Learning Health Systems最新文献

{"title":"Evaluating HEART: Student Engagement and Health System Impact in a Person-Centered Learning Health System Initiative.","authors":"Tracey Carr, Stefanie Foster, Phoebe Stobart, Carson Squair, Taylor Spock, Candace Skrapek, Margaret King, Brenda Andreas, Noelle Rohatinsky, Christine Stobart, Caitlin Ward, Tina Zheng, Gerald Farthing","doi":"10.1002/lrh2.70124","DOIUrl":"https://doi.org/10.1002/lrh2.70124","url":null,"abstract":"<p><strong>Background: </strong>Healthcare Education and Research Training (HEART) is a cocurricular, engaged learning initiative that supported undergraduate students in acquiring and applying healthcare research skills. The project was guided by a learning health system (LHS)-aligned model focused on the collection, synthesis, and rapid translation of patient-reported experience data into actionable recommendations. In the 2023/2024 academic year, a cohort of 28 students completed the pilot project to report LHS-based recommendations to healthcare directors. This paper reports the qualitative evaluation conducted in August 2024 following the pilot to assess the initiative's implementation, participant experience, and healthcare system impacts.</p><p><strong>Methods: </strong>Virtual, semi-structured interviews were conducted with students who participated in HEART and health system directors from a provincial health authority. Interview guides were developed by the research team in collaboration with Patient Partners. Inductive content analysis (ICA) was used to categorize information significant to the research questions. Final themes were established using a team-based approach.</p><p><strong>Results: </strong>Student interviews indicated that participants found HEART to be a meaningful learning experience that strengthened their understanding of the healthcare system and patient experiences and helped them build applied research skills. Health system directors also expressed strong satisfaction with the project, noting that student-collected qualitative data identified service gaps, supported patient and community engagement, and contributed to measurable care improvements in at least one clinic. Suggested areas for project improvement included adjusting length of training sessions, increasing clarity around expectations and timelines, streamlining final reporting, and refining the patient interview process to gather more detailed information about specific patient experiences.</p><p><strong>Conclusion: </strong>While various opportunities for improvement were identified, overall, HEART was determined to be a valuable opportunity for developing student healthcare research skills and was of direct benefit to health system partners as an LHS-aligned initiative providing actionable data used to identify healthcare gaps and improve patient care. Feedback and recommendations drawn from the evaluation were used to adapt and improve HEART for the following academic year.</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":"e70124"},"PeriodicalIF":2.3,"publicationDate":"2026-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13677444/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149225205","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":"Electronic Health Record Integration of a Calculator for Cesarean Risk During Labor Induction","authors":"Rebecca F. Hamm,&nbsp;M. Corinne Steele,&nbsp;Sameh Saleh,&nbsp;Mika Epps,&nbsp;E. Madeline Grenader,&nbsp;Lisa D. Levine,&nbsp;M. Kit Delgado","doi":"10.1002/lrh2.70120","DOIUrl":"10.1002/lrh2.70120","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Our group developed a calculator to predict individualized likelihood of cesarean delivery for patients undergoing labor induction. We aimed to determine whether nudge theory informed EHR integration of the cesarean risk calculator would increase (1) calculator utilization, and (2) documentation of patient counseling on the result.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This was a prospective cohort comparing 6 months pre (10/2022–4/2023) versus 6 months post EHR-release of the cesarean risk calculator (4/2023–10/2023) in two labor units. Prior to EHR-integration, Site #1 had a 2018 focused effort towards calculator website use, while Site #2 had no previous use. EHR-integration was automated to recognize eligible patients and allowed clinicians to confirm and utilize EHR variables for score automation, visible on electronic display. Counseling recommendations, specific to the patient's cesarean risk level, were then available for insertion into an EHR-note. The primary outcomes were (1) calculator utilization measured as a score generated in the EHR and (2) risk counseling defined as documentation of score discussion with the patient. The primary outcomes were also analyzed stratified by site.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 2018 patients met eligibility criteria for the cesarean risk calculator (pre:998; post:1010). Clinician calculator utilization significantly increased POST-EHR implementation from 13.4% to 77.4% (<i>p</i> &lt; 0.001). Site #2, without a prior effort towards calculator use, had greater increase in use with EHR integration compared to Site #1 (Site#1 pre: 28.8% vs. post: 62.3%, <i>p</i> &lt; 0.001; Site#2 pre: 0.4% vs. post: 91.8%, <i>p</i> &lt; 0.001). Documentation of patient counseling also increased overall (4.0% vs. 9.9%, <i>p</i> &lt; 0.001); when stratified by site, this difference was only seen at Site #2.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Behaviorally designed EHR integration of a cesarean risk calculator for labor induction was associated with significant increases in calculator utilization and documentation of patient counseling. This model could be applied to other evidence-based health-related risk calculators.