Learning Health Systems最新文献

{"title":"Correction to \"Learning Health Systems Symposium: Charting the Future of Saskatchewan Healthcare\".","authors":"","doi":"10.1002/lrh2.70081","DOIUrl":"https://doi.org/10.1002/lrh2.70081","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1002/lrh2.70060.].</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 ","pages":"e70081"},"PeriodicalIF":2.6,"publicationDate":"2026-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13111144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784591","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}

{"title":"Enhancing Learning Health Systems in Primary and Community Care: Contributions of NHS Library and Knowledge Specialists.","authors":"Alison Day, Louise Goswami","doi":"10.1002/lrh2.70079","DOIUrl":"https://doi.org/10.1002/lrh2.70079","url":null,"abstract":"<p><strong>Context: </strong>Learning communities driving the data-knowledge-practice learning cycle are at the core of learning health systems (LHS). With the right team in place, including knowledge management expertise, LHS accelerates improvements, delivering on the healthcare quadruple aim and health equity. Within the National Health Service (NHS) in England, knowledge management and librarian expertise exist mainly within acute hospital settings. This makes it harder for those developing LHS in community health settings to benefit from this expertise.</p><p><strong>Experience report methods and results: </strong>Three proof-of-concept studies are described in this experience report, and results present the learning from surveys, after-action reviews, and impact case studies. Results explore the value of placing an embedded knowledge specialist alongside primary healthcare professionals; discovery work about partnership approaches to delivering knowledge and library services within integrated care systems; and work in partnership with public libraries helping citizens to navigate digital health so they can be informed partners in LHS.</p><p><strong>Discussion: </strong>The three initiatives demonstrate the role of knowledge specialists within LHS teams to accelerate knowledge into practice. Knowledge specialists curate collections of biomedical knowledge and present research in decision-ready formats to expedite evidence-informed decision-making, underpinning knowledge into action. In addition, they encourage tacit knowledge sharing and help establish learning communities and partnerships. However, traditional structures in England raise operational barriers which prevent this from happening at scale and suggestions are made to redress this inequity.</p><p><strong>Conclusion: </strong>Knowledge management specialist roles contribute to the creation of learning cultures within community settings, acting as knowledge intermediaries, enabling LHS to thrive. The aim of sharing this learning is to encourage others developing LHS to consider how they can leverage the expertise of health librarians and knowledge specialists to put in place one of the building blocks of a successful LHS.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":"e70079"},"PeriodicalIF":2.6,"publicationDate":"2026-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147784347","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}

{"title":"Hand in Glove: Health Equity and Learning Health Systems.","authors":"Susan Lacey Bryant, Gerald J Perry, Terrie R Wheeler","doi":"10.1002/lrh2.70078","DOIUrl":"10.1002/lrh2.70078","url":null,"abstract":"","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":"e70078"},"PeriodicalIF":2.6,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13086554/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147723926","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}

{"title":"Twenty-First Century Data Systems: Evolving Cancer Registries to a Learning Health System.","authors":"Peter P Yu, W Scott Campbell, Eric B Durbin, Lawrence N Shulman, Jeremy L Warner","doi":"10.1002/lrh2.70080","DOIUrl":"https://doi.org/10.1002/lrh2.70080","url":null,"abstract":"<p><strong>Introduction: </strong>Oncology is a data-rich environment reflecting the increasing incidence of cancer in the US aging population, transformation of cancer into a chronic disease due to advances in treatment, and the emergence of new data categories such as genomics. Concomitantly, healthcare systems are challenged to meet regulatory and voluntary reporting of cancer data to support government, quality certification, research and strategic partnership needs.</p><p><strong>Materials and methods: </strong>The National Academies of Science, Engineering, and Medicine organized a workshop entitled \"Enabling 21st-century applications for cancer surveillance through enhanced registries and beyond\" with representation from NCI Comprehensive Cancer Centers, oncology and medical informatics professional societies, industry, CDC, NCI, and patient advocacy groups.</p><p><strong>Results: </strong>The proliferation of cancer registries has resulted in heterogeneity in data vocabularies and data transport standards. Federal policy is complementing private initiatives to modernize cancer data architecture that would support a Learning Health System. However, business models are needed to provide sustained investments in data infrastructure.</p><p><strong>Conclusion: </strong>A computational approach to cancer registries would set the stage for interoperability and data sharing within a learning health ecosystem. Healthcare systems need to invest in their data infrastructure to improve data quality and adaptation of new data sources such as genomics and wearables. The ecosystem must evolve business models to sustain these investments.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":"e70080"},"PeriodicalIF":2.6,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13078859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147692889","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}

