As healthcare systems transition toward Learning Health Systems (LHS), the need for executive-level leadership in systems thinking becomes urgent. This commentary advocates for the institutionalization of a Chief Systems Engineer (CSE) role in hospitals to embed systems engineering (SE) principles within leadership structures, navigate complexity, integrate technology with clinical workflows, and drive continuous organizational learning. Drawing on lessons from high-reliability industries and existing healthcare initiatives, this commentary argues that establishing dedicated SE leadership is essential for achieving both horizontal and vertical integration across clinical, operational, and strategic domains. It outlines the responsibilities of the CSE, aligns them with LHS goals, and offers recommendations for sustained and scalable implementation across healthcare organizations.
{"title":"Embedding Systems Engineering Leadership in Learning Health Systems: The Case for a Chief Systems Engineer in Every Hospital","authors":"Md Doulotuzzaman Xames","doi":"10.1002/lrh2.70054","DOIUrl":"https://doi.org/10.1002/lrh2.70054","url":null,"abstract":"<p>As healthcare systems transition toward Learning Health Systems (LHS), the need for executive-level leadership in systems thinking becomes urgent. This commentary advocates for the institutionalization of a Chief Systems Engineer (CSE) role in hospitals to embed systems engineering (SE) principles within leadership structures, navigate complexity, integrate technology with clinical workflows, and drive continuous organizational learning. Drawing on lessons from high-reliability industries and existing healthcare initiatives, this commentary argues that establishing dedicated SE leadership is essential for achieving both horizontal and vertical integration across clinical, operational, and strategic domains. It outlines the responsibilities of the CSE, aligns them with LHS goals, and offers recommendations for sustained and scalable implementation across healthcare organizations.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145983590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexandra Zingg, L. Ida Tovar, Laura Witte, Kelsey L. Koym, Kyler Godwin
Introduction
Learning health systems leverage clinical data and knowledge to advance healthcare quality. Effective training in informatics concepts and tools is essential for medical trainees to become health system experts and contributors to positive organizational change. The objective of this study is to summarize characteristics of existing clinical informatics training programs and map these to recommended Learning Health System informatics competencies. We aim to answer the following research questions: (1) How are academic medical institutions implementing informatics education initiatives for medical trainees? (2) Are these initiatives implementing recommended informatics competencies? and (3) How effective are these initiatives according to established health professions education evaluation frameworks?
Methods
We searched for literature in the databases Embase, Ovid Medline, and Web of Science. Three researchers independently screened study titles and abstracts. Inclusion criteria were (a) studies with medical students and/or postgraduate medical professionals in the study sample, (b) in an academic medical setting, and (c) describing a clinical informatics curriculum initiative.
Results
We included a total of 27 studies for analysis. Most curricula (n = 16) had the objective of basic informatics knowledge acquisition. Instruction delivery for most (n = 17) included a combination of didactic and practical components. The most common evaluation tool was student self-reported confidence and self-efficacy. All but three of the studies integrated the recommended informatics competency of demonstrating knowledge of clinical information systems such as Electronic Health Records. Most studies (n = 12) reported outcomes related to the Kirkpatrick Level II of Learning.
Conclusion
Gaps remain in the context of leveraging education to pursue Learning Health System endeavors of clinical research, quality improvement, and achieving organizational-level results. Further research on recent education initiatives targeting undergraduate and graduate medical trainees is needed to elevate the rate of clinical informatics education implementation, while simultaneously advocating for standardization in the design and evaluation of these initiatives.
学习型卫生系统利用临床数据和知识来提高医疗质量。信息学概念和工具的有效培训对于医学学员成为卫生系统专家和积极组织变革的贡献者至关重要。本研究的目的是总结现有临床信息学培训计划的特点，并将这些特点映射到推荐的学习卫生系统信息学能力。我们旨在回答以下研究问题：(1)学术医疗机构如何实施医学实习生信息学教育举措？(2)这些举措是否实现了推荐的信息学能力？(3)根据现有的卫生专业教育评估框架，这些举措的效果如何？方法在Embase、Ovid Medline和Web of Science数据库中检索文献。三位研究者独立筛选了研究题目和摘要。纳入标准是(a)在研究样本中有医学生和/或研究生医学专业人员的研究，(b)在学术医学环境中进行的研究，以及(c)描述临床信息学课程倡议。结果共纳入27项研究进行分析。大多数课程（n = 16）以获取基本信息学知识为目标。大多数（n = 17）的教学包括教学和实践成分的结合。最常见的评估工具是学生自我报告的自信和自我效能。除了三个研究外，所有研究都整合了推荐的信息学能力，展示了临床信息系统（如电子健康记录）的知识。大多数研究（n = 12）报告了与柯克帕特里克二级学习相关的结果。结论：在利用教育来追求临床研究、质量改进和实现组织层面结果的学习卫生系统努力的背景下，差距仍然存在。为了提高临床信息学教育的实施率，需要进一步研究近期针对本科和研究生医学培训生的教育举措，同时倡导这些举措的设计和评估的标准化。
{"title":"Clinical Informatics Education to Advance Learning Health Systems: A Scoping Review","authors":"Alexandra Zingg, L. Ida Tovar, Laura Witte, Kelsey L. Koym, Kyler Godwin","doi":"10.1002/lrh2.70050","DOIUrl":"https://doi.org/10.1002/lrh2.70050","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Learning health systems leverage clinical data and knowledge to advance healthcare quality. Effective training in informatics concepts and tools is essential for medical trainees to become health system experts and contributors to positive organizational change. The objective of this study is to summarize characteristics of existing clinical informatics training programs and map these to recommended Learning Health System informatics competencies. We aim to answer the following research questions: (1) How are academic medical institutions implementing informatics education initiatives for medical trainees? (2) Are these initiatives implementing recommended informatics competencies? and (3) How effective are these initiatives according to established health professions education evaluation frameworks?</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We searched for literature in the databases Embase, Ovid Medline, and Web of Science. Three researchers independently screened study titles and abstracts. Inclusion criteria were (a) studies with medical students and/or postgraduate medical professionals in the study sample, (b) in an academic medical setting, and (c) describing a clinical informatics curriculum initiative.