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13658053/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149185002","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":"From Challenge to Studio: A Prototype Frontline AI Innovation Mechanism to Address the AI Embedding Deficit in Healthcare and Educational Institutions","authors":"Bo Xie","doi":"10.1002/lrh2.70126","DOIUrl":"https://doi.org/10.1002/lrh2.70126","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Introduction&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Health systems are expanding access to artificial intelligence (AI), yet frontline integration into teaching, clinical workflows, and research practice remains uneven. We frame this gap as the “AI embedding deficit,” reflecting limited organizational pathways that enable frontline professionals to translate local needs into legitimate, supported, and sustainable AI-enabled tools and workflows. This Experience Report describes a prototype intervention mechanism implemented at an academic nursing school: a rapid-cycle Nursing-AI Challenge followed by a year-round Nursing-AI Studio (NAIS) designed to stabilize and scale embedding.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We implemented the Nursing-AI Challenge as a structured, time-bounded mechanism to solicit real-world challenges from nursing faculty, translate and curate submissions through an interdisciplinary facilitation role, match challenges to AI trainees and mentors, and support rapid proposal development culminating in a public showcase. We then developed NAIS to address continuity and embedding barriers revealed in the Challenge, incorporating continuous intake, environmental scanning, supported co-development, year-round coordination, formalized interdisciplinary partnerships, and a strategic memorandum of understanding with the Chief Information Officer's office to support legitimate integration pathways.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;In the inaugural Challenge cycle (Spring 2025), nursing faculty identified 17 challenges spanning education, clinical practice, and research, and students in AI-related fields submitted eight proposals, followed by team formation, co-design of the AI prototypes, and a public showcase event. Implementation reflections identified key sustainability barriers including semester-bounded participation, summer momentum gaps, and intellectual property ambiguity. NAIS was established (Fall 2025 onward) to mitigate these barriers and support ongoing embedding. In early Spring 2026, NAIS launched “Teaching with AI,” a clinical faculty innovation initiative piloting an AI-powered teaching tool fully deployed within the university's information technology infrastructure.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;A Challenge-to-Studio pathway may function as a practical prototype mechanism for learning health systems seeking to reduce embedding barriers and convert decentralized frontline innovation into durable, governable, and evaluable practice change.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 &lt;/di","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70126","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146236","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":"Moving Person-Centered Care Planning From Theory Into Practice: Patient Perspectives","authors":"Claire Sachs,&nbsp;Mary F. Henningfield,&nbsp;Sarina Schrager,&nbsp;Meagan Sulikowski,&nbsp;Michelle Robinson","doi":"10.1002/lrh2.70122","DOIUrl":"10.1002/lrh2.70122","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Introduction&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Persons with multiple chronic conditions often receive care from a complicated network of multiple providers across multiple health systems unique to their conditions, needs, available resources, and insurance. Patients must navigate this healthcare system, which is a difficult and complicated process with just one provider or system, let alone multiple. Developing new solutions to overcome the systemic challenges within healthcare systems to provide high-quality, comprehensive, person-centered care for persons living with, or at risk for, multiple chronic conditions is critical. Person-centered care is needed, not only because it is the right and just approach to supporting patients, but because of the profound implications of the increasing prevalence of multiple chronic conditions on healthcare costs, caregiver burden, workforce productivity, and the broader social fabric. In this commentary, we present patient perspectives on a project that brought together diverse groups to identify potential solutions to challenges in implementation of person-centered care.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Patients, families, and family caregivers are essential to the design and implementation of person-centered care planning for people with multiple chronic conditions. The Agency for Healthcare Research and Quality (AHRQ) funded a project aimed at compiling best practices and discussing barriers. The project used a learning system approach to engage policy experts, clinicians, researchers, and persons with multiple chronic conditions, their families, and family caregivers. Four main activities included a technical expert panel, an environmental scan, a partner roundtable, and a learning collaborative. An in-person/hybrid summit held in March 2025 summarized activities and provided a forum for presentations to share activities of the project and conduct small group discussions on select topics.