Learning Health Systems最新文献

{"title":"Thanks to our peer reviewers","authors":"","doi":"10.1002/lrh2.10464","DOIUrl":"10.1002/lrh2.10464","url":null,"abstract":"<p>The publication of Issue 4 marks the completion of Volume 8 of <i>Learning Health Systems</i>. An international, trans-disciplinary, open access publication, the journal has advanced research and scholarship on learning health systems in partnership with our reviewers. With indexing in multiple major sources and an Impact Factor of 2.6, we have achieved a publication milestone that signals a sustainable, positive trajectory. Articles from the journal were downloaded over 123, 126 times in 2023.</p><p>Each year, the journal publishes a Special Issue; we have now published eight <i>Special Issues</i>: “Patient Empowerment and the Learning Health System” (v.1); “Ethical, Legal, and Social Implications of Learning Health Systems” (v.2); “Learning Health Systems: Connecting Research to Practice Worldwide” (v.3); “Human Phenomics and the Learning Health System” (v.4); “Collaborative Learning Health Systems: Science and Practice” (v.5); and “Education To Meet the Multidisciplinary Workforce Needs of Learning Health Systems” (v.6); “Transforming Health Through Computable Biomedical Knowledge (CBK)” (v.7); and “Envisioning Public Health As a Learning Health System” (v.8). Our talented guest editors have been instrumental in helping these <i>Special Issues</i> come to fruition.</p><p>In addition, we published a Supplement (“Focus on Research by AcademyHealth members”) in June 2024. The Supplement was a collaboration with the Department of Learning Health Sciences (University of Michigan), Academy Health, (LHS Interest Group), and John Wiley &amp; Sons.</p><p>We are keenly aware that these achievements would not have happened without the dedicated efforts and insightful comments of all those individuals who accepted invitations to review submitted articles. With busy schedules and full commitments, these individuals found the time and energy to contribute their expertise to our authors to help ensure that their papers met (and often exceeded) the journal's high standards for publication.</p><p>Please accept our sincere gratitude for your outstanding efforts!</p><p><i>Charles P. Friedman</i>, Editor in Chief</p>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493543/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510012","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":"Envisioning public health as a learning health system","authors":"Theresa A. Cullen,&nbsp;Lisa Villarroel","doi":"10.1002/lrh2.10465","DOIUrl":"10.1002/lrh2.10465","url":null,"abstract":"&lt;p&gt;This Special Issue of &lt;i&gt;Learning Health Systems&lt;/i&gt; seeks to understand what it would take for public health to become a learning health system. The selected articles highlight the required organizational insights and foundational components, such as including public health partners in care networks and ensuring timely, relevant public health data in cycles of public health learning—both of which reflect the foundational public health core functions of Assessment, Assurance, and Policy.&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;The transition to a learning public health system may herald the next phase of public health. Public Health 1.0 envisioned governmental entities providing functions to improve public health during a time of growth of clinical and public healthcare. Public Health 2.0, as outlined in the 1988 Institute of Medicine's &lt;i&gt;The Future of Public Health&lt;/i&gt;,&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt; focused on traditional public health agency programs. In 2016, Public Health 3.0 stressed multi-partner engagement around social determinants of health.&lt;span&gt;&lt;sup&gt;3&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;We propose that Public Health 4.0 integrate historical lessons from public health with those from a learning healthcare system to embody a Learning Public Health System model.&lt;span&gt;&lt;sup&gt;4&lt;/sup&gt;&lt;/span&gt; By expanding stakeholders, integrating organizational learning into our processes, continually using data and evaluation to form new public health practices, and incorporating self-evaluation and communication transparency, public health can continually learn and improve.&lt;/p&gt;&lt;p&gt;As public health officials in state and local health departments, we acknowledge that our own institutions are not yet learning public health systems. Our foundational cycles of Assessment, Assurance, and Policy often buckle due to the lack of workforce, funding, and infrastructure. However, we believe that aligning with a learning health system framework would recommit public health to rapid cycle innovation and response as we face stubborn foes like heat, loneliness, substance use, and vaccine hesitancy.&lt;/p&gt;&lt;p&gt;This published collection of articles helps inform the framework of a learning health system that needs to be envisioned and actualized.&lt;/p&gt;&lt;p&gt;One approach for the creation of a learning public health system model is to broaden the conceptual framework of what is included in a learning health system. Rather than insulating the model within a healthcare system, participating partners would include public health and community-based organizations. The case study from Semprini et al.