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We included a total of 27 studies for analysis. Most curricula (<i>n</i> = 16) had the objective of basic informatics knowledge acquisition. Instruction delivery for most (<i>n</i> = 17) included a combination of didactic and practical components. The most common evaluation tool was student self-reported confidence and self-efficacy. All but three of the studies integrated the recommended informatics competency of demonstrating knowledge of clinical information systems such as Electronic Health Records. Most studies (<i>n</i> = 12) reported outcomes related to the Kirkpatrick Level II of Learning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Gaps remain in the context of leveraging education to pursue Learning Health System endeavors of clinical research, quality improvement, and achieving organizational-level results. Further research on recent education initiatives targeting undergraduate and graduate medical trainees is needed to elevate the rate of clinical informatics education implementation, while simultaneously advocating for standardization in the design and evaluation of these initiatives.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146002079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Samantha Greenberg, Bob Wong, Katherine A. Sward, Kathleen A. Cooney, Jonathan Tward, Andrew Post, Mollie R. Cummins
Introduction
Germline testing and pretest genetic counseling are advised for many cancer patients, yet not all receive these services. Electronic Health Records (EHRs) offer a valuable resource to measure referral to genetic counseling (referral receipt) and uptake (completion of counseling). This study uses EHR data to assess demographic factors influencing genetic counseling referral and uptake among prostate cancer patients, serving as a learning health system model.
Methods
We included prostate cancer patients who met germline testing and counseling criteria at an NCI-designated cancer center from January 1, 2018, to June 30, 2022. Demographic factors—age at diagnosis, race, employment, insurance, and geographic region—were assessed for associations with genetic counseling referral and uptake. Analyses involved descriptive statistics, two-group comparisons, and regression models.
Results
Among 356 prostate cancer patients, only 34.2% received genetic counseling referrals, and of these, 73% completed a counseling visit. Older patients were less likely to receive referrals (OR = 0.93, 95% CI [0.89–0.97]) and complete visits (OR = 0.92, 95% CI [0.87–0.96]). Patients employed full-time were more likely to receive referrals (39.2% vs. 23.1%; p = 0.01), while White (93% vs. 81%; p = 0.047) and rural patients (42.7% vs. 6.1%; p = 0.02) had higher uptake. Insurance status did not significantly affect referral or uptake.
Conclusion
This study demonstrates the potential of EHRs to identify demographic disparities in genetic counseling services. Using a learning health system approach, healthcare institutions can leverage EHR data to design targeted interventions aimed at improving access and reducing disparities in genetic services, ultimately enhancing patient outcomes.
许多癌症患者建议进行生殖系检测和检测前遗传咨询，但并非所有患者都接受这些服务。电子健康记录（EHRs）提供了一个宝贵的资源来衡量转介到遗传咨询（转介接收）和吸收（咨询完成）。本研究使用电子病历数据评估影响前列腺癌患者遗传咨询转诊和接受的人口统计学因素，作为学习卫生系统模型。方法纳入2018年1月1日至2022年6月30日在nci指定的癌症中心符合生殖系检测和咨询标准的前列腺癌患者。人口统计学因素——诊断年龄、种族、就业、保险和地理区域——被评估与遗传咨询转诊和接受的关系。分析包括描述性统计、两组比较和回归模型。结果356例前列腺癌患者中，只有34.2%的人接受了遗传咨询，其中73%的人完成了咨询拜访。老年患者接受转诊（OR = 0.93, 95% CI[0.89-0.97]）和完整就诊（OR = 0.92, 95% CI[0.87-0.96]）的可能性较小。全职工作的患者更容易接受转诊（39.2% vs. 23.1%; p = 0.01），而白人（93% vs. 81%; p = 0.047）和农村患者（42.7% vs. 6.1%; p = 0.02）的接受率更高。保险状况对转诊或吸收没有显著影响。结论：本研究表明电子病历在遗传咨询服务中具有识别人口差异的潜力。使用学习型卫生系统方法，卫生保健机构可以利用电子病历数据设计有针对性的干预措施，旨在改善遗传服务的可及性并减少差异，最终提高患者的治疗效果。
{"title":"Exploring Factors That Impact Genetic Counseling Referral and Uptake Using Learning Health Approaches","authors":"Samantha Greenberg, Bob Wong, Katherine A. Sward, Kathleen A. Cooney, Jonathan Tward, Andrew Post, Mollie R. Cummins","doi":"10.1002/lrh2.70049","DOIUrl":"https://doi.org/10.1002/lrh2.70049","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Germline testing and pretest genetic counseling are advised for many cancer patients, yet not all receive these services. Electronic Health Records (EHRs) offer a valuable resource to measure referral to genetic counseling (referral receipt) and uptake (completion of counseling). This study uses EHR data to assess demographic factors influencing genetic counseling referral and uptake among prostate cancer patients, serving as a learning health system model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We included prostate cancer patients who met germline testing and counseling criteria at an NCI-designated cancer center from January 1, 2018, to June 30, 2022. Demographic factors—age at diagnosis, race, employment, insurance, and geographic region—were assessed for associations with genetic counseling referral and uptake. Analyses involved descriptive statistics, two-group comparisons, and regression models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 356 prostate cancer patients, only 34.2% received genetic counseling referrals, and of these, 73% completed a counseling visit. Older patients were less likely to receive referrals (OR = 0.93, 95% CI [0.89–0.97]) and complete visits (OR = 0.92, 95% CI [0.87–0.96]). Patients employed full-time were more likely to receive referrals (39.2% vs. 23.1%; <i>p</i> = 0.01), while White (93% vs. 81%; <i>p</i> = 0.047) and rural patients (42.7% vs. 6.1%; <i>p</i> = 0.02) had higher uptake. Insurance status did not significantly affect referral or uptake.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This study demonstrates the potential of EHRs to identify demographic disparities in genetic counseling services. Using a learning health system approach, healthcare institutions can leverage EHR data to design targeted interventions aimed at improving access and reducing disparities in genetic services, ultimately enhancing patient outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146002115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Southern California Healthcare Delivery Science Center organizes an annual symposium for a broad audience interested in health innovation.
