Learning Health Systems最新文献

{"title":"How senior leaders support innovations in large learning health systems: Insights from United States Veterans Health Administration national program office leaders","authors":"Jaifred Christian F. Lopez,&nbsp;Sallie Allgood,&nbsp;Kate Sheahan,&nbsp;Brandolyn White,&nbsp;M. Amy Kirshner,&nbsp;Suzanne Shirley,&nbsp;Madison Coffey,&nbsp;Amanda Milo,&nbsp;Sarah L. Cutrona,&nbsp;Laura Damschroder,&nbsp;Gemmae M. Fix,&nbsp;Andrea L. Nevedal,&nbsp;Caitlin M. Reardon,&nbsp;Marilla A. Opra Widerquist,&nbsp;Maria Arasim,&nbsp;Allen L. Gifford,&nbsp;Kathryn DeLaughter,&nbsp;George L. Jackson","doi":"10.1002/lrh2.70012","DOIUrl":"https://doi.org/10.1002/lrh2.70012","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The U.S. Veterans Health Administration (VHA) formed an Innovation Ecosystem that develops and disseminates innovative practices to enhance Veterans' health. Support of senior leadership and their perception of the innovation process is key to the Ecosystem's success. We aimed to elicit insights on (1) how national VHA program office leaders define innovation, and (2) important considerations in facilitating the adoption of innovations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>As part of a quality improvement initiative, we conducted 19 semi-structured interviews via teleconference. Interviews involved 4 administration offices, 7 clinical and population health program offices, and 8 policy and quality improvement offices; 12 of these offices reported experience working with the Innovation Ecosystem. Responses were audio recorded, transcribed, and analyzed using constructs from the Consolidated Framework for Implementation Research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Participants generally agreed that innovation within VHA is defined by evidence-based development and implementation of interventions that improve response to Veterans' needs. Considerations in facilitating innovations include: (1) implementation climate that promotes network-building, open communication, and well-executed planning processes; (2) implementation infrastructures that enable engagement with key players and augment existing resources; and (3) innovation evidence strength and responsiveness to patient needs. Individuals working in policy-related offices were more likely to identify complexity, leadership engagement, culture and available resources as factors in choosing innovations to adopt. Individuals who reported experience of working with the Ecosystem emphasized the importance of intra-organizational networks and a favorable implementation climate, while those without experience noted the importance of working with external change agents. CFIR ‘inner setting’ constructs were seen in responses across all categories; meanwhile, emerging constructs highlight how innovation should be balanced by the reality of operations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Among national VHA program office leaders, innovation is pursued to improve Veterans' health. Resources, networks, culture, and processes are considered important factors among program office leaders to support and encourage innovation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635208","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":"The surprising politics of learning health systems","authors":"Adalsteinn Brown,&nbsp;Robert J. Reid","doi":"10.1002/lrh2.70008","DOIUrl":"https://doi.org/10.1002/lrh2.70008","url":null,"abstract":"<p>Learning Health Systems (LHS) are an increasingly common element of health policy reform efforts in a number of jurisdictions. There is little disagreement around the LHS vision, and early adopters provide some development guidance. Despite the attractiveness of the LHS vision, progress on adoption by systems remains slow. In this commentary, we consider one potential reason, namely politics, or the ways in which government bodies, interest groups, and political ideas shape structures and policies. LHS can change the ways that health systems work and interact with payors and populations and thereby create political challenges. The need for upfront new investment to build capacity for LHS activities, the creation of new partnerships or collaborations, increased transparency, and the direct engagement of populations can all create political risks and subsequent barriers. With a broad population health focus that extends across typical political cycles, politics may create an even greater barrier. We suggest that building strong engagement, clear and transparent accountabilities, communities of practice and other vehicles to promote data sharing and transparency, and careful attention to risk management may all help reduce political challenges. Some sets of policies—like value-based care—can support these sorts of changes and accelerate the adoption of LHS.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635503","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":"Four distinct models of learning health systems: Strength through diversity","authors":"Charles P. Friedman,&nbsp;Sarah M. Greene","doi":"10.1002/lrh2.70009","DOIUrl":"https://doi.org/10.1002/lrh2.70009","url":null,"abstract":"<p>The concept of a learning health system (LHS) was established nearly 20 years ago as a unifying commitment to speed the generation and use of evidence primarily by leveraging rapid advances in data and technologies, resulting in optimized care for each patient. In the ensuing decades, vanguard adopters of the LHS who have sought to move the LHS from conceptual to operational have done so in ways that fit with and reflect their organizational structure, mission, and culture—as well as their personal values and experiences. They have also extended the focus from health care to include individual and population health more broadly. This commentary describes four distinctive models that have evolved as learning health system activities have matured. Viewing this diversity as a strength, the features, commonalities, and unique differences of these models are described.