{"title":"Inpatient Recovery of Function After Knee Replacement: A Longitudinal Evaluation Across Four Sequential Care Pathway Redesigns.","authors":"Jelmer Jager, Wim van Houtert, Wim P Krijnen, Richard Bimmel, Nico L U van Meeteren, Thomas J Hoogeboom, Reinier P Akkermans, Geert van der Sluis","doi":"10.1002/lrh2.70076","DOIUrl":"https://doi.org/10.1002/lrh2.70076","url":null,"abstract":"<p><strong>Introduction: </strong>Inpatient recovery of activities (IRoA) is a key outcome after total knee replacement (TKR), reflecting the patient's ability to regain independence. Preoperative prediction can support shared decision-making and care planning, but its accuracy may decline as healthcare contexts evolve. This study evaluated: Stability of the predictors used for estimating IRoA across sequential care pathway redesigns.Temporal transportability of prediction models for IRoA over different time periods.</p><p><strong>Methods: </strong>A retrospective longitudinal cohort study was conducted at Nij Smellinghe Hospital (the Netherlands) using routine clinical data from 1853 patients opting for TKR surgery between 2009 and 2020. Four consecutive care pathway periods were studied: Joint-Care, Function Tailored, Fast Track, and Prehabilitation. IRoA was assessed using the modified Iowa Levels of Assistance Scale (mILAS). Multinomial regression and minimum Akaike Information Criterion (AIC) guided selection of preoperative predictors (e.g., age, ASA score, TUG, DEMMI). Model performance and temporal transportability were evaluated across periods.</p><p><strong>Results: </strong>Predictor stability was limited across care pathways. Age was consistently retained in all periods for both slow and regular recovery groups. DEMMI was retained in all but the Function Tailored period, while BMI was not retained in any model. ASA and ISAR were variably retained, mainly in later periods and predominantly for slow recovery. TUG was inconsistently retained and primarily selected in earlier periods. Model performance declined when models were applied to later care pathways, with predicted correct proportions decreasing from 0.70 to 0.59, 0.66 to 0.43, and 0.51 to 0.36 across successive transitions. The Prehabilitation model achieved a predicted correct proportion of 0.65 within its own period.</p><p><strong>Conclusions: </strong>Prediction of IRoA after TKR is sensitive to changes in care pathways. Predictor relevance and model performance varied over time, limiting temporal transportability. Ongoing model updating and local recalibration are required to maintain clinical usefulness in evolving care contexts.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":"e70076"},"PeriodicalIF":2.6,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13074427/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147692849","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}

{"title":"Inishowen Child and Adolescent Mental Health Service: Developing a Learning Health Microsystem","authors":"Tom Foley,&nbsp;Bennie Steyn,&nbsp;Eoin Fitzgerald,&nbsp;Liesl Roos,&nbsp;Areej Gazzaz,&nbsp;Mohamed Mohamed,&nbsp;Jumanah Al Ibrahim,&nbsp;Amr Abu Shehab,&nbsp;Gavin McBridge,&nbsp;Aoife Robb,&nbsp;Sheila Gill,&nbsp;Caoimhe McDaid,&nbsp;Breidge McGarvey,&nbsp;Jessica Du Preez,&nbsp;Tom Sharpe,&nbsp;Paige Leigh McDonald,&nbsp;Sue Lacey Bryant,&nbsp;Fiona McNicholas","doi":"10.1002/lrh2.70077","DOIUrl":"10.1002/lrh2.70077","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Learning health systems (LHSs) offer a model for continuous improvement in complex, real-world clinical environments. While widely described internationally, little evidence exists regarding their implementation within Irish mental health services. Inishowen child and adolescent mental health service (CAMHS), a small rural microsystem with limited digital maturity, sought to apply a LHS framework through the creation of a learning community, manual data collection and a living standard operating policies and procedures (SOPP) manual.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This study examines the development and early outcomes of this locally driven learning health microsystem, taking wait times as an exemplar. It explores the organizational complexity using the non-adoption, abandonment, scale-up, spread and sustainability (NASSS) framework.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A descriptive case-study design was used. Data were drawn from routine audits, caseload analysis, patient experience measures, referral metrics, and outputs from the learning community. The NASSS framework was applied to analyze complexity across conditions, technology, adopters, organization, wider system influences, and the capacity for embedding and adaptation over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Implementation of LHS processes was feasible despite paper-based records and minimal infrastructure. Between 2020 and 2024, the caseload reduced by half; from 2023, 100% of young people were seen within 3 months, and maximum waiting times fell from 743 days in 2020 to 49 days in 2025. Patient and family experience remained highly positive. Several elements, including the SOPP and youth engagement, became embedded, whereas continuous data collection remained vulnerable to staff turnover and workload pressures.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>A learning health microsystem can emerge in digitally immature, resource-constrained CAMHS settings. Inishowen CAMHS demonstrates measurable service improvements and offers a replicable early model for LHS development in Irish mental health care. Future work should focus on scaling this microsystem approach and spreading nationally, strengthening digital infrastructure to support faster, more reliable learning cycles and to sustain improvements over time.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13052015/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634752","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}

