Learning Health Systems最新文献_第9页

The Cystic Fibrosis Learning Network: A mixed methods evaluation of program goals, attributes, and impact 囊性纤维化学习网络：项目目标、属性和影响的混合方法评估。

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-12-20 DOI: 10.1002/lrh2.10356

Aricca D. Van Citters, Madge E. Buus-Frank, Joel R. King, Michael Seid, Megan M. Holthoff, Raouf S. Amin, Maria T. Britto, Eugene C. Nelson, Bruce C. Marshall, Kathryn A. Sabadosa

Introduction

The Cystic Fibrosis (CF) Foundation sponsored the design, pilot testing, and implementation of the CF Learning Network (CFLN) to explore how the Foundation's Care Center Network (CCN) could become a learning health system. Six years after the design, the Foundation commissioned a formative mixed methods evaluation of the CFLN to assess: CFLN participants' understanding of program goals, attributes, and perceptions of current and future impact.

Methods

We performed semi-structured interviews with CFLN participants to identify perceived goals, attributes, and impact of the network. Following thematic analyses, we developed and distributed a survey to CFLN members and a matched sample of CCN programs to understand whether the themes were unique to the CFLN.

Results

Interviews with 24 CFLN participants were conducted. Interviewees identified the primary CFLN goal as improving outcomes for people living with CF, with secondary goals of providing training in quality improvement (QI), creating a learning community, engaging all stakeholders in improvement, and spreading best practices to the CCN. Project management, use of data, common QI methods, and the learning community were seen as critical to success. Survey responses were collected from 103 CFLN members and 25 CCN members. The data revealed that CFLN respondents were more likely than CCN respondents to connect with other CF programs, routinely use data for QI, and engage patient and family partners in QI.

Conclusions

Our study suggests that the CFLN provides value beyond that achieved by the CCN. Key questions remain about whether spread of the CFLN could improve outcomes for more people living with CF.

简介：囊性纤维化（CF）基金会赞助了CF学习网络（CFLN）的设计、试点测试和实施，以探索基金会的护理中心网络（CCN）如何成为一个学习型健康系统。设计六年后，基金会委托对CFLN进行形成性混合方法评估，以评估：CFLN参与者对项目目标、属性的理解，以及对当前和未来影响的看法。方法：我们对CFLN参与者进行了半结构化访谈，以确定网络的感知目标、属性和影响。在主题分析之后，我们制定并分发了一份调查给CFLN成员和CCN项目的匹配样本，以了解这些主题是否是CFLN独有的。结果：对24名CFLN参与者进行了访谈。受访者确定，CFLN的主要目标是改善CF患者的结果，次要目标是提供质量改进培训（QI），创建学习社区，让所有利益相关者参与改进，并向CCN传播最佳实践。项目管理、数据的使用、常见的QI方法和学习社区被视为成功的关键。从103名解阵线成员和25名CCN成员收集了调查答复。数据显示，与CCN受访者相比，CFLN受访者更有可能与其他CF项目建立联系，常规使用QI数据，并让患者和家庭伙伴参与QI。结论：我们的研究表明，CFLN提供的价值超过了CCN实现的价值。关于CFLN的传播是否能改善更多CF患者的预后，关键问题仍然存在。

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引用次数: 1

Establishing a Cystic Fibrosis Learning Network: Interventions to promote collaboration and data-driven improvement at scale 建立囊性纤维化学习网络：促进合作和数据驱动的大规模改进的干预措施。

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-12-19 DOI: 10.1002/lrh2.10354

Thida Ong, Dana Albon, Raouf S. Amin, Julianna Bailey, Srujana Bandla, Maria T. Britto, Jonathan Flath, Breck Gamel, Michael Powers, Kathryn A. Sabadosa, Anna K. Saulitis, Lacrecia K. Thomas, Sophia Thurmond, Michael Seid, the Cystic Fibrosis Learning Network

Introduction

A learning health network is a type of learning health system in which stakeholders use network organization to improve health and health care. Building on existing resources in the cystic fibrosis (CF) community, the Cystic Fibrosis Learning Network (CFLN) was designed to improve medical outcomes and quality of life through an intentional focus on achieving reliable evidence-based chronic care delivery and creating a system for data-driven collaborative learning.