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results/Framework&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We present patient narratives to complement content provided by the partner roundtables and other AHRQ-funded activities that provided foundational knowledge and diverse perspectives to promote person-centered care planning as standard practice for persons with multiple chronic conditions. Although many challenges to implementation of person-centered care were identified and discussed, learning from successful models and customization of models using components as appropriate may help overcome barriers. In particular, the need for culture change, use of meaningful measures, scalability, and other concepts must be addressed. Alignment of payment structures and ","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13628701/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149116234","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":"Harnessing Potential: A Systematic Investigation of How and Why Learning Happens in a Health System","authors":"Marissa Bird,&nbsp;Ruoxi Wang,&nbsp;Jayshree Joshi,&nbsp;Jaason Geerts,&nbsp;Farah Khan,&nbsp;Balpreet Panesar,&nbsp;Laura Desveaux","doi":"10.1002/lrh2.70116","DOIUrl":"https://doi.org/10.1002/lrh2.70116","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The ability to learn is central to innovation and performance across industries, and it is the hallmark feature of the rapidly growing movement toward Learning Health Systems. While learning drivers—such as experimentation, risk-taking, participative decision-making, dialogue, and interaction with the external environment—are well defined, they have received little attention in healthcare contexts.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This study explored the nature of organizational learning within Trillium Health Partners (THP), one of Canada's largest community-based teaching hospital systems.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Formal leaders at THP completed the Organizational Learning Capability instrument. A latent profile analysis identified the number and nature of distinct learning profiles. Semi-structured interviews were conducted to develop an empirically grounded explanation of how organizational learning drivers interact to enable—or constrain—learning within the organization.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of 334 eligible leaders, 231 responded to the survey, and 141 provided sufficient data for inclusion in the analyses. Latent Profile Analysis identified two distinct learning profiles: one with relatively higher perceived learning capability and another with relatively lower perceived capability. Interviews with leaders (<i>n</i> = 12) from both groups described how theoretical factors that influence organizational learning manifest to drive (or derail) learning in practice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our systematic investigation into how and why learning occurs within a large community hospital system may support other healthcare systems in developing programs that foster the learning necessary to develop and implement innovative delivery models at scale.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048332","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":"Leveraging a Locally Anchored Learning Health Care System Toward Equitable Telehealth: Assessing Broadband Access and Supporting Use of Federal Internet Subsidies in a Safety-Net Setting","authors":"Samantha M. R. Kling,&nbsp;Jonathan G. Shaw,&nbsp;Aaron A. Tierney,&nbsp;Mayra Reyes,&nbsp;Kalijah Terilli,&nbsp;Louis Mckinnon,&nbsp;Noha Aboelata,&nbsp;Temesgen Woldeyesus","doi":"10.1002/lrh2.70121","DOIUrl":"10.1002/lrh2.70121","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Objective&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;To understand patients' access to telehealth and broadband and interest in the &lt;i&gt;Affordable&lt;/i&gt; Connectivity Program (ACP) in an urban, safety-net setting, using community-engaged iterative learning cycles to improve patient-centered care.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Data Sources and Study Setting&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Roots Community Health, a health center focused on uplifting those impacted by systemic inequities, functions as a community-anchored learning health system (LHS). Community was engaged in data collection and intervention development through Roots' Telehealth Patient Advisory Council. A cross-sectional survey was administered to adult patients.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Study Design&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Roots designed and implemented an intervention to connect patients to digital access resources, including a 66-item questionnaire capturing patients' telehealth experience and barriers, device and broadband access, and awareness of ACP—a federal benefit providing up to $30 monthly toward internet for low-income households. Patients interested in ACP were offered enrollment support.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Data Collection Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Patients were screened for ACP interest and eligibility and offered survey participation, in-person or by phone by trained clinic staff and volunteers.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Principal Findings&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;One hundred nine patients were screened for ACP eligibility and interest; 99 completed the survey. Two-thirds (65/99) had experience with telehealth and 53% (52/99) were interested in future telehealth appointments. Patients reported several notable barriers: slow internet (46/98), no Internet access (40/99), mobile data plan issues (31/98), and downloading/using the telehealth software (31/98). Surveyed patients frequently reported utilizing the Internet for resources categorizable as Social Drivers of Health (SDOH). Most screened patients (65/109) had not heard of ACP, but over half (60/109) reported interest in applying.