Aims
The 2024 symposium convened healthcare professionals, researchers, policymakers, and advocates to explore innovative strategies for advancing health equity.
Materials & Methods
Organizers assembled panels of patients, health system leaders, and researchers to present their perspectives on four primary themes: (1) conceptual frameworks for social determinants of health, (2) community-engaged healthcare delivery interventions, (3) healthcare system-based strategies and innovations, and (4) the ethical use of emerging technologies. The agenda also included poster presentations and interactive break-out sessions.
Results
Twenty presenters and facilitators engaged attendees in discussions throughout the day-long symposium. A common theme was understanding social determinants as fundamental, intermediate, and proximate drivers of health inequities. Strategies to bridge these gaps included interdisciplinary collaboration, engaging individuals with lived experience, healthcare system-based and community-centered interventions, ethical use of artificial intelligence, and policy reform.
Discussion
Presentations emphasized the importance of interdisciplinary collaboration, innovation, and policy reform in addressing social determinants of health and achieving equity. They also highlighted the significance of lived experience, community involvement, and data-driven strategies in advancing healthcare delivery science.
Conclusion
The 2024 Healthcare Delivery Science Symposium successfully convened broad stakeholders to exchange ideas and proven strategies for advancing health equity.
{"title":"2024 Healthcare Delivery Science: Innovation and Partnerships for Health Equity Research (DESCIPHER) Symposium","authors":"Amytis Towfighi, Allison Z. Orechwa","doi":"10.1002/lrh2.70042","DOIUrl":"https://doi.org/10.1002/lrh2.70042","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The Southern California Healthcare Delivery Science Center organizes an annual symposium for a broad audience interested in health innovation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>The 2024 symposium convened healthcare professionals, researchers, policymakers, and advocates to explore innovative strategies for advancing health equity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials & Methods</h3>\u0000 \u0000 <p>Organizers assembled panels of patients, health system leaders, and researchers to present their perspectives on four primary themes: (1) conceptual frameworks for social determinants of health, (2) community-engaged healthcare delivery interventions, (3) healthcare system-based strategies and innovations, and (4) the ethical use of emerging technologies. The agenda also included poster presentations and interactive break-out sessions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Twenty presenters and facilitators engaged attendees in discussions throughout the day-long symposium. A common theme was understanding social determinants as fundamental, intermediate, and proximate drivers of health inequities. Strategies to bridge these gaps included interdisciplinary collaboration, engaging individuals with lived experience, healthcare system-based and community-centered interventions, ethical use of artificial intelligence, and policy reform.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Presentations emphasized the importance of interdisciplinary collaboration, innovation, and policy reform in addressing social determinants of health and achieving equity. They also highlighted the significance of lived experience, community involvement, and data-driven strategies in advancing healthcare delivery science.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The 2024 Healthcare Delivery Science Symposium successfully convened broad stakeholders to exchange ideas and proven strategies for advancing health equity.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145983464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paige Coyne, Leah Copeland, Dana Murphy, Ashley Redding, Christine C. Johnson, Karen E. Kippen, Sara Santarossa
Background
Despite growing acknowledgement that patient engagement (PE) in research, quality improvement, and clinical care is important, models showcasing how learning health systems (LHSs) can sustain long-term PE across endeavors remain scant. Henry Ford Health's (HFH) Patient Engaged Research Center (PERC) provides a replicable example by which other LHSs can feasibly sustain/grow PE across research, quality improvement, and clinical care in a more efficient and cohesive manner.
Methods
To support its current infrastructure, PERC obtains financial support from an array of sources, including internal health system funding, external grant funding, and philanthropic support. In addition, PERC has created a Sustainable Funding Framework (SFF) and offers à la carte patient-centered services to further diversify its funding and ensure the sustainability of PE throughout the system. PERC utilizes a four-step SFF to offer expertise in conducting patient-centered research, as well as operational and programming support for PE-related initiatives at HFH and within the broader community. The steps are as follows: awareness/need recognition, intake process (intake form, intake meeting, and invoice), project status (approval or not), and project details/start date. Example services include, but are not limited to, instrument development (surveys, moderator guides for interviews/focus groups), facilitation/transcription (surveys/interviews/focus groups), data analysis and reporting (mixed methods and qualitative), Patient Advisor recruitment and training, development/maintenance of Patient and Family Advisory Councils, placement of patient advisors on committees/councils/projects, and grant writing.