Methods

We describe the development and growth of the CFLN considering six domains of a Network Maturity Grid: system leadership; governance and policy management; quality improvement (QI); engagement and community building; data and analytics; and research. We illustrate the impact of the CFLN experience on chronic care processes and indicators of collaborative infrastructure.

Results

The CFLN represents 36 accredited care centers in the CF Foundation Care Center Network caring for over 6300 patients. Of 6779 patient clinical care visits/quarter, 77% are entered into the CF Foundation Patient Registry within 30 days, providing timely means to track outcomes. Collaborative visit planning is occurring in 93% of clinical care visits to share agenda setting with patients and families. Almost all CFLN teams (94%, n = 34) have a patient/family partner (PFP), and 74% of PFPs indicate they are actively participating, taking ownership of, or leading QI initiatives with the interdisciplinary care team. In 2022, 97% of centers reported completing 1–13 improvement cycles per month, and 82% contributed to monthly QI progress reports to share learning.

Conclusion

The CFLN is a maturing, collaborative infrastructure. CFLN centers practice at an advanced level of coproduction. The CFLN fosters interdisciplinary and PFP leadership and the performance of consistent data-driven improvement cycles. CFLN centers are positioned to respond to rapid changes in evidence-based care and advance the practice of QI and implementation science on a broader scale.

引言：学习型健康网络是一种学习型健康系统，利益相关者利用网络组织来改善健康和医疗保健。在囊性纤维化（CF）社区现有资源的基础上，囊性纤维化学习网络（CFLN）旨在通过有意专注于实现可靠的循证慢性护理提供和创建数据驱动的协作学习系统来改善医疗结果和生活质量。方法：我们描述了CFLN的发展和增长，考虑了网络成熟度网格的六个领域：系统领导；治理和政策管理；质量改进；参与和社区建设；数据和分析；和研究。我们展示了CFLN经验对慢性病护理流程和合作基础设施指标的影响。结果：CFLN代表CF基金会护理中心网络中的36个认证护理中心，照顾6300多名患者。在每季度6779次患者临床护理就诊中，77%在30天内进入CF基金会患者登记处天，提供及时的方法来跟踪结果。93%的临床护理就诊都进行了协作就诊计划，以与患者和家属共享议程设置。几乎所有的CFLN团队（94%，n=34）都有患者/家庭伙伴（PFP），74%的PFP表示他们积极参与、拥有或领导跨学科护理团队的QI倡议。2022年，97%的中心报告每月完成1-13个改进周期，82%的中心每月提交QI进度报告以分享学习。结论：CFLN是一个成熟的合作基础设施。CFLN以先进的合作生产水平为中心进行实践。CFLN培养跨学科和PFP的领导力，以及一致的数据驱动改进周期的绩效。CFLN中心的定位是应对循证护理的快速变化，并在更广泛的范围内推进QI和实施科学的实践。

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引用次数: 3

Reducing hospital acquired pressure injury in a learning health center: Making the case for quality 在学习型健康中心减少医院获得性压力伤害:为质量辩护

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-12-15 DOI: 10.1002/lrh2.10355

Shea Polancich, Patricia Patrician, Rebecca Miltner, Katherine Meese, Amy Armstrong, Shannon Layton, Ross Vander Noot, Terri Poe, Allyson G. Hall

Introduction

The purpose of this descriptive study is to examine a learning health system (LHS) continuous improvement and learning approach as a case for increased quality, standardized processes, redesigned workflows, and better resource utilization. Hospital acquired pressure injuries (HAPI) commonly occur in the hospitalized patient and are costly and preventable. This study examines the effect of a LHS approach to reducing HAPI within a large academic medical center.