&lt;span&gt;&lt;sup&gt;5&lt;/sup&gt;&lt;/span&gt; presents how a rural cancer network worked with the public health cancer registry to access their data to enhance patient outcomes. Along a similar model, Meigs et al.&lt;span&gt;&lt;sup&gt;6&lt;/sup&gt;&lt;/span&gt; propose incorporating community-based organizations (CBOs) into a learning health system at all stages, with examples of successful integrations in refugee initiatives. These papers illustrate the expansion of l","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510009","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 to implement chronic disease prevention programs: A novel framework and perspectives from an Australian health service","authors":"Luke Wolfenden,&nbsp;John Wiggers,&nbsp;Courtney Barnes,&nbsp;Cassandra Lane,&nbsp;Daniel Groombridge,&nbsp;Katie Robertson,&nbsp;Jannah Jones,&nbsp;Sam McCrabb,&nbsp;Rebecca K. Hodder,&nbsp;Adam Shoesmith,&nbsp;Nayerra Hudson,&nbsp;Nicole McCarthy,&nbsp;Melanie Kingsland,&nbsp;Emma Doherty,&nbsp;Emily Princehorn,&nbsp;Meghan Finch,&nbsp;Nicole Nathan,&nbsp;Rachel Sutherland","doi":"10.1002/lrh2.10466","DOIUrl":"10.1002/lrh2.10466","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Chronic diseases are a considerable burden to health systems, communities, and patients. Much of this burden, however, could be prevented if interventions effective in reducing chronic disease risks were routinely implemented.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>The aim of this paper is to discuss the role of public health agencies in preventing chronic disease through the application of learning health system (LHS) approaches to improve the implementation of evidence-based interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>We draw on the literature and our experience operating a local LHS in Australia that has achieved rapid improvements in the implementation of chronic disease prevention interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The proposed LHS framework has been adapted to be both implementation and chronic disease prevention focused. The framework describes both broad improvement processes, and the infrastructure and other support (pillars) recommended to support its core functions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The framework serves as a basis for further exploration of the potentially transformative role LHS's may have in addressing the chronic disease health crisis.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493556/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510010","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 translation-to-policy learning cycle to improve public health","authors":"Amy M. Kilbourne,&nbsp;Melissa Z. Braganza,&nbsp;Dawn M. Bravata,&nbsp;Jack Tsai,&nbsp;Richard E. Nelson,&nbsp;Alex Meredith,&nbsp;Kenute Myrie,&nbsp;Rachel Ramoni","doi":"10.1002/lrh2.10463","DOIUrl":"10.1002/lrh2.10463","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>Learning Health Systems (LHSs) have not directly informed evidence-based policymaking. The Translation-to-Policy (T2P) Learning Cycle aligns scientists, end-users, and policymakers to support a repeatable roadmap of innovation and quality improvement to optimize effective policies toward a common public health goal. We describe T2P learning cycle components and provide examples of their application.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The T2P Learning Cycle is based on the U.S. Department of Veterans Affairs (VA) Office of Research and Development and Quality Enhancement Research Initiative (QUERI), which supports research and quality improvement addressing national public health priorities to inform policy and ensure programs are evidence-based and work for end-users. Incorporating LHS infrastructure, the T2P Learning Cycle is responsive to the Foundations for Evidence-based Policymaking Act, which requires U.S. government agencies to justify budgets using evidence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The learning community (patients, providers, clinical/policy leaders, and investigators) drives the T2P Learning Cycle, working toward one or more specific, shared priority goals, and supports a repeatable cycle of evidence-building and evaluation. Core T2P Learning Cycle functions observed in the examples from housing/economic security, precision oncology, and aging include governance and standard operating procedures to promote effective priority-setting; complementary research and quality improvement initiatives, which inform ongoing data curation at the learning system level; and sustainment of continuous improvement and evidence-based policymaking.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The T2P Learning Cycle integrates research translation with evidence-based policymaking, ensuring that scientific innovations address public health priorities and serve end-users through a repeatable process of research and quality improvement that ensures policies are scientifically based, effective, and sustainable.