Discussion
PE in research, quality improvement, and clinical care within most health systems is often siloed and disjointed, lacking a sustainable financial or work process model. PERC's SFF provides a promising and replicable example by which LHSs can feasibly sustain and grow PE across research, quality improvement, and clinical care delivery, as well as incorporate this data in a feedback loop to improve all three.
{"title":"The Patient Engaged Research Center's Sustainable Funding Framework: A Path Towards Sustainable Patient Engagement in Care and Research Within a Health System","authors":"Paige Coyne, Leah Copeland, Dana Murphy, Ashley Redding, Christine C. Johnson, Karen E. Kippen, Sara Santarossa","doi":"10.1002/lrh2.70047","DOIUrl":"https://doi.org/10.1002/lrh2.70047","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Despite growing acknowledgement that patient engagement (PE) in research, quality improvement, and clinical care is important, models showcasing how learning health systems (LHSs) can sustain long-term PE across endeavors remain scant. Henry Ford Health's (HFH) Patient Engaged Research Center (PERC) provides a replicable example by which other LHSs can feasibly sustain/grow PE across research, quality improvement, and clinical care in a more efficient and cohesive manner.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To support its current infrastructure, PERC obtains financial support from an array of sources, including internal health system funding, external grant funding, and philanthropic support. In addition, PERC has created a Sustainable Funding Framework (SFF) and offers à la carte patient-centered services to further diversify its funding and ensure the sustainability of PE throughout the system. PERC utilizes a four-step SFF to offer expertise in conducting patient-centered research, as well as operational and programming support for PE-related initiatives at HFH and within the broader community. The steps are as follows: awareness/need recognition, intake process (intake form, intake meeting, and invoice), project status (approval or not), and project details/start date. Example services include, but are not limited to, instrument development (surveys, moderator guides for interviews/focus groups), facilitation/transcription (surveys/interviews/focus groups), data analysis and reporting (mixed methods and qualitative), Patient Advisor recruitment and training, development/maintenance of Patient and Family Advisory Councils, placement of patient advisors on committees/councils/projects, and grant writing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>PE in research, quality improvement, and clinical care within most health systems is often siloed and disjointed, lacking a sustainable financial or work process model. PERC's SFF provides a promising and replicable example by which LHSs can feasibly sustain and grow PE across research, quality improvement, and clinical care delivery, as well as incorporate this data in a feedback loop to improve all three.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146002570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>The publication of Issue 4 marks the completion of Volume 9 of <i>Learning Health Systems</i>. An international, trans-disciplinary, open access publication, the journal has advanced research and scholarship on learning health systems in partnership with our reviewers. With indexing in multiple major sources and an Impact Factor of 2.6, we have achieved a publication milestone that signals a sustainable, positive trajectory. Articles from the journal had more than 142,000 full-text views in 2024. We continue to diversify the offerings of the journal through special issues and special collections, and through the supplemental issue published each year in collaboration with Academy Health.</p><p>We are keenly aware that these achievements would not have happened without the dedicated efforts and insightful comments of all those individuals who accepted invitations to review submitted articles. With busy schedules and full commitments, these individuals found the time and energy to contribute their expertise to our authors to help ensure that their papers met (and often exceeded) the journal's high standards for publication.</p><p>Please accept our sincere gratitude for your outstanding efforts!</p><p>Charles P. Friedman, Editor in Chief</p><p>Nancy Allee, Senior Associate Editor</p><p>Linda Novak, Managing Editor</p><p> <b><i>Learning Health Systems</i> Peer Reviewers</b> </p><p>Note: These are the reviewers for articles published in all four issues of Volume 9 and for all articles currently published and posted online in Early View through September 30, 2025. Reviewers of manuscripts that were not ultimately published are also included in this list.