Methods

Our learning health center implemented a 6-year series of iterative improvements that included both process and technology changes, with robust data and analytical reforms. In this descriptive, observational study, we retrospectively examined longitudinal data from April 1, 2018 to March 31, 2022, examining the variables of total number of all-stage HAPI counts and average length of stay (ALOS). We also analyzed patient characteristics observed/expected mortality ratios, as well as total patient days, and the case-mix index to determine whether these factors varied over the study period. We used the Agency for Healthcare Research and Quality cost estimates to identify the estimated financial benefit of HAPI reductions on an annualized basis.

Results

HAPI per 1000 patient days for FY 20 (October 1-September 30) and FY 21, decreased from 2.30 to 1.30 and annualized event AHRQ cost estimates for HAPI decreased by $4 786 980 from FY 20 to FY 21. A strong, statistically significant, negative and seemingly counterintuitive correlation was found (r = −.524, P = .003) between HAPI and ALOS.

Conclusions

The LHS efforts directed toward HAPI reduction led to sustained improvements during the study period. These results demonstrate the benefits of a holistic approach to quality improvement offered by the LHS model. The LHS model goes beyond a problem-based approach to process improvement. Rather than targeting a specific problem to solve, the LHS system creates structures that yield process improvement benefits over a continued time period.

引言本描述性研究的目的是检验学习健康系统（LHS）的持续改进和学习方法，以提高质量、标准化流程、重新设计工作流程和更好地利用资源。医院获得性压力损伤（HAPI）通常发生在住院患者身上，费用高昂且可预防。这项研究考察了大型学术医疗中心内LHS方法降低HAPI的效果。方法我们的学习健康中心实施了一系列为期6年的迭代改进，包括流程和技术变革，以及稳健的数据和分析改革。在这项描述性观察性研究中，我们回顾性检查了2018年4月1日至2022年3月31日的纵向数据，检查了所有阶段HAPI计数总数和平均住院时间（ALOS）的变量。我们还分析了观察到的/预期的患者特征死亡率、总患者天数和病例组合指数，以确定这些因素是否在研究期间发生变化。我们使用医疗保健研究和质量机构的成本估算来确定每年减少HAPI的估计财务效益。结果20财年（10月1日至9月30日）和21财年每1000个患者日的HAPI从2.30下降到1.30，HAPI的年度事件AHRQ成本估计下降了4美元 786 980。HAPI和ALOS之间存在强烈的、具有统计学意义的、负的、似乎违反直觉的相关性（r=−.524，P=.003）。结论在研究期间，LHS致力于减少HAPI的努力导致了持续的改善。这些结果证明了LHS模型提供的整体质量改进方法的好处。LHS模型超越了基于问题的过程改进方法。LHS系统不是针对特定的问题来解决，而是创建在持续的时间段内产生过程改进效益的结构。

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引用次数: 1

Hurdles of innovation—insights from a new healthcare delivery innovation program 创新的障碍——来自一个新的医疗服务创新项目的见解

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-11-02 DOI: 10.1002/lrh2.10353

Shoshana Bardach, Amanda Perry, Lillian Powell, Nirav Kapadia, Amber Barnato

Introduction

Healthcare systems are actively working to innovate their care delivery models, seeking to improve service quality, improve patient and provider satisfaction, and reduce cost.

Methods

By critically evaluating our experiences to date, this article highlights challenges systems may face in the process of trying to redesign healthcare and offers insights on how to navigate hurdles. We identify barriers to—and ultimately approaches to promote—rapid, scalable, sustainable, and transformative care redesign.

Results

Dedicated electronic health record IT and analytic support, and ongoing leadership engagement and communication, play a valuable role in enabling redesign efforts. Flexible, but guided, innovation support helps teams stay accountable and motivated, while accommodating new project needs and directions. Understanding the change ecosystem and evaluating and sharing outcomes on an ongoing basis, enables teams to adapt as needed. Facilitation and support help realize the value of diverse, engaged teams; novel approaches and techniques draw out innovative perspectives and promote creative thinking.