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493547/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510013","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":"Creating a learning health system to include environmental determinants of health: The GroundsWell experience","authors":"Sarah E. Rodgers,&nbsp;Rebecca S. Geary,&nbsp;Roberto Villegas-Diaz,&nbsp;Iain E. Buchan,&nbsp;Hannah Burnett,&nbsp;Tom Clemens,&nbsp;Rebecca Crook,&nbsp;Helen Duckworth,&nbsp;Mark Alan Green,&nbsp;Elly King,&nbsp;Wenjing Zhang,&nbsp;Oliver Butters","doi":"10.1002/lrh2.10461","DOIUrl":"10.1002/lrh2.10461","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Policies aiming to prevent ill health and reduce health inequalities need to consider the full complexity of health systems, including environmental determinants. A learning health system that incorporates environmental factors needs healthcare, social care and non-health data linkage at individual and small-area levels. Our objective was to establish privacy-preserving household record linkage for England to ensure person-level data remain secure and private when linked with data from households or the wider environment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A stakeholder workshop with participants from our regional health board, together with the regional data processor, and the national data provider. The workshop discussed the risks and benefits of household linkages. This group then co-designed actionable dataflows between national and local data controllers and processors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A process was defined whereby the Personal Demographics Service, which includes the addresses of all patients of the National Health Service (NHS) in England, was used to match patients to a home identifier, for the time they are recorded as living at that address. Discussions with NHS England resulted in secure and quality-assured data linkages and a plan to flow these pseudonymised data onwards into regional health boards. Methods were established, including the generation of matching algorithms, transfer processes and information governance approvals. Our collaboration accelerated the development of a new data governance application, facilitating future public health intervention evaluations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>These activities have established a secure method for protecting the privacy of NHS patients in England, while allowing linkage of wider environmental data. This enables local health systems to learn from their data and improve health by optimizing non-health factors. Proportionate governance of health and linked non-health data is practical in England for incorporating key environmental factors into a learning health system.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510008","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":"Accelerating a learning public health system: Opportunities, obstacles, and a call to action","authors":"Jessica D. Tenenbaum","doi":"10.1002/lrh2.10449","DOIUrl":"10.1002/lrh2.10449","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Public health systems worldwide face increasing challenges in addressing complex health issues and improving population health outcomes. This experience report introduces the concept of a Learning Public Health System (LPHS) as a potential solution to transform public health practice. Building upon the framework of a Learning Health System (LHS) in healthcare, the LPHS aims to create a dynamic, data-driven ecosystem that continuously improves public health interventions and policies. This report explores the definition, benefits, challenges, and implementation strategies of an LPHS, highlighting its potential to revolutionize public health practice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This report employs a comparative analysis approach, examining the similarities and differences between an LPHS and an LHS. It also identifies and elaborates on the potential benefits, challenges, and barriers to implementing an LPHS. Additionally, the study investigates promising national initiatives that exemplify elements of an LPHS in action.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>An LPHS integrates data from diverse sources to inform knowledge generation, policy development, and operational improvements. Key benefits of implementing an LPHS include improved disease prevention, evidence-informed policy-making, and enhanced health outcomes. However, several challenges were identified, such as interoperability issues, governance concerns, funding limitations, and cultural factors that may impede the widespread adoption of an LPHS.