational psychology and management, published their reflections on the importance of psychological safety in helping individuals feel secure in the work environment.^5-7 Psychological safety in the workplace is foundational to staff members feeling comfortable asking questions or expressing concerns without fear of negative consequences.^8,9 It supports both individual and team efforts to raise safety concerns and report near misses and adverse events so that similar events can be averted in the future.⁹ Patients aren’t the only ones who benefit; psychological safety has also been found to promote job satisfaction and employee well-being.¹⁰

THE VETERANS HEALTH ADMINISTRATION JOURNEY

Achieving psychological safety is by no means an easy or comfortable process. As with any organizational change, a multipronged approach offers the best chance of success.^6,9 When the Veterans Health Administration (VHA) began its incremental, enterprise-wide journey to high reliability in 2019, 3 cohorts were identified. In February 2019, 18 US Department of Veterans Affairs (VA) medical centers (VAMCs) (cohort 1) began the process of becoming HROs. Cohort 2 followed in October 2020 and included 54 VAMC. Finally, in October 2021, 67 additional VAMCs (cohort 3) started the process.² During cohort 2, the VA Providence Healthcare System (VAPHCS) decided to emphasize psychological safety at the start of the journey to becoming an HRO. This system is part of the VA New England Healthcare System (VISN 1), which includes VAMCs and clinics in Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont.¹¹ Soon thereafter, the VA Bedford Healthcare System and the VA Connecticut Healthcare System adopted similar strategies. Since then, other VAMCs have also adopted this approach. These collective experiences identified 4 useful strategies for achieving psychological safety: leadership engagement, open communication, education and training, and accountability.

Leadership Engagement

Health care organization leaders play a critical role in making psychological safety happen—especially in complex and constantly changing environments, such as HROs.⁴ Leaders behaviors are consistently linked to the perception of psychological safety at the individual, team, and organizational levels.⁸ It is especially important to have leaders who recognize the views of individuals and team members and encourage staff participation in discussions to gain additional perspectives.^7,8,12 Psychological safety can also be facilitated when leaders are visible, approachable, and communicative.^4,7-9

Organizational practices, policies, and processes (eg, reporting adverse events without the fear of negative consequences) are also important ways that leaders can establish and sustain psychological safety. On a more granular level, leaders can enhance psychological safety by promoting and acknowledging individuals who speak up, regularly asking staff about safety concerns, highlighting “good catches” when harm is avoided, and using staff feedback to initiate improvements.^4,7,13Finally, in the authors’ experience, psychological safety requires clear commitment from leaders at all levels of an organization. Communication should be bidirectional, and leaders should close the proverbial “loop” with feedback and timely follow-up. This encourages and reinforces staff engagement and speaking up behaviors.^2,4,7,13

Open Communication

Promoting an environment of open communication, where all individuals and teams feel empowered to speak up with questions, concerns, and recommendations—regardless of position within the organization—is critical to psychological safety.^4,6,9 Open communication is especially critical when processes and systems are constantly changing and advancing as a result of new information and technology.⁹ Promoting open, bidirectional communication during the delivery of patient care can be accomplished with huddles, tiered safety huddles, leader rounding for high reliability, and time-outs.^2,4,6 These opportunities allow team members to discuss concerns, identify resources that support safe, high-quality care; reflect on successes and opportunities for improvement; and circle back on concerns.^2,6 Open communication in psychologically safe environments empowers staff to raise patient care concerns and is instrumental for improving patient safety, increasing staff job satisfaction, and decreasing turnover.^6,14

Education and Training

Education and training for all staff—from the frontline to the executive level—are essential to successfully implementing the principles and practices of psychological safety.^5-7 VHA training covers many topics, including the origins, benefits, and implementation strategies of psychological safety (Table). Role-playing simulation is an effective teaching format, providing staff with opportunities to practice techniques for raising concerns or share feedback in a controlled environment.⁶ In addition, education should be ongoing; it helps leaders and staff members feel competent and confident when implementing psychological safety across the health care organization.^6,10

Accountability

The final critical strategy for achieving psychological safety is accountability. It is the responsibility of all leadership—from senior leaders to clinical and nonclinical managers—to create a culture of shared accountability.⁵ But first, expectations must be set. Leadership must establish well-defined behavioral expectations that align with the organization’s values. Understanding behavioral expectations will help to ensure that employees know what achievement looks like, as well as how they are being held accountable for their individual actions.^4,5,7 In practical terms, this means ensuring that staff members have the skills and resources to achieve goals and expectations, providing performance feedback in a timely manner, and including expectations in annual performance evaluations (as they are in the VHA).