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835793","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":"Development and implementation of a sensitivity training curriculum focused on equity in healthcare","authors":"Allen M. Chen","doi":"10.1002/lrh2.70007","DOIUrl":"https://doi.org/10.1002/lrh2.70007","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>A longitudinal sensitivity-based curriculum focused on diversity, equity, and inclusion (DEI) and consisting of interactive seminars and roundtable discussions was constructed to equip participants with tools to enhance culturally effective care and to create an inclusive learning environment. The purpose of this study was to report our single-institutional experience with the development and implementation of this evidence-based curriculum.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Materials</h3>\u0000 \u0000 <p>Core DEI themes on which to center the sensitivity training curriculum were identified through an evidence-based review based on the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) statement. A MEDLINE search was undertaken to identify original peer-reviewed works using the items “equity, diversity, inclusion,” “underserved,” “disadvantaged,” “sensitivity training,” and “curriculum.”</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Based on the search results, a 12-month curriculum was established centered on the core themes that emerged. The 98 peer-reviewed publications chosen to develop this thematic framework could be broadly categorized as follows: health disparities (<i>N</i> = 33); workplace diversity (<i>N</i> = 24); implicit bias (<i>N</i> = 21); and structural racism (<i>N</i> = 20). Between November 2022 and January 2024, a total of 12 interactive sessions were scheduled. The mean number of attendees for each DEI session was 19 (range: 3 to 32), and the mean length of each session was 50 min (range: 20 to 81).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The developed curriculum helped promote awareness of historical inequities in healthcare and empowered learners to become better advocates for colleagues and patients alike. The implication for healthcare leaders are discussed.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634988","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":"A learning health system model for addressing substance use: Denver Health Center for Addiction Medicine","authors":"Emily Bacon,&nbsp;Laura J. Podewils,&nbsp;Brooke Bender,&nbsp;Joshua Blum,&nbsp;Christian Thurstone,&nbsp;Alia Al-Tayyib,&nbsp;John Mills,&nbsp;Alexandra R. Tillman,&nbsp;Judith Shlay","doi":"10.1002/lrh2.70003","DOIUrl":"https://doi.org/10.1002/lrh2.70003","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Substance use disorders (SUDs) continue to place heavy burdens on patients, health systems, and communities. Rapidly evolving treatment for SUDs requires health systems that can efficiently and effectively assess data and integrate evidence to practice. This paper describes the implementation of a learning health systems model of SUD care at an urban, safety-net, integrated health system in Denver, Colorado.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The health system created the Center for Addiction Medicine (CAM) to coordinate comprehensive services for patients with SUD, including research, evaluation, and quality improvement efforts. CAM implemented a hub-and-spoke model of care and developed four strategic areas to identify, integrate, and grow SUD services. CAM also created a process for engaging community members with lived experience with SUDs and a CAM Academy to educate partners within the health system and across the region.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>CAM successfully implemented processes for gathering and assessing evidence, informing clinical practice, fostering community partnerships, and strategically expanding services and reach. Key factors driving success include strategic planning, leadership buy-in, data infrastructure, and community partnerships.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Integrated SUD care at a safety-net institution is a continued challenge. Persistent barriers include the SUD policy and regulatory landscape, addressing co-occurring social and health circumstances when treating SUDs, and accurate clinical documentation of SUDs. Applying a learning health system model can help health systems adapt to these challenges.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635179","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":"How an evidence synthesis program's growth has supported research use and learning community partnership networks within a learning health system: A descriptive analysis and case series","authors":"Isomi Miake-Lye,&nbsp;Selene Mak,&nbsp;Tom Valente,&nbsp;Nicole Floyd,&nbsp;Paul Shekelle","doi":"10.1002/lrh2.70004","DOIUrl":"https://doi.org/10.1002/lrh2.70004","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The Veterans Administration Evidence Synthesis Program (VA ESP) was established in 2007 to support evidence-based decisions about policies and programs in the VA healthcare system and has served as a critical component in the VA learning health system. Our objective was to document the growth of the ESP partner network and key policy and practice impacts of the program through a descriptive social network analysis and case series. We also aimed to provide insights into key features of some successful partnerships and the role evidence synthesis can play in supporting the improvement of the health system.