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Implementation of an LPHS has the potential to significantly transform public health practice. To realize this potential, a call to action is issued for stakeholders across the public health ecosystem. Recommendations include investing in informatics infrastructure, prioritizing workforce development, establishing robust data governance frameworks, and creating incentives to support the development and implementation of a LPHS. By addressing these key areas, public health systems can evolve to become more responsive, efficient, and effective in improving population health outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510006","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":"Community-led transformation principles: Transforming public health learning systems by centering authentic collaboration with community-based organizations","authors":"Reba Meigs,&nbsp;Amina Sheik Mohamed,&nbsp;Adriana Bearse,&nbsp;Sarah Vicente,&nbsp;Nghi Dang,&nbsp;Asmaa Deiranieh,&nbsp;Reem Zubaidi,&nbsp;Valerie Nash,&nbsp;Maliha Ali,&nbsp;Trenita Childers,&nbsp;Mohammad Wahdatyar,&nbsp;Emily Treichler,&nbsp;Blanca Meléndrez","doi":"10.1002/lrh2.10451","DOIUrl":"10.1002/lrh2.10451","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>In the face of evolving public health challenges, including emerging diseases, pervasive health disparities, and escalating environmental threats, the integration of learning health system (LHS) principles emerges as a vital strategy for enhancing the adaptability and efficacy of public health initiatives. Traditional approaches within these systems often overlook the potential to deeply involve community-based organizations (CBO) that are led and staffed by the communities they serve as equal and essential partners in the public health discourse.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This commentary proposes a suite of nine community-led transformation (CLT) principles aimed at reimagining LHS frameworks to authentically incorporate CBOs at their core. Drawing on the experiences from initiatives supporting Afghan refugees, we illustrate the application of these principles through two detailed case studies.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>These examples demonstrate the CLT principles in action and spotlight the enhanced cultural competency, effectiveness, and equitable power distribution that arise from such partnerships. Centering small to mid-sized CBOs including ethnic-led and/or faith based within LHS structures enables the system to access invaluable cultural insights, strengthen community bonds, and empower those communities to spearhead their transformative journey toward sustainable health, equity, and well-being improvements.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The CLT principles herald a shift toward a more inclusive and co-led public health paradigm by offering a blueprint for stakeholders eager to forge strong, trust-based coalitions and cocreate initiatives with community leaders including Black, Indigenous, and People of Color (BIPOC) leaders from ethnic-led and/or faith-based CBOs. By embracing these principles, public health systems can evolve into truly inclusive, responsive, and sustainable entities poised to advance health equity for all community members.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510007","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 conceptual learning analysis of paired after action and intra action reviews for health emergencies","authors":"Elliot Brennan,&nbsp;Seye Abimbola","doi":"10.1002/lrh2.10447","DOIUrl":"10.1002/lrh2.10447","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Processes of self-reflection and the learning they allow are crucial before, during, and after acute emergencies, including infectious disease outbreaks. Tools—such as Action Reviews—offer World Health Organization (WHO) member states a platform to enhance learning. We sought to better understand the value of these tools and how they may be further refined and better used.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We searched the publicly available WHO Strategic Partnership for Health Security website for paired reports of Action Reviews, that is, reports with a comparable follow-up report. We complemented the paired action reviews, with a literature search, including the gray literature. The paired action reviews were analyzed using the “Learning Health Systems” framework.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified three paired action reviews: Lassa Fever After Action Reviews (AARs) in Nigeria (2017 and 2018), COVID-19 Intra-Action Reviews (IARs) in Botswana (2020 and 2021), and COVID-19 IARs in South Sudan (2020 and 2021). Action Reviews allowed for surfacing relevant knowledge and, by engaging the right (in different contexts) actors, asking “are we doing things right?” (single loop learning) was evident in all the reports. Single loop learning is often embedded within examples of double loop learning (“are we doing the right things?”), providing a more transformative basis for policy change. Triple loop learning (“are we learning right”?) was evident in AARs, and less in IARs. The range of participants involved, the level of concentrated focus on specific issues, the duration available for follow through, and the pressures on the health system to respond influenced the type (i.e., loop) and the effectiveness of learning.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Action Reviews, by design, surface knowledge. With favorable contextual conditions, this knowledge can then be applied and lead to corrective and innovative actions to improve health system performance, and in exceptional cases, continuous learning.