</p><p>Julia Adler-Milstein (United States)</p><p>Aneel Advani (United States)</p><p>Holt Anderson (United States)</p><p>Nate Apathy (United States)</p><p>Cristina Ardura-Garcia (Cambodia)</p><p>Amir Reza Azizian (United States)</p><p>Ross Bailie (Australia)</p><p>Rebecca Baker (United States)</p><p>Timothy Beebe (United States)</p><p>Peter Bower (United Kingdom of Great Britain and Northern Ireland)</p><p>Jeffrey Brown (United States)</p><p>Michael Bushey (United States)</p><p>Michael Cantor (United States)</p><p>Yidan Cao (United States)</p><p>Harold Collard (United States)</p><p>Marisa Conte (United States)</p><p>Theresa Cullen (United States)</p><p>Jennie David (United States)</p><p>Josie Dickerson (United Kingdom of Great Britain and Northern Ireland)</p><p>Anne Douglass (United States)</p><p>Douglas Easterling (United States)</p><p>Davide Ferrari (United Kingdom of Great Britain and Northern Ireland)</p><p>Stephan Fihn (United States)</p><p>Karen Fisher (Australia)</p><p>Allen Flynn (United States)</p><p>Tom Foley (United Kingdom of Great Britain and Northern Ireland)</p><p>Kelly Foltz-Ramos (United States)</p><p>Rachel Forcino (United States)</p><p>Patricia Franklin (United States)</p><p>Nicholas Fusco (United States)</p><p>Melissa Garrido (United States)</p><p>Cheryl G
{"title":"Thanks to our peer reviewers","authors":"","doi":"10.1002/lrh2.70046","DOIUrl":"https://doi.org/10.1002/lrh2.70046","url":null,"abstract":"<p>The publication of Issue 4 marks the completion of Volume 9 of <i>Learning Health Systems</i>. An international, trans-disciplinary, open access publication, the journal has advanced research and scholarship on learning health systems in partnership with our reviewers. With indexing in multiple major sources and an Impact Factor of 2.6, we have achieved a publication milestone that signals a sustainable, positive trajectory. Articles from the journal had more than 142,000 full-text views in 2024. We continue to diversify the offerings of the journal through special issues and special collections, and through the supplemental issue published each year in collaboration with Academy Health.</p><p>We are keenly aware that these achievements would not have happened without the dedicated efforts and insightful comments of all those individuals who accepted invitations to review submitted articles. With busy schedules and full commitments, these individuals found the time and energy to contribute their expertise to our authors to help ensure that their papers met (and often exceeded) the journal's high standards for publication.</p><p>Please accept our sincere gratitude for your outstanding efforts!</p><p>Charles P. Friedman, Editor in Chief</p><p>Nancy Allee, Senior Associate Editor</p><p>Linda Novak, Managing Editor</p><p>\u0000 <b><i>Learning Health Systems</i> Peer Reviewers</b>\u0000 </p><p>Note: These are the reviewers for articles published in all four issues of Volume 9 and for all articles currently published and posted online in Early View through September 30, 2025. Reviewers of manuscripts that were not ultimately published are also included in this list.</p><p>Julia Adler-Milstein (United States)</p><p>Aneel Advani (United States)</p><p>Holt Anderson (United States)</p><p>Nate Apathy (United States)</p><p>Cristina Ardura-Garcia (Cambodia)</p><p>Amir Reza Azizian (United States)</p><p>Ross Bailie (Australia)</p><p>Rebecca Baker (United States)</p><p>Timothy Beebe (United States)</p><p>Peter Bower (United Kingdom of Great Britain and Northern Ireland)</p><p>Jeffrey Brown (United States)</p><p>Michael Bushey (United States)</p><p>Michael Cantor (United States)</p><p>Yidan Cao (United States)</p><p>Harold Collard (United States)</p><p>Marisa Conte (United States)</p><p>Theresa Cullen (United States)</p><p>Jennie David (United States)</p><p>Josie Dickerson (United Kingdom of Great Britain and Northern Ireland)</p><p>Anne Douglass (United States)</p><p>Douglas Easterling (United States)</p><p>Davide Ferrari (United Kingdom of Great Britain and Northern Ireland)</p><p>Stephan Fihn (United States)</p><p>Karen Fisher (Australia)</p><p>Allen Flynn (United States)</p><p>Tom Foley (United Kingdom of Great Britain and Northern Ireland)</p><p>Kelly Foltz-Ramos (United States)</p><p>Rachel Forcino (United States)</p><p>Patricia Franklin (United States)</p><p>Nicholas Fusco (United States)</p><p>Melissa Garrido (United States)</p><p>Cheryl G","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145375198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Charles P. Friedman, Sarah M. Greene, Joshua C. Rubin
<p>The description of each feature, to follow, is accompanied by at least one citation, out of multitudes that are eligible to be referenced. A fully referenced paper goes beyond the scope of this commentary; but in almost every case, the works referenced below point to a more complete set of citations supporting the assertions offered here.</p><p>There are many reasons why innovations are adopted, but the process typically begins when the idea behind the innovation attracts the attention of potential adopters [<span>2</span>]. Beginning with the 2007 seminal workshop report from the (then) Institute of Medicine [<span>3</span>] with 574 citations and later with the Friedman et al. 2010 article cited 622 times [<span>4</span>] and Greene et al. cited 430 times [<span>5</span>], the concepts and methods associated with Learning Health Systems have garnered significant attention. Gro wth of the LHS, both as a concept and set of methods, is difficult to quantify, but the two indices presented in Figure 1 offer evidence of steadily increasing attention. The first is the number of retrievals through a PubMed search for articles with the title or abstract containing “Learning Health Systems” or “Learning Healthcare Systems.” (The actual number of relevant publications is likely much higher since the search as conducted retrieved only 52% of the articles published in this journal.) The second is the number of full-text downloads of articles published in <i>Learning Health Systems</i>, which is fully online.