Consistency is key. Accountability should be the expectation across all levels and services of the health care organization. No staff member should be exempt from promoting a psychologically safe work environment. Compliance with behavioral expectations should be monitored and if a person’s actions are not consistent with expectations, the situation will need to be addressed. Interventions will depend on the type, severity, and frequency of the problematic behaviors. Depending on an organization’s policies and practices, courses of action can range from feedback counseling to employment termination.⁵

A practical matter in ensuring accountability is implementing a psychologically safe process for reporting concerns. Staff members must feel comfortable reporting behavioral concerns without fear of retaliation, negative judgment, or consequences from peers and supervisors. One method for doing this is to create a confidential, centralized process for reporting concerns.⁵

First-Hand Results

VAPHCS has seen the results of implementing the strategies outlined here. For example, VAPHCS has observed a 45% increase in the use of the patient safety reporting system that logs medical errors and near-misses. In addition, there have been improvements in levels of psychological safety and patient safety reported in the annual VHA All Employee Survey, which is conducted annually to gauge workplace satisfaction, culture, climate, turnover, supervisory behaviors, and general workplace perceptions. VAPHCS has shown consistent improvements in 12 patient safety elements scored on a 5-point scale (1, very dissatisfied; 5, very satisfied) (Figure). Notably, employee ratings of error prevention discussed increased from 4.0 in 2022 to 4.3 in 2024. Data collection and analysis are ongoing; more comprehensive findings will be published in the future.

CONCLUSIONS

Health care organizations are increasingly recognizing the importance of psychologically safe workplaces in order to provide safe, high-quality patient care. Psychological safety is a critical tool for empowering staff to raise concerns, ask tough questions, challenge the status quo, and share new ideas for providing health care services. While psychological safety has been slowly adopted in health care, it’s clear that evidence-based strategies can make psychological safety a reality.

Worldwide, health care is becoming increasingly complex as a result of greater clinical workforce demands, expanded roles and responsibilities, health care system mergers, stakeholder calls for new capabilities, and digital transformation. ^1,2These increasing demands has prompted many health care institutions to place greater focus on the psychological safety of their workforce, particularly in high reliability organizations (HROs). Building a robust foundation for high reliability in health care requires the presence of psychological safety—that is, staff members at all levels of the organization must feel comfortable speaking up when they have questions or concerns.^3,4 Psychological safety can improve the safety and quality of patient care but has not reached its full potential in health care.^5,6 However, there are strategies that promote the widespread implementation of psychological safety in health care organizations.^3-6

PSYCHOLOGICAL SAFETY

The concept of psychological safety in organizational behavior originated in 1965 when Edgar Schein and Warren Bennis, leaders in organizational psychology and management, published their reflections on the importance of psychological safety in helping individuals feel secure in the work environment.^5-7 Psychological safety in the workplace is foundational to staff members feeling comfortable asking questions or expressing concerns without fear of negative consequences.^8,9 It supports both individual and team efforts to raise safety concerns and report near misses and adverse events so that similar events can be averted in the future.⁹ Patients aren’t the only ones who benefit; psychological safety has also been found to promote job satisfaction and employee well-being.¹⁰

THE VETERANS HEALTH ADMINISTRATION JOURNEY

Achieving psychological safety is by no means an easy or comfortable process. As with any organizational change, a multipronged approach offers the best chance of success.^6,9 When the Veterans Health Administration (VHA) began its incremental, enterprise-wide journey to high reliability in 2019, 3 cohorts were identified. In February 2019, 18 US Department of Veterans Affairs (VA) medical centers (VAMCs) (cohort 1) began the process of becoming HROs. Cohort 2 followed in October 2020 and included 54 VAMC. Finally, in October 2021, 67 additional VAMCs (cohort 3) started the process.² During cohort 2, the VA Providence Healthcare System (VAPHCS) decided to emphasize psychological safety at the start of the journey to becoming an HRO. This system is part of the VA New England Healthcare System (VISN 1), which includes VAMCs and clinics in Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont.¹¹ Soon thereafter, the VA Bedford Healthcare System and the VA Connecticut Healthcare System adopted similar strategies. Since then, other VAMCs have also adopted this approach. These collective experiences identified 4 useful strategies for achieving psychological safety: leadership engagement, open communication, education and training, and accountability.