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510004","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 public health cancer surveillance capacity to develop and support a rural cancer network","authors":"Jason Semprini,&nbsp;Ingrid M. Lizarraga,&nbsp;Aaron T. Seaman,&nbsp;Erin C. Johnson,&nbsp;Madison M. Wahlen,&nbsp;Jessica S. Gorzelitz,&nbsp;Sarah A. Birken,&nbsp;Mary C. Schroeder,&nbsp;Tarah Paulus,&nbsp;Mary E. Charlton","doi":"10.1002/lrh2.10448","DOIUrl":"10.1002/lrh2.10448","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>As the rural–urban cancer mortality gap widens, centering care around the needs of rural patients presents an opportunity to advance equity. One barrier to delivering patient-centered care at rural hospitals stems from limited analytic capacity to leverage data and monitor patient outcomes. This case study describes the experience of a public health cancer surveillance system aiming to fill this gap within the context of a rural cancer network.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To support the implementation of a novel network model intervention in Iowa, the Iowa Cancer Registry began generating hospital-specific and catchment area reports. Then, the Iowa Cancer Registry supported adapting the network model to fit the context of Iowa's cancer care delivery system by performing data monitoring and reporting functions. Informed by a gap analysis, the Iowa Cancer Registry then identified which quality accreditation standards could be achieved with public health surveillance data and analytic support.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The network intervention in Iowa supported 5 rural cancer centers across the state, each concurrently pursuing quality accreditation standards. The Iowa Cancer Registry's hospital and catchment-specific reports illuminated the cancer burden and needs of rural cancer centers within the network. Our team identified 19 (of the 36 total) quality standards that can be supported by public health surveillance functions typically performed by the registry. These standards encompassed data-driven quality improvement, patient monitoring, and reporting guideline-concordant care standards.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>As rural hospitals continue to face resource constraints, multisectoral efforts informed by data from centralized public health surveillance systems can promote quality improvement initiatives across rural communities. While our work remains preliminary, we predict that analytic support provided by the Iowa Cancer Registry will enable the rural network hospitals to focus their capacity toward developing the infrastructure necessary to deliver high-quality care and serve the unique needs of rural cancer patients.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510011","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":"US public health surveillance, reimagined","authors":"Elina Guralnik","doi":"10.1002/lrh2.10445","DOIUrl":"10.1002/lrh2.10445","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>This study presents two novel concepts for standardizing electronic health records (EHR)-based public health surveillance through utilization of existing informatics methods and data platforms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Drawing from the collective experience in applied epidemiology, health services research and health informatics, the author presents a vision for an alternative path to public health surveillance by repurposing existing tools and resources, such as (1) computable phenotypes which have already been created and validated for a variety of chronic diseases of interest to public health and (2) large data platforms/collaboratives, such as All of Us Research Program and National COVID Cohort Collaborative. Opportunities and challenges are discussed regarding EHR-based chronic disease surveillance, as well as the concept of phenotype definitions and large data platforms reuse for public health needs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results/Framework</h3>\u0000 \u0000 <p>Reusing of computable phenotypes for EHR-based public health surveillance would require secure data platforms and nationally representative data. Standardization metrics for reuse of previously developed and validated computable phenotypes are also necessary and are currently being developed by the author. This study presents a reimagined Learning Health System framework by incorporating Public Health and two novel concept sets of solutions into the healthcare ecosystem.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion/Next Steps</h3>\u0000 \u0000 <p>Alternative approaches to limited resources and current infrastructure of the US Public Health System, especially as applied to disease surveillance, are needed and may be possible when repurposing the resources and methodologies across the Learning Health System.</p>\u0000 </section>\u0000 </div>","PeriodicalId":43916,"journal":{"name":"Learning Health Systems","volume":"8 4","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493541/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510014","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}