</p><p>In the authors' own subjective experience with LHS, dating back to 2009, no one has said that LHS is a bad idea. One conjecture about the appeal of the idea goes to its name: very few people oppose “learning” and almost no one opposes “health.” While “system” is a somewhat more controversial concept, when combined with the other two terms, “system” takes on a more positive connotation. Indeed, the challenge and the corresponding opportunity associated with realizing learning and transformation at the system level can attract diverse thinkers who recognize that system problems demand system solutions.</p><p>There are many descriptions of “improvement cycles” in LHS; but, to a reasonable approximation, all such models include transitional elements of practice to data, data to knowledge (evidence), and knowledge (evidence) back to practice. While cyclical activity to drive improvement is hardly a new concept, the LHS brings inclusion and co-creation—similarly referred to as co-production—to the level of imperatives. An extensive literature describes the hyper-collaborative nature of Learning Health Systems [<span>11</span>], and a scoping review [<span>12</span>] offers examples of how LHS models incorporate the related concept of co-production. The imperative for inclusion, however, derives primarily from common sense. It is intuitively obvious that including everyone with a stake in a health problem in learning communities that are dedicated to
接下来的每个特征的描述都至少有一个引用，这些引用来自于有资格被引用的众多引用。完全引用的论文超出了本评论的范围；但在几乎所有情况下，下面引用的作品都指向了一组更完整的引用，以支持这里提供的断言。创新被采用的原因有很多，但这个过程通常始于创新背后的想法吸引了潜在采用者的注意。从2007年（当时）医学研究所的开创性研讨会报告[3]（574次引用）开始，后来Friedman等人2010年的文章被引用了622次[5]，Greene等人被引用了430次[5]，与学习健康系统相关的概念和方法获得了极大的关注。LHS的增长，无论是作为一个概念还是一套方法，都很难量化，但图1中的两个指标提供了人们对其关注稳步增加的证据。第一个是通过PubMed搜索标题或摘要包含“学习卫生系统”或“学习卫生系统”的文章的检索次数。（相关出版物的实际数量可能要高得多，因为进行的搜索只检索了该期刊上发表的52%的文章。）第二个指标是发表在《学习卫生系统》（Learning Health Systems）上的文章全文下载的数量，该杂志完全在线。在作者自己2009年对LHS的主观体验中，没有人说LHS是一个坏主意。关于这一理念的吸引力，有一种猜测来自于它的名字：很少有人反对“学习”，几乎没有人反对“健康”。虽然“系统”是一个更有争议的概念，但当与其他两个术语结合在一起时，“系统”具有更积极的内涵。实际上，在系统级别实现学习和转换的挑战和相应的机会可以吸引认识到系统问题需要系统解决方案的不同思考者。在LHS中有许多关于“改进周期”的描述；但是，在合理的近似下，所有这些模型都包括实践到数据、数据到知识（证据）和知识（证据）再到实践的过渡元素。虽然推动改进的周期性活动并不是一个新概念，但LHS将包容和共同创造（类似地称为共同生产）提升到了势在必行的水平。大量文献描述了学习型卫生系统[11]的高度协作性质，范围审查[12]提供了LHS模型如何纳入合作生产相关概念的示例。然而，包容的必要性主要来自常识。显而易见的是，将每个与健康问题有利害关系的人纳入致力于解决该问题的学习社区，将导致更有可能实施和有效的解决方案。这一基本理念反映在上述LHS的几个核心价值观和承诺中。强调基础设施作为学习型卫生系统的关键组成部分出现在[13]概念的早期。以一套全面的社会技术共享服务的形式大力强调基础设施，这是保健服务与其他改善保健和护理方法的一个重要区别[13,14]。可以说，基础设施使LHS成为一个系统，而不是一组脱节或松散连接的健康改善项目。与LHS作为一个系统的概念相一致，LHS基础设施可以描述为一组10个社会技术服务，如表2所示，每个服务主要支持改进周期[15]的特定阶段。基础设施通过由专业人员提供服务，使LHS具有弹性，这些人员有目的地拥有冗余的技能；它通过增强服务的潜力使适应性增强，从而使所有改进活动受益；通过将新的改进工作连接到这些服务的低边际成本，它提供了可伸缩性。对构成完整基础设施的综合服务进行协调，也确保每项服务的工作始终以任务为重点，尽量减少与其他服务的冗余。由包容性社区指导的改进周期将收集和分析组织、组织网络或管辖区域边界的内部数据。这些数据及其分析结果将产生适合当地情况的证据。然后通过审查和整合其他地方进行的研究所产生的证据来补充这一内部证据[b]。通常情况下，地方研究是利用机构资源进行的，并采用较小的样本，从而能够更迅速地进行研究。 外部研究通常由拨款支持，使用更大的样本。虽然外部研究通常需要更长的时间才能完成，但他们的结果如果发表，在一个越来越多地提供公开获取已发表知识的世界里，是很容易获得的。反映当地情况的快速开展的研究和反映其他地方现有情况的已发表的研究强有力地结合在一起，使学习型社区能够迅速产生干预措施，并确信这些干预措施是基于现有的最佳证据。人工智能方法的潜力，如果经过深思熟虑和合乎道德的实施，将深刻改善健康和护理得到广泛认可[17,18]。然而，目前体现这种潜力的人工智能模型的创建速度远远大于它们的实施速度。打个比方，就像飞机离开地面比安全着陆容易得多一样，开发一个人工智能模型比以一种真正改善健康的方式部署它要容易得多。由于LHS改进周期包括发现和实施，如表2所示，成熟的LHS基础设施提供的服务提供了使人工智能模型“安全落地”所需的条件，即有效地部署到促进健康和提供保健的环境中。虽然一些人工智能支持者可能会认为，先进的人工智能将为学习型卫生系统提供另一种选择，但更现实的情况是，人工智能和LHS可以共同成熟，并相互加强。关于创新采用的文献提醒我们，小规模的“可试验”创新更有可能被成功采用。学习型卫生系统可以通过“有机渗透”这一过程进行扩展，而不是“接种”，后者需要大量的前期资源投入。LHS可以通过少量的改进周期扎根，每个周期都是由不同的个人发起的，他们都有解决健康问题的热情。同时，原始的基础设施可以与现有的服务拼凑在一起。成功的经验将开始改变文化。这个过程将产生双向的积极反馈，如图2所示，其中任何一个元素的积极变化将导致其他两个元素的积极变化。关于什么是学习型卫生系统的共识仍然处于高度抽象的水平。目前，至少有四种不同的LHS[19]方法，至少作为一个目标，可以满足最初的IOM定义。作为复杂的自适应系统，这些方法将不可避免地进化并可能产生分支。虽然有些人可能会要求LHS的特异性，但这可能被证明是徒劳的追求。当前构建能力/成熟度模型的努力[21,22]可能会对LHS的一种类型或方法产生令人满意的特异性水平，但总会有其他类型或方法。展望未来，LHS将变得更加善于学习和应用知识；这就是“元学习”。通过“学习如何更好地学习”，并弄清楚如何摒弃和取消那些不起作用的东西，他们将增强自己改善健康的能力。这将通过自我评估，通过专业协会继续发展LHS亲缘团体的会议讨论，以及通过同一组织成员之间的非正式讨论来进行内省。随着LHS的成熟，如图2所示的机制随着时间的推移而运行，改进周期将变得越来越多。重点改进将从特殊活动变为日常活动。在这一点上，机构、网络或地区将从每个人的经验中学习b[24]。支持改进周期的社会技术基础设施将得到发展，以支持日常学习，该机构的文化将与核心价值和承诺保持一致。那些最先引起先驱者想象力的想法将继续引起后来者的想象力。综上所述，以上列举的10个理由构成了一个令人信服的“为什么”。那些寻求在自己的环境中应用这一模型的人可以使用这些原因作为高层路线图，将组织领导人带到谈判桌上，并帮助将LHS与其他将知识转化为行动的方法区分开来。通过LHS方法，Mate及其同事所引用的短暂成功和渐进式改进可以变得持久和具有变革性。作者声明无利益冲突。
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Joyce R. Javier, Anne T. Vo, Gery W. Ryan, Craig W. Robbins, Heidi D. Nelson, Ashwini Lakshmanan
Background
Ensuring patient safety (PS) and implementing quality improvement (QI) are well-recognized functions of healthcare delivery systems and fall within physicians' scope of practice. How to effectively introduce equity-centered PS and QI concepts into an already overloaded undergraduate medical education curriculum is a challenge.