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Using a community-embedded LHS approach, we found that broadband connectivity is crucial for equitable telehealth access, an essential part of healthcare in clinics that aim to remedy persistent health inequities affecting people of African descent. Policy and advocacy should prioritize this SDOH, while ","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13593365/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149018050","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":"Promising Patient-Engagement Practices Used by National Research Networks at the US Veterans Health Administration: Perspectives of Veterans, Staff, and Research Leaders","authors":"Tracy L. Sides,&nbsp;Jennifer Wisdom,&nbsp;Malloree M. Argust,&nbsp;Erin C. Amundson,&nbsp;Diana Burgess,&nbsp;Laura A. Meis,&nbsp;Agnes C. Jensen,&nbsp;Erin E. Krebs","doi":"10.1002/lrh2.70119","DOIUrl":"10.1002/lrh2.70119","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Active involvement of patients is an essential feature of learning health systems and patient-centered research. Research networks and healthcare organizations lack guidance on best practices for developing and sustaining patient engagement infrastructure. We sought to examine perspectives on promising Veteran-engagement infrastructure and practices used by US Veterans Affairs (VA) research networks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We solicited expert opinion from three separate panels of Veterans, VA engagement staff, and VA research leaders using a modified Delphi process comprising two rounds of online surveys and a set of virtual group meetings or individual interviews. In a prior study, we identified promising engagement practices in use by VA national research networks. We analyzed survey data with predefined rating categories to determine which practices the three expert panels consistently endorsed. We used thematic analysis to compare experts' perspectives across panels and to identify emergent cross-cutting themes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Veterans, VA engagement staff, and VA research leaders consistently endorsed 66% (29/44) of the research networks' promising Veteran-engagement practices. Summarized, these practices formed five recommended engagement-related responsibilities for VA research networks. Some network engagement practices were inconsistently endorsed (13/44, 30%), and two practices (4%) received overall ratings of neutral or unsure by at least one expert panel. Network practices not consistently endorsed varied by expert panel, but panelists' comments reflected three overarching themes: constraint of resource availability, commitment to respectful and meaningful engagement processes, and concern for potential burden on partners.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Panelists' perspectives highlight challenges regarding how to best invest limited patient-engagement resources within research and learning health system organizations. Research network engagement infrastructure can help expand the capacity and culture of patient-centered research and care. Organizations seeking to function as learning health systems need to devote planning time, skilled staff, and funds to develop and sustain patient-engagement infrastructure tailored to their context.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13579376/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148991715","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":"Beyond Blind Trust in Hospital Data Warehouses: Evaluating Real-World Data Accountability","authors":"Akemi Morohashi,&nbsp;Satoshi Yamashita,&nbsp;Takahiro Imaizumi,&nbsp;Takuto Sano,&nbsp;Yachiyo Kuwatsuka,&nbsp;Masahiko Ando,&nbsp;Yoshimune Shiratori","doi":"10.1002/lrh2.70118","DOIUrl":"10.1002/lrh2.70118","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The reliability of real-world evidence (RWE) depends on data accuracy and secondary users' ability to evaluate how data are generated and transformed. Although recent frameworks emphasize provenance, transparency, and auditability, their practical assessment in routine hospital settings remains unclear. This study examines the practical evaluability of real-world data (RWD) and explores operational boundaries limiting data quality assessment within learning health systems.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An empirical case study was conducted at a tertiary-care university hospital in Japan. Data extracted from electronic health records and a clinical data warehouse were compared using 15 quality indicators derived from the <i>Data Quality Management Guidebook</i> of the Digital Agency of Japan (based on ISO/IEC 25012). Evaluability was assessed using a two-step framework comprising empirical verification and contextual explanation from the perspective of research support personnel operating under routine institutional access permissions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Evaluability varied substantially across clinical domains. Diagnosis records were generally verifiable and explainable, whereas medication-related domains contained observations that could be verified but not fully explained by secondary users. Indicators including currentness and efficiency faced additional operational constraints, revealing boundaries between observable data characteristics and available explanatory information.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Practical RWD use depends not only on observable data characteristics but also on the accessibility of information needed to interpret them. Evaluability boundaries reflect operational constraints rather than poor data quality. Rendering these boundaries visible may support more transparent and accountable RWD governance and inform future improvements through system design and data governance practices.