{"title":"Connecting Homeless and Criminal Justice-Involved Veterans to Primary Care: Process and Outcomes of a Learning Health System Activity","authors":"Jack Tsai,&nbsp;Austin Lampros,&nbsp;Faustine Huynh Arzadon,&nbsp;Anne Dunn,&nbsp;Deborah Lee,&nbsp;Sean Clark,&nbsp;Thomas P. O'Toole","doi":"10.1002/lrh2.70069","DOIUrl":"https://doi.org/10.1002/lrh2.70069","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The Department of Veterans Affairs (VA) undertook an initiative to ensure veterans enrolled in its national supported housing program or its criminal justice outreach program were connected to primary care for treatment and preventive healthcare. This article describes the process and outcomes of a learning health system initiative to empanel homeless and justice-involved veterans in primary care in the largest, integrated healthcare system in the United States.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>At the start of 2024, the Connecting Vulnerable Veterans to Care (CVVC) workgroup was created with interdisciplinary national, regional, and local VA leadership to work toward the goal of increasing the number of veterans in the Housing and Urban Development-VA Supportive Housing (HUD-VASH) program and the Veterans Justice Outreach (VJO) program who were empaneled in VA primary care. Within the CVVC workgroup, weekly meetings were organized with stakeholders, data dashboards were created and used to develop target outcomes, monitor progress, share organizational learning and knowledge, and form a culture of continuous inquiry and quality improvement. Participants were 142 VA medical centers with HUD-VASH and VJO programs. The main outcome measure was the proportion of veterans empaneled in VA primary care.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>During this initiative, nearly all VA medical centers reached targeted benchmarks of 85% enrollment in primary care among veterans in the HUD-VASH program and the majority of VA medical centers reached the goal of 80% enrollment in primary care among veterans in the VJO program. More specifically, among the 142 VA medical centers, 56% showed increased primary care enrollment in their HUD-VASH program and 70% showed increased primary care enrollment in their VJO program.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This work illustrates how a learning health system initiative in a large, integrated national healthcare system supports activities that were associated with improved local engagement in primary care services.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70069","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147615186","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}

{"title":"Evaluating a National Training Program for Health Services and Policy Research: Building Capacity for Learning Health Systems","authors":"Elizabeth Oddone Paolucci,&nbsp;Natasha Gallant,&nbsp;Elena Lopatina,&nbsp;Kim McGrail,&nbsp;Tom Noseworthy,&nbsp;Kiran J. Pohar Manhas,&nbsp;Chelsea L. Russill,&nbsp;Simron Sidhu,&nbsp;Nitya Suryaprakash,&nbsp;Venezya H. Thorsteinson,&nbsp;Tracy Wasylak,&nbsp;Deborah A. Marshall","doi":"10.1002/lrh2.70074","DOIUrl":"https://doi.org/10.1002/lrh2.70074","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Healthcare systems face persistent challenges, including workforce pressures and increasing patient complexity, and leaders are increasingly seeking approaches that support rapid learning and improvement. Learning Health Systems (LHSs) support continuous knowledge generation and application and depend on professionals with both traditional research competencies and skills in knowledge mobilization, implementation science, and collaborative leadership. The Health Systems Impact Fellowship (HSIF) National Cohort Training Program (NCTP) prepares doctoral students, postdoctoral fellows, and early-career researchers (ECRs) in Health Services and Policy Research (HSPR) through embedded research training.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We evaluated NCTP outcomes using the Kirkpatrick Evaluation Framework (KEF). Using a convergent mixed-methods survey design, we collected quantitative ratings and qualitative narrative feedback via online surveys mapped to KEF levels (reaction, learning, behavior, and results/impacts). Descriptive statistics summarized ratings across survey rounds, and directed content analysis (guided by the KEF) was used to analyze open-ended responses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Among 195 invited participants, response rates varied by training session. Overall satisfaction (agree/strongly agree) was 60.6% and varied across themes (52.6%–78.6%), reflecting diverse training needs within a multidisciplinary cohort. Respondents reported knowledge gains (over 70% for several items) and improved confidence (62%). Behavior- and impact-level evidence was less frequent but included early examples of skill application and perceived shifts in organizational practices. Qualitative feedback helped clarify what drove variation across themes. Interim findings were used to refine both training delivery and the evaluation approach.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Fellowship-based training programs such as the NCTP can support knowledge-to-action capabilities relevant to LHSs. Future evaluations should incorporate longer-term follow-up and additional data sources to better assess behavior change and organizational impact.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147585142","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}