Methods
This report describes our experiences at the Kaiser Permanente Bernard J. Tyson School of Medicine (KPSOM), a new medical school, and how we have developed our Quality Improvement and Patient Safety curriculum within a larger institutional environment where equity and social justice are highly valued.
Results
Integrating health systems science into undergraduate medical education and concepts related to health equity requires intentional curricular design and ongoing adaptation. Lessons learned include: (1) importance of using the Basic Improvement Framework as an educational anchor; (2) understanding the value of integration across curricular phases; and (3) creating a dedicated space for curricular refinement over time.
Conclusions
Medical schools and health systems aiming to strengthen their health systems science curricula may find value in implementing structured approaches—such as the Basic Improvement Framework utilized at KPSOM—to promote early and meaningful engagement with systems-based concepts, especially health equity, throughout learners’ training.
背景：确保患者安全（PS）和实施质量改进（QI）是医疗保健服务系统公认的功能，属于医生的实践范围。如何有效地将以公平为中心的PS和QI概念引入已经超负荷的本科医学教育课程是一个挑战。本报告描述了我们在Kaiser Permanente Bernard J. Tyson医学院（KPSOM）的经验，这是一所新的医学院，以及我们如何在一个更大的机构环境中发展我们的质量改进和患者安全课程，公平和社会正义是高度重视的。结果将卫生系统科学融入本科医学教育和卫生公平相关概念需要有意识的课程设计和持续的适应。经验教训包括：(1)使用基本改进框架作为教育锚的重要性；(2)理解跨课程阶段整合的价值；(3)随着时间的推移，为课程的完善创造一个专门的空间。旨在加强其卫生系统科学课程的医学院和卫生系统可能会发现实施结构化方法的价值，例如kpsom使用的基本改进框架，以促进学习者在整个培训过程中早期和有意义地参与基于系统的概念，特别是卫生公平。
{"title":"Bridging Health Equity, Quality Improvement, and Patient Safety: A Framework for Medical Student Education","authors":"Joyce R. Javier, Anne T. Vo, Gery W. Ryan, Craig W. Robbins, Heidi D. Nelson, Ashwini Lakshmanan","doi":"10.1002/lrh2.70045","DOIUrl":"https://doi.org/10.1002/lrh2.70045","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Ensuring patient safety (PS) and implementing quality improvement (QI) are well-recognized functions of healthcare delivery systems and fall within physicians' scope of practice. How to effectively introduce equity-centered PS and QI concepts into an already overloaded undergraduate medical education curriculum is a challenge.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This report describes our experiences at the Kaiser Permanente Bernard J. Tyson School of Medicine (KPSOM), a new medical school, and how we have developed our Quality Improvement and Patient Safety curriculum within a larger institutional environment where equity and social justice are highly valued.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Integrating health systems science into undergraduate medical education and concepts related to health equity requires intentional curricular design and ongoing adaptation. Lessons learned include: (1) importance of using the Basic Improvement Framework as an educational anchor; (2) understanding the value of integration across curricular phases; and (3) creating a dedicated space for curricular refinement over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Medical schools and health systems aiming to strengthen their health systems science curricula may find value in implementing structured approaches—such as the Basic Improvement Framework utilized at KPSOM—to promote early and meaningful engagement with systems-based concepts, especially health equity, throughout learners’ training.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145983751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Charis X. Xie, Patricia D. Franklin, Theresa L. Walunas, Rinad S. Beidas
The digital transformation of healthcare has generated unprecedented volumes of routine clinical data, enabling health system leaders, including quality improvement (QI) efforts, to optimize care using real-time analytics. However, health system QI typically focuses on changes within localized environments; it is often limited in its ability to address systemic barriers or scale evidence-based strategies across diverse settings. Thoughtful integration of implementation science (IS) approaches addresses this gap by systematically integrating interventions into diverse practice settings and defining generalizable implementation strategies. These attributes position IS as a cornerstone of learning health systems (LHS), which strive for population-wide improvements through continuous, data-driven learning. Within this paradigm, randomized implementation trials provide the gold standard for comparing and optimizing implementation strategies. By leveraging routine data, these trials generate causal evidence on the effectiveness of different approaches and offer rigorous insights for health system decision-makers. In this viewpoint, we highlight data-driven implementation trials as catalysts for rigorous and scalable health system transformation. Specifically, we articulate the value proposition of data-driven implementation trials, examine their transformative potential toward learning health systems, and outline persistent challenges. Drawing on experiences from the UK and the US in large health systems, we propose actionable recommendations to optimize infrastructure, foster collaboration, secure health system-level commitments, and cultivate a culture that is grounded in IS while augmenting the impact of QI—critical steps toward realizing scalable, equitable healthcare innovation.