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using social network analysis and national ESP program data, we depicted the network at its initial, fully operational, and established phases of development to describe over a decade of ESP partnerships. We also queried program leadership and ESP partners about their collaboration experiences to generate a case series that demonstrates key examples of successful partnerships.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of the 82 partner offices for whom the ESP has generated a report, over half (66%, <i>n</i> = 54) collaborated with the ESP on multiple projects, having received two or more synthesis products over time. Case studies revealed the impacts of ESP evidence synthesis on policy and practice, how our partners used the evidence generated from these processes, and the future work spawned from these efforts. While infrastructure and formal mechanisms can support these connections, relationships and partnering are instrumental facets as well.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Partnerships between the ESP and decision-makers can facilitate access to evidence and leadership's ongoing use of this evidence. The ESP has led to meaningful, evidence-driven communication between research and operational partners and has supported stakeholders in informing policy and system change.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635362","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":"Landscape of informed consent practices and challenges in point-of-care clinical trials","authors":"Caleigh Propes,&nbsp;Trevan Locke,&nbsp;Rachele Hendricks-Sturrup","doi":"10.1002/lrh2.10467","DOIUrl":"https://doi.org/10.1002/lrh2.10467","url":null,"abstract":"<p>Point-of-care trials, an approach to trial design that assesses medical product effectiveness while fully integrating research and care, represent a promising opportunity to generate practically relevant evidence efficiently for priority disease areas. However, this approach presents unique considerations for appropriate and ethical informed consent. As point-of-care trials evolve, it will be important to examine informed consent through the lens of their supporting technology, of the clinicians who are responsible for administering it, and of their broader regulatory environment. Steps should be taken to establish ethical standards for point-of-care trials that reflect and serve the best interests of patients while reducing administrative burden and complexity. Our commentary describes, overall and through the use of real-world examples, how this work is vital to ensuring a modern clinical trial enterprise that is patient-centered and equips patients to make fully informed decisions about their health care.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.10467","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635448","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":"Charting progress in learning health systems: A systematic review of 5 years of definitions, models, and frameworks","authors":"Louise A. Ellis,&nbsp;Georgia Fisher,&nbsp;Maree Saba,&nbsp;Genevieve Dammery,&nbsp;Kate Churruca,&nbsp;Samantha Spanos,&nbsp;Carolynn L. Smith,&nbsp;Bianca Forrester,&nbsp;Yvonne Zurynski,&nbsp;Jeffrey Braithwaite","doi":"10.1002/lrh2.70006","DOIUrl":"https://doi.org/10.1002/lrh2.70006","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Since being introduced by the Institute of Medicine (IoM) in 2007, the learning health system (LHS) concept has gained traction as a promising solution for achieving systems-level healthcare transformation. This review of the LHS literature consolidates current understanding of LHS definitions, models, frameworks, and underlying theory, relative to their initial conceptualization by the IoM.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Three academic databases (PubMed, Embase, and Scopus) were searched for peer-reviewed literature between 2018 and 2023. Articles were included that explicitly focused on LHSs and described an LHS definition, model, or framework. Extracted article information included key article characteristics and article type; LHS definition(s) and their reference(s); components of LHS models or frameworks; and any reported theories underpinning LHS models or frameworks. Extracted data were examined using thematic and visual network analyses, and practical examples of how the domains of an LHS can be actualized in health settings were synthesized.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The majority of the 226 included articles were nonempirical (47%) and originated from high-income countries (97%), with a significant portion from the United States (62%). A third of articles described an LHS implemented in a real-world setting (35%). A significant majority (82%) provided a definition of an LHS, with key concepts centering around “knowledge to practice,” “workplace culture,” and “informatics.” Over half of included articles described an LHS model or framework. From thematic deductive-inductive coding of 145 LHS models and frameworks, most identified aspects related to Science and Informatics (83%) and a Continuous Learning Culture (81%), with the most prevalent sub-domain being Supportive System Competencies (76%). Implementation science was the most used theory to underpin existing models and frameworks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>By dissecting LHS definitions, models, and frameworks, we present an integrated framework that can serve as a useful tool for LHS researchers, clinicians, and policymakers working to improve health system performance and outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635648","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":"Cyclical medication management interventions in health care settings: A systematic review","authors":"Isabelle Meulenbroeks,&nbsp;Crisostomo Mercado,&nbsp;Rachel Urwin,&nbsp;Karla Seaman,&nbsp;Anna Kelly,&nbsp;Osman Qadri,&nbsp;Johanna Westbrook