Conclusions

Although not an exhaustive list of challenges or strategies to overcome them, we hope these insights will contribute to a culture of innovation and support other institutions in their healthcare redesign initiatives.

医疗保健系统正在积极创新他们的医疗服务模式，寻求提高服务质量，提高病人和提供者的满意度，并降低成本。方法通过批判性地评估我们迄今为止的经验，本文强调了系统在尝试重新设计医疗保健过程中可能面临的挑战，并提供了如何克服障碍的见解。我们确定障碍和最终促进快速，可扩展，可持续和变革性的护理重新设计的方法。结果:专门的电子健康记录IT和分析支持，以及持续的领导参与和沟通，在实现重新设计工作中发挥了重要作用。灵活但有指导的创新支持帮助团队保持责任和动力，同时适应新的项目需求和方向。了解变更生态系统，并在持续的基础上评估和共享结果，使团队能够根据需要进行调整。促进和支持有助于实现多元化、敬业团队的价值;新颖的方法和技术引出创新的观点，促进创造性思维。尽管没有详尽的挑战列表或克服这些挑战的策略，但我们希望这些见解将有助于创新文化，并支持其他机构的医疗保健重新设计计划。

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引用次数: 0

Guiding principles for technical infrastructure to support computable biomedical knowledge 支持可计算生物医学知识的技术基础设施指导原则

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-11-01 DOI: 10.1002/lrh2.10352

Jamie McCusker, Leslie D. McIntosh, Chris Shaffer, Peter Boisvert, James Ryan, Vivek Navale, Umit Topaloglu, Rachel L. Richesson

Over the past 4 years, the authors have participated as members of the Mobilizing Computable Biomedical Knowledge Technical Infrastructure working group and focused on conceptualizing the infrastructure required to use computable biomedical knowledge. Here, we summarize our thoughts and lay the foundation for future work in the development of CBK infrastructure, including: explaining the difference between computable knowledge and data, and contextualizing the conversation with the Learning Health Systems and the FAIR principles. Specifically, we provide three guiding principles to advance the development of CBK infrastructure: (a) Promote interoperable systems for data and knowledge to be findable, accessible, interoperable, and reusable. (b) Enable stable, trustworthy knowledge representations that are human and machine readable. (c) Computable knowledge resources should, when possible, be open. Standards supporting computable knowledge infrastructures must be open.

在过去的4年里，作者作为动员可计算生物医学知识技术基础设施工作组的成员，专注于概念化使用可计算生物医学知识所需的基础设施。在这里，我们总结了我们的想法，并为CBK基础设施发展的未来工作奠定了基础，包括:解释可计算知识和数据之间的区别，并将与学习健康系统和公平原则的对话置于背景下。具体而言，我们提出了推进CBK基础设施发展的三个指导原则:(a)促进数据和知识的可互操作系统的可查找、可访问、可互操作和可重用。(b)实现人类和机器可读的稳定、可信的知识表示。(c)可计算的知识资源应尽可能开放。支持可计算知识基础设施的标准必须是开放的。

引用次数: 1

Developing a highly-reliable learning health system 发展高度可靠的学习卫生系统

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-10-27 DOI: 10.1002/lrh2.10351

Robert El-Kareh, David A. Brenner, Christopher A. Longhurst

Multiple independent frameworks to support continuous improvement have been proposed to guide healthcare organizations. Two of the most visible are High-reliability Health care, (Chassin et al., 2013) which is emphasized by The Joint Commission, and Learning Health Systems, (Institute of Medicine, 2011) highlighted by the National Academy of Medicine. We propose that organizations consider tightly linking these two models, creating a “Highly-reliable Learning Health System.” We describe several efforts at our organization that has resulted from this combined model and have helped our organization weather the COVID-19 pandemic. The organizational changes created using this framework will enable our health system to support a culture of quality across our teams and better fulfill our tripartite mission of high-quality care, effective education of trainees, and dissemination of important innovations.