{"title":"Data-Driven Implementation Trials: Realizing Their Full Potential in Achieving the Promise of Learning Health Systems","authors":"Charis X. Xie, Patricia D. Franklin, Theresa L. Walunas, Rinad S. Beidas","doi":"10.1002/lrh2.70043","DOIUrl":"https://doi.org/10.1002/lrh2.70043","url":null,"abstract":"<p>The digital transformation of healthcare has generated unprecedented volumes of routine clinical data, enabling health system leaders, including quality improvement (QI) efforts, to optimize care using real-time analytics. However, health system QI typically focuses on changes within localized environments; it is often limited in its ability to address systemic barriers or scale evidence-based strategies across diverse settings. Thoughtful integration of implementation science (IS) approaches addresses this gap by systematically integrating interventions into diverse practice settings and defining generalizable implementation strategies. These attributes position IS as a cornerstone of learning health systems (LHS), which strive for population-wide improvements through continuous, data-driven learning. Within this paradigm, randomized implementation trials provide the gold standard for comparing and optimizing implementation strategies. By leveraging routine data, these trials generate causal evidence on the effectiveness of different approaches and offer rigorous insights for health system decision-makers. In this viewpoint, we highlight data-driven implementation trials as catalysts for rigorous and scalable health system transformation. Specifically, we articulate the value proposition of data-driven implementation trials, examine their transformative potential toward learning health systems, and outline persistent challenges. Drawing on experiences from the UK and the US in large health systems, we propose actionable recommendations to optimize infrastructure, foster collaboration, secure health system-level commitments, and cultivate a culture that is grounded in IS while augmenting the impact of QI—critical steps toward realizing scalable, equitable healthcare innovation.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145983890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kayla R. Mehl, Stephanie R. Morain, Jeremy Sugarman
Background
Pragmatic clinical trials (PCTs) offer insights into real-world intervention effectiveness, but they may involve challenging ethical issues. Empirical ethics research may inform deliberations about them.
Methods
We conducted a scoping review of empirical ethics research related to PCTs. This involved searching in PubMed and Embase, charting findings, and analyzing themes to identify trends and gaps.
Results
Eighty-two publications were included, which examined a vast number of issues encompassing 22 themes. The five most prominent were: consent/disclosure; risk assessment; trust and transparency; burdens, barriers, and costs; and engagement. Written consent is often impractical, prompting interest in opt-out or general notification approaches. Challenges in risk assessment include variability in defining minimal risk, thereby complicating regulatory determinations for the appropriateness of particular participant protections and communicating research risks. Trust-building practices, such as result-sharing and data-use disclosure, can foster confidence. Stakeholder engagement can address logistical barriers, improve recruitment, and align research with participant needs. Time, financial, and regulatory burdens are significant obstacles to implementing PCTs.
Conclusion
There has been progress in understanding many ethical issues encountered in PCTs, including appropriately navigating alternatives to obtaining written informed consent, trust-building, and the operational role of stakeholder engagement. However, critical gaps remain, with research concentrated in Western contexts and reliant on surveys and hypothetical scenarios, limiting generalizability and real-world insights. Addressing these gaps with geographically inclusive studies, innovative methods, and nested empirical work will be important for more comprehensively understanding the ethical issues in PCTs and developing appropriate approaches to mitigating them.
{"title":"Empirical research related to the ethics of pragmatic clinical trials: A scoping review","authors":"Kayla R. Mehl, Stephanie R. Morain, Jeremy Sugarman","doi":"10.1002/lrh2.70041","DOIUrl":"https://doi.org/10.1002/lrh2.70041","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Pragmatic clinical trials (PCTs) offer insights into real-world intervention effectiveness, but they may involve challenging ethical issues. Empirical ethics research may inform deliberations about them.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a scoping review of empirical ethics research related to PCTs. This involved searching in PubMed and Embase, charting findings, and analyzing themes to identify trends and gaps.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Eighty-two publications were included, which examined a vast number of issues encompassing 22 themes. The five most prominent were: consent/disclosure; risk assessment; trust and transparency; burdens, barriers, and costs; and engagement. Written consent is often impractical, prompting interest in opt-out or general notification approaches. Challenges in risk assessment include variability in defining minimal risk, thereby complicating regulatory determinations for the appropriateness of particular participant protections and communicating research risks. Trust-building practices, such as result-sharing and data-use disclosure, can foster confidence. Stakeholder engagement can address logistical barriers, improve recruitment, and align research with participant needs. Time, financial, and regulatory burdens are significant obstacles to implementing PCTs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>There has been progress in understanding many ethical issues encountered in PCTs, including appropriately navigating alternatives to obtaining written informed consent, trust-building, and the operational role of stakeholder engagement. However, critical gaps remain, with research concentrated in Western contexts and reliant on surveys and hypothetical scenarios, limiting generalizability and real-world insights. Addressing these gaps with geographically inclusive studies, innovative methods, and nested empirical work will be important for more comprehensively understanding the ethical issues in PCTs and developing appropriate approaches to mitigating them.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146002077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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