I.","doi":"10.1002/lrh2.70005","DOIUrl":"https://doi.org/10.1002/lrh2.70005","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>It is estimated that one in 30 patients experiences at least one preventable medication-related harm while receiving care. Cyclical medicine improvement interventions, where health systems continuously collect data, implement prescribing/dispensing interventions, review outcomes, and revise the intervention, have demonstrated health outcome improvements in a range of health care settings. This systematic review aimed to synthesize information on the characteristics and outcomes of cyclical medication management interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Five databases were systematically searched for cyclical medication management interventions from 2000 to 2023. Studies were screened in a two-step process: title/abstract and full-text screening. All intervention, population, and outcome data were extracted. Intervention data were thematically categorized, and outcome data were categorized using Proctor's framework. The quality of data was assessed using the Mixed Methods Appraisal Tool (MMAT).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Forty-five cyclical interventions from 46 publications were included. Most interventions studied cyclical medication management interventions in hospital settings (80%, <i>n</i> = 37) and utilized the plan-do-study-act framework to guide intervention design (64%, <i>n</i> = 29). Cyclical medication management interventions comprised multiple components (mean 2.4 components), with common components including practice standardization (<i>n</i> = 23), clinician feedback (<i>n</i> = 20), and clinician education (<i>n</i> = 18). One hundred and twenty-two outcome measures were extracted and categorized as implementation (<i>n</i> = 77), service (<i>n</i> = 41), and patient outcomes (<i>n</i> = 4). The quality of many publications was poor; 8 publications could not be scored or scored 0 on the MMAT, and the remaining publications scored on average (mean) 60% on the MMAT.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Cyclical medication management interventions show weak evidence that they can be implemented successfully and improve health system and service outcomes. Significant further research and health system structuring are required to address the quality issues surrounding cyclical medication management implementation and reporting.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635639","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":"2024 Advances in Learning Health System Sciences (AiLHSS) Conference: Abstracts","authors":"","doi":"10.1002/lrh2.70000","DOIUrl":"https://doi.org/10.1002/lrh2.70000","url":null,"abstract":"&lt;p&gt;The &lt;i&gt;Advances in Learning Health System Sciences&lt;/i&gt; (&lt;i&gt;AiLHSS) Conference&lt;/i&gt; is an annual event that addresses pressing and emerging Learning Health System (LHS) topics while fostering collaboration among researchers advancing the field presented by the University of Minnesota (UMN) Center for Learning Health System Sciences (CLHSS), a collaboration between the Medical School and School of Public Health at the UMN. The 2024 conference was held on September 9–10 at Coffman Memorial Union at UMN in Minneapolis, MN. This year's conference featured 219 attendees including clinicians, researchers, policymakers, and trainees, with local, national, and international representation from professional organizations, research institutes, healthcare organizations, and universities serving the needs of diverse populations such as children, the elderly, rural communities, and veterans. The agenda was composed of keynote presentations, scientific forums, workshops, and poster sessions all designed to foster collaboration and innovation in the field of LHS. Throughout the conference, attendees had the opportunity to engage in various networking sessions. This year's agenda highlighted the importance of collaboration and continuous learning in improving healthcare delivery, with a focus on practical tools, real-world examples, and the integration of patient and community perspectives.&lt;/p&gt;&lt;p&gt;On the first day, September 9, the conference began with coffee and networking, followed by welcome and opening remarks from Genevieve Melton-Meaux, MD, PhD (Director, CLHSS), and Jakub Tolar, MD, PhD (Dean, UMN Medical School). The morning sessions included a keynote by Sarah Greene, MPH, from the National Academy of Medicine discussing the complexities and opportunities in building and sustaining learning health systems. This was followed by a spotlight session and a panel on active data sharing collaboratives. The afternoon featured scientific forums on topics such as organ donation data, opioid substance use treatment, and cardiac imaging in stroke evaluation, as well as a workshop on partnering with patients to improve study design and outcomes. The day ended with a poster session which included networking opportunities.&lt;/p&gt;&lt;p&gt;The second day, September 10, started with coffee and networking, followed by opening remarks from Timothy Beebe, PhD (Deputy Director, CLHSS), and a keynote by Sara Singer, PhD, MBA, from Stanford University on the importance of learning in health systems. The morning sessions included evidence synthesis case studies and a spotlight session on implementation science reporting and adherence challenges. The conference concluded with a keynote by Angela D. Thomas, DrPH, MPH, MBA, from MedStar Health discussing the realities of being a learning health system.&lt;/p&gt;&lt;p&gt;This article features a curated collection of abstracts from spotlight sessions, oral presentations, and the highest-scored posters, all of which were recognized for their innovative","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"9 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143836471","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}