已经提出了支持持续改进的多个独立框架，以指导医疗保健组织。其中最明显的两个是由联合委员会强调的高可靠性医疗保健(Chassin et al.， 2013)和由国家医学院强调的学习卫生系统(医学研究所，2011)。我们建议组织考虑将这两种模式紧密联系起来，创建一个“高度可靠的学习健康系统”。我们描述了该组合模型在我们组织中产生的几项努力，并帮助我们组织度过了COVID-19大流行。利用这一框架所产生的组织变革将使我们的卫生系统能够在我们的团队中支持质量文化，并更好地履行我们的三重使命:高质量的护理、对受训者的有效教育和重要创新的传播。

引用次数: 1

Unpacking the challenges of conducting embedded, learning health system research: The winning entries of a Challenge Contest sponsored by AcademyHealth 解开进行嵌入式学习卫生系统研究的挑战:由健康学院赞助的挑战赛的获奖作品

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-10-17 DOI: 10.1002/lrh2.10346

Project : injuries (PrIs) worsen patient morbidity and increase hospital costs. Early recognition is imperative for reducing preventable harm. A process improvement project, TIC DOWN PrI, was undertaken to decrease PrIs by increasing the performance of a 2-RN skin assessment within 24 hours of admission using video technology and TeleICU RNs. TeleICU RNs docu-ment assessment findings, review PrI prevention best practices, and discuss missed opportunities with the bedside RNs. Wound Ostomy Continence RNs are consulted for validating skin alter-ations, when necessary. The project is being conducted in three medical ICUs (79 beds) within the BJC Healthcare System from October 2021 to March 2023. No funding was received for the project.

引用次数: 0

Development of a learning health system science competency assessment to guide training and proficiency assessment 发展学习型卫生系统科学能力评估，以指导培训和能力评估

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-10-14 DOI: 10.1002/lrh2.10343

Patricia D. Franklin, Denise Drane, Lauren Wakschlag, Ronald Ackerman, Abel Kho, David Cella

<div> <section> <h3> Introduction</h3> <p>Learning health systems (LHS) science is fundamentally a transdisciplinary field. To capture the breadth of the competencies of an LHS scientist, AHRQ and national experts defined a series of 42 competencies across seven domains that support success. Clinicians, researchers, and leaders who are new to the LHS field can identify and prioritize proficiency development among these domains. In addition, existing leaders and researchers will assemble teams of experts who together represent the LHS science domains. To serve LHS workforce development and proficiency assessment, the AHRQ-funded ACCELERAT K12 training program recruited domain experts and trainees to define and operationalize items to include in an LHS Competency Assessment to support emerging and existing LHS scientists in prioritizing and monitoring proficiency development.</p> </section> <section> <h3> Methods</h3> <p>Sequential interviews with 18 experts iteratively defined skills and tasks to illustrate stage in proficiency, and its progression, for each of 42 competencies in the seven LHS expertise domains: systems science; research questions and standards of scientific evidence; research methods; informatics; ethics of research and implementation in health systems; improvement and implementation science; and engagement, leadership, and research management. An educational assessment expert and LHS scientist refined the assessment criteria at each stage to use parallel language across domains. Last, current trainees reviewed and pilot tested the assessment and the LHS Competency Assessment was further refined using their feedback. The assessment framework was informed by Bloom's revised taxonomy of educational objectives (Anderson and Krathwohl, A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives, 2001) where learning progresses from recalling, defining, understanding, and awareness at the lower levels of the taxonomy, to applying and adopting and finally to creating, designing, and critiquing at the upper levels of the taxonomy. We also developed assessment criteria that could be used for longer term assessment of direct performance. Van der Vleuten et al. (Best Pract Res Clin Obstetr Gynaecol. 2010;24(6):703-719) define longer term direct assessment methods as assessment that occurs over a period ranging from weeks to even years and involves multiple assessment methods and exposure to the learner's work over an extended period.</p> </section> <section> <h3> Results</h3> <p>This experience report describes the content of the LHS Competency Assessment. For each domain and competency, the ass