{"title":"Person-Centered Care Planning for Persons With Multiple Chronic Conditions: Summary of an Agency for Health Care Research and Quality Sponsored Summit","authors":"Melinda M. Davis,&nbsp;Jennifer Coury,&nbsp;Zsolt Nagykaldi,&nbsp;Kisha Coa,&nbsp;Brittany Badicke,&nbsp;Ana R. Quiñones,&nbsp;LeAnn C. Michaels,&nbsp;Alex H. Krist,&nbsp;Arlene S. Bierman,&nbsp;David A. Dorr","doi":"10.1002/lrh2.70073","DOIUrl":"https://doi.org/10.1002/lrh2.70073","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Individuals at risk for or living with multiple chronic conditions (MCC) require coordinated care that is often navigated across primary, specialty care, and community environments. Person-centered care planning (PCCP) is an effective way to manage care for people with MCC needs but is not yet routine practice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The PCCP for Persons with MCC Summit was the culminating event of 14-months of three working groups and a series of environmental scans of PCCP approaches and models. The Summit convened participants from multiple sectors to address these questions of interest: (1) strategies to address and mitigate barriers to PCCP as an integral component of routine practice; (2) the development of actionable Learning Health System-related steps for PCCP implementation; and (3) research priorities to advance PCCP for persons with MCC. Audio recordings, meeting transcripts and detailed notes were consolidated and reviewed to identify and synthesize key findings.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The Summit was held March 2025 and attended by 84 in-person and 31 online participants. Participants emphasized three key outcomes: improving the patient experience, strengthening the clinician-patient relationship, and reducing care team burnout. Six interconnected themes relate to what needs to change to achieve PCCP: demand and awareness; quality measurement; team-based care; technology; payment reform; and training. Strategies for change focused on short and long-term goals, cross-sector coordination, context, and community-level interventions. Participants identified actionable implementation steps and six categories of research opportunities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Widespread adoption of PCCP requires short- and long-term efforts that raise awareness and investment, engage multi-sector partners, and attend to context. Scaling PCCP as a widely used model of care for persons with or at risk of MCC will benefit from action from each partner in care. This transformational change could build upon evidence and Learning Health System strategies to advance research and inform organizational, payment and policy changes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147565444","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}

{"title":"Learning Health Systems, Equity, and Bounded Justice: A Critical Scoping Review","authors":"Vivetha Thambinathan,&nbsp;Katie Lynch,&nbsp;Maricruz Moya,&nbsp;Maria G. Flores,&nbsp;Rama Mwenesi Musalia,&nbsp;Joshua Rubin,&nbsp;Jenna Lepczyk,&nbsp;Francesca A. Williamson","doi":"10.1002/lrh2.70072","DOIUrl":"10.1002/lrh2.70072","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The science of learning health systems (LHSs) has expanded to include equity aims. However, efforts toward this end are nascent. The purpose of this study was to critically examine how equity has been discussed in LHS literature.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a critical scoping review informed by the bounded justice concept. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, Pubmed, Embase, Scopus, and CINAHL Complete (Ebsco) databases were searched to identify relevant literature from inception to June 2024. We used qualitative descriptive analysis for detailed extraction and to identify patterns across equity conceptions in the literature.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The search strategy generated 420 articles. Forty articles met the selection criteria. Our analysis generated four interrelated themes: (1) <i>equity as central</i>, (2) <i>equity as reducing risk</i>, (3) <i>equity as process</i>, and (4) <i>equity defined as population of interest</i>. Most articles fell into the <i>equity as central</i> theme. Notably, 35 (87.5%) articles were published between 2020 and 2024. We also identified five emerging equity-centered LHS approaches.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>LHS equity science is emerging, though it still privileges narrow, Westernized approaches. It is imperative that future work more deeply engages health justice traditions to inform LHS theory, research, and practice.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12976803/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147445551","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}