Leadership Engagement

Health care organization leaders play a critical role in making psychological safety happen—especially in complex and constantly changing environments, such as HROs.⁴ Leaders behaviors are consistently linked to the perception of psychological safety at the individual, team, and organizational levels.⁸ It is especially important to have leaders who recognize the views of individuals and team members and encourage staff participation in discussions to gain additional perspectives.^7,8,12 Psychological safety can also be facilitated when leaders are visible, approachable, and communicative.^4,7-9

Organizational practices, policies, and processes (eg, reporting adverse events without the fear of negative consequences) are also important ways that leaders can establish and sustain psychological safety. On a more granular level, leaders can enhance psychological safety by promoting and acknowledging individuals who speak up, regularly asking staff about safety concerns, highlighting “good catches” when harm is avoided, and using staff feedback to initiate improvements.^4,7,13Finally, in the authors’ experience, psychological safety requires clear commitment from leaders at all levels of an organization. Communication should be bidirectional, and leaders should close the proverbial “loop” with feedback and timely follow-up. This encourages and reinforces staff engagement and speaking up behaviors.^2,4,7,13

Open Communication

Promoting an environment of open communication, where all individuals and teams feel empowered to speak up with questions, concerns, and recommendations—regardless of position within the organization—is critical to psychological safety.^4,6,9 Open communication is especially critical when processes and systems are constantly changing and advancing as a result of new information and technology.⁹ Promoting open, bidirectional communication during the delivery of patient care can be accomplished with huddles, tiered safety huddles, leader rounding for high reliability, and time-outs.^2,4,6 These opportunities allow team members to discuss concerns, identify resources that support safe, high-quality care; reflect on successes and opportunities for improvement; and circle back on concerns.^2,6 Open communication in psychologically safe environments empowers staff to raise patient care concerns and is instrumental for improving patient safety, increasing staff job satisfaction, and decreasing turnover.^6,14

Education and Training

Education and training for all staff—from the frontline to the executive level—are essential to successfully implementing the principles and practices of psychological safety.^5-7 VHA training covers many topics, including the origins, benefits, and implementation strategies of psychological safety (Table). Role-playing simulation is an effective teaching format, providing staff with opportunities to practice techniques for raising concerns or share feedback in a controlled environment.⁶ In addition, education should be ongoing; it helps leaders and staff members feel competent and confident when implementing psychological safety across the health care organization.^6,10

Accountability

The final critical strategy for achieving psychological safety is accountability. It is the responsibility of all leadership—from senior leaders to clinical and nonclinical managers—to create a culture of shared accountability.⁵ But first, expectations must be set. Leadership must establish well-defined behavioral expectations that align with the organization’s values. Understanding behavioral expectations will help to ensure that employees know what achievement looks like, as well as how they are being held accountable for their individual actions.^4,5,7 In practical terms, this means ensuring that staff members have the skills and resources to achieve goals and expectations, providing performance feedback in a timely manner, and including expectations in annual performance evaluations (as they are in the VHA).

Consistency is key. Accountability should be the expectation across all levels and services of the health care organization. No staff member should be exempt from promoting a psychologically safe work environment. Compliance with behavioral expectations should be monitored and if a person’s actions are not consistent with expectations, the situation will need to be addressed. Interventions will depend on the type, severity, and frequency of the problematic behaviors. Depending on an organization’s policies and practices, courses of action can range from feedback counseling to employment termination.⁵

A practical matter in ensuring accountability is implementing a psychologically safe process for reporting concerns. Staff members must feel comfortable reporting behavioral concerns without fear of retaliation, negative judgment, or consequences from peers and supervisors. One method for doing this is to create a confidential, centralized process for reporting concerns.⁵

First-Hand Results

VAPHCS has seen the results of implementing the strategies outlined here. For example, VAPHCS has observed a 45% increase in the use of the patient safety reporting system that logs medical errors and near-misses. In addition, there have been improvements in levels of psychological safety and patient safety reported in the annual VHA All Employee Survey, which is conducted annually to gauge workplace satisfaction, culture, climate, turnover, supervisory behaviors, and general workplace perceptions. VAPHCS has shown consistent improvements in 12 patient safety elements scored on a 5-point scale (1, very dissatisfied; 5, very satisfied) (Figure). Notably, employee ratings of error prevention discussed increased from 4.0 in 2022 to 4.3 in 2024. Data collection and analysis are ongoing; more comprehensive findings will be published in the future.

CONCLUSIONS

Health care organizations are increasingly recognizing the importance of psychologically safe workplaces in order to provide safe, high-quality patient care. Psychological safety is a critical tool for empowering staff to raise concerns, ask tough questions, challenge the status quo, and share new ideas for providing health care services. While psychological safety has been slowly adopted in health care, it’s clear that evidence-based strategies can make psychological safety a reality.