学习卫生系统(LHS)科学基本上是一个跨学科领域。为了掌握LHS科学家能力的广度，AHRQ和国家专家在七个领域定义了一系列支持成功的42项能力。临床医生、研究人员和LHS领域的新领导者可以在这些领域中识别和优先考虑熟练程度的发展。此外，现有的领导和研究人员将组建专家团队，共同代表LHS科学领域。为了服务于LHS劳动力的发展和能力评估，ahrq资助的加速器K12培训项目招募了领域专家和受训人员来定义和实施LHS能力评估中的项目，以支持新兴和现有的LHS科学家优先考虑和监测能力发展。方法对18位专家进行连续访谈，反复定义技能和任务，以说明LHS七个专业领域的42个能力中的每一个能力的熟练程度及其进展:系统科学;科学证据的研究问题与标准研究方法;信息学;卫生系统研究和实施的伦理;改进与实施科学;参与，领导和研究管理。一位教育评估专家和LHS科学家对每个阶段的评估标准进行了细化，以跨领域使用并行语言。最后，在职学员对评估进行了回顾和试点测试，并根据他们的反馈进一步完善了LHS能力评估。评估框架是由布鲁姆修订的教育目标分类法(安德森和克拉斯沃，《学习、教学和评估的分类法:布鲁姆教育目标分类法的修订版》，2001年)提供的，其中学习从分类法较低层次的回忆、定义、理解和意识，到分类法较高层次的应用和采用，最后到创造、设计和批评。我们还制定了可用于长期直接绩效评估的评估标准。Van der Vleuten等人(Best practice Res clinical obstetrics妇科，2010;24(6):703-719)将长期直接评估方法定义为持续数周甚至数年的评估，包括多种评估方法，并在较长一段时间内对学习者的工作进行观察。结果本经验报告描述了LHS胜任力评估的内容。对于每个领域和能力，评估列出了证据示例，以支持每个熟练程度的专业知识:没有接触;基础(认识/了解);新兴(早期申请);精通(高水平技能的应用)。受训者从基线标准评估表开始，在那里他们可以表明没有接触或标记他们有能力的基础和新兴技能。对于已经获得基础和新兴技能的领域，用户可以转到列出熟练程度证据的评估表。结论LHS能力评估在LHS 7个领域提供了一致的分级标准，指导学员和导师评估从无经验到基础知识、新熟练程度和熟练程度的进展。该评估还可用于为刚接触生命卫生科学的人员和希望扩展生命卫生专业知识的具有关键专业知识的人员设计培训和指导。

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引用次数: 4

Learning health system, positive deviance analysis, and electronic health records: Synergy for a learning health system 学习型健康系统，积极偏差分析和电子健康记录:学习型健康系统的协同作用

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-10-11 DOI: 10.1002/lrh2.10348

Kristen M.J. Azar, Mark J. Pletcher, Sarah M. Greene, Alice R. Pressman

Introduction

Over the past decade, numerous efforts have encouraged the realization of the learning health system (LHS) in the United States. Despite these efforts, and promising aims of the LHS, the full potential and value of research conducted within LHSs have yet to be realized. New technology coupled with a catalyzing global pandemic have spurred momentum. In addition, the LHS has lacked a consistent framework within which “best evidence” can be identified. Positive deviance analysis, itself reinvigorated by recent advances in health information technology (IT) and ubiquitous adoption of electronic health records (EHRs), may finally provide a framework through which LHSs can be operationalized and optimized.

Methods

We describe the synergy between positive deviance and the LHS and how they may be integrated to achieve a continuous cycle of health system improvement.

Results

As we describe below, the positive deviance approach focuses on learning from high-performing teams and organizations.

Conclusion

Such learning can be enabled by EHRs and health IT, providing a lens into how digital clinical interventions are successfully developed and deployed.