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13547741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148907626","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":"Evaluation of a Real-Time Knowledge Exchange Network Supporting Syphilis Rapid Testing and Immediate Treatment in Seven Public Health Units in Ontario, Canada","authors":"Megan Ann Carter,&nbsp;Sara Tryon,&nbsp;Mary Southall,&nbsp;Kandace Belanger,&nbsp;Mary France Caron-Bruneau,&nbsp;Anne Charron,&nbsp;Sandra Dereski,&nbsp;Michael Evans,&nbsp;Natasha Larkin,&nbsp;Kassandra Plante,&nbsp;Melanie St. John,&nbsp;Nicole Szumlanski,&nbsp;Lucy Mackrell,&nbsp;Sahar Saeed","doi":"10.1002/lrh2.70106","DOIUrl":"10.1002/lrh2.70106","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The Syphilis Point of care Rapid testing and Immediate Treatment Evaluation (SPRITE) is a collaborative, community-based initiative that strengthens syphilis prevention and control in Ontario, Canada through flexible outreach nursing and point-of-care testing (POCT) and immediate treatment. Seven public health units (PHUs) partnered with 86 community-based organizations (CBOs) to deliver syphilis/HIV POCTs in underserved settings. This study evaluated a real-time knowledge exchange network that supported syphilis POCT implementation and capacity-building across PHUs and CBOs in Ontario.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The evaluation was a mixed-methods case study using surveys and interviews focusing on the community of practice (CoP), community engagement, and knowledge mobilization. It considers SPRITE CoP activities from beginning of implementation (mid 2023) to the Fall of 2025.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The CoP, consisting of public health nurses, researchers, and knowledge specialists, supported engagement, co-development, and peer learning. Members shared lessons learned, built partnerships, and supported each other in navigating challenges. Flexibility in funding allowed innovation by CoP members in their CBO engagement efforts but also created some uncertainty and possible confusion. CoP members were overall satisfied with CoP functioning, and CBOs surveyed appeared knowledgeable and engaged in SPRITE.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>The CoP model, while distinct from traditional public health CoPs, proved effective in fostering engagement, resource development, and knowledge mobilization. Lessons learned and tools developed provide guidance for future POCT efforts. Improvements should include clearer goals, stronger facilitation, and structured engagement strategies. Addressing funding stability, particularly for POCT services and CoP management roles, is essential. Strengthening CBO partnerships through incentives and bi-directional information sharing will further enhance POCT and syphilis prevention. This evaluation underscores the importance of flexible yet accountable approaches to knowledge mobilization and POCT implementation in diverse public health contexts. Continued investment in collaborative networks like SPRITE remains critical to advancing syphilis elimination efforts across Ontario.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13531007/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148876106","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":"Toward a Smart Learning Health System: An Ontology-Based Framework","authors":"Meg Ma,&nbsp;Ping Yu,&nbsp;Louise D. Hickman","doi":"10.1002/lrh2.70117","DOIUrl":"https://doi.org/10.1002/lrh2.70117","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Learning health system (LHS) frameworks have been presented in multiple forms, but there is no standardized representation that captures both their core concepts and the relationships among them. This limits their practical use by health services seeking to design, implement, and evaluate LHS capabilities in changing sociotechnical environments. This study developed the Smart Learning Health System ontology (SMARTLHS), a formal semantic framework that synthesizes concepts and relationships from published LHS frameworks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Relevant literature was identified through a systematic database search. SMARTLHS was developed using an iterative system mapping and ontology engineering approach, comprising five steps: (1) ontology requirements specification, (2) iterative ontology conceptualization, (3) concept and relationship comparison and formalization, (4) ontology evaluation and refinement, and (5) ontology alignment with foundational ontology, to ensure semantic consistency and interoperability. The SMARTLHS ontology was implemented using the Web Ontology Language (OWL) and developed in Protégé.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>SMARTLHS contains 447 classes and 134 object properties. Its structure is organized around four high-level groupings: <i>LHSs, supporting pillars, cross-cutting themes,</i> and <i>common reference LHS frameworks</i>. The supporting pillars comprise seven domains: <i>Care delivery and organizational strategies</i>, <i>community and patient engagement, culture and change management, data and technology infrastructure, governance and leadership, research and education,</i> and <i>workforce and capacity building</i>. The cross-cutting themes include <i>ethics and oversight, evaluation and methodology</i>, and <i>value creation and benefits</i>. Together, these classes and relationships provide a computable semantic representation of LHS implementation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>SMARTLHS addresses key limitations of existing LHS frameworks by transforming narrative framework concepts into a formal, extensible semantic knowledge model. By explicitly representing both concepts and relationships, it provides a foundation for organizational assessment, semantic interoperability, and future AI-enabled applications, including ontology-guided retrieval and Retrieval-Augmented Generation (RAG).</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"10 4","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/lrh2.70117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784324","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}