在过去的十年中，许多努力鼓励了美国学习型医疗系统(LHS)的实现。尽管做出了这些努力，LHS的目标也很有希望，但在LHS内进行的研究的全部潜力和价值尚未实现。新技术加上催化性的全球大流行推动了这一势头。此外，LHS缺乏一个可以确定“最佳证据”的一致框架。积极偏差分析本身因最近卫生信息技术(IT)的进步和电子健康记录(EHRs)的普遍采用而重新焕发活力，最终可能提供一个框架，通过该框架，lhs可以运作和优化。方法我们描述了积极偏差和LHS之间的协同作用，以及如何将它们整合起来以实现卫生系统改进的连续循环。正如我们下面所描述的，积极偏差方法侧重于向高绩效团队和组织学习。这样的学习可以通过电子病历和医疗信息技术来实现，为数字化临床干预的成功开发和部署提供了一个视角。

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引用次数: 0

Evaluating a learning health system initiative: Lessons learned during COVID-19 in Saskatchewan, Canada 评估学习型卫生系统倡议:加拿大萨斯喀彻温省在COVID-19期间吸取的经验教训

IF 3.1 Q2 HEALTH POLICY & SERVICES

Learning Health Systems

Pub Date : 2022-10-09 DOI: 10.1002/lrh2.10350

Gary Groot, Stephanie Witham, Andreea Badea, Susan Baer, Michelle Dalidowicz, Bruce Reeder, John Froh, Tracey Carr

Introduction

Evaluating a learning health system (LHS) encourages continuous system improvement and collaboration within the healthcare system. Although LHS is a widely accepted concept, there is little knowledge about evaluating an LHS. To explore the outputs and outcomes of an LHS model, we evaluated the COVID-19 Evidence Support Team (CEST) in Saskatchewan, Canada, an initiative to rapidly review scientific evidence about COVID-19 for decision-making. By evaluating this program during its formation, we explored how and to what extent the CEST initiative was used by stakeholders. An additional study aim was to understand how CEST could be applied as a functional LHS and the value of similar knowledge-to-action cycles.

Methods

Using a formative evaluation design, we conducted qualitative interviews with key informants (KIs) who were involved with COVID-19 response strategies in Saskatchewan. Transcripts were analyzed using reflexive thematic analysis to identify key themes. A program logic model was created to represent the inputs, activities, outputs, and outcomes of the CEST initiative.

Results

Interview data from 11 KIs were collated under three overarching categories: (1) outputs, (2) short-term outcomes, and (3) long-term outcomes from the CEST initiative. Overall, participants found the CEST initiative improved speed and access to reliable information, supported and influenced decision-making and public health strategies, leveraged partnerships, increased confidence and reassurance, and challenged misinformation. Themes relating to the long-term outcomes of the initiative included improving coordination, awareness, and using good judgment and planning to integrate CEST sustainably into the health system.

Conclusion

This formative evaluation demonstrated that CEST was a valued program and a promising LHS model for Saskatchewan. The future direction involves addressing program recommendations to implement this model as a functional LHS in Saskatchewan.

引言评估学习型医疗系统（LHS）鼓励医疗系统内持续的系统改进和协作。尽管LHS是一个被广泛接受的概念，但对评估LHS知之甚少。为了探索LHS模型的输出和结果，我们评估了加拿大萨斯喀彻温省的新冠肺炎证据支持小组（CEST），该小组旨在快速审查有关新冠肺炎的科学证据以供决策。通过在该计划形成期间对其进行评估，我们探讨了利益相关者如何以及在多大程度上使用CEST倡议。另一项研究的目的是了解CEST如何作为一种功能性LHS应用，以及类似知识对行动周期的价值。方法采用形成性评价设计，对萨斯喀彻温省参与新冠肺炎应对策略的关键信息者（KI）进行定性访谈。使用反身主题分析来分析转录本，以确定关键主题。创建了一个程序逻辑模型来表示CEST倡议的输入、活动、输出和结果。结果11个KI的访谈数据按三个总体类别进行了整理：（1）产出，（2）短期结果，（3）CEST倡议的长期结果。总体而言，与会者发现，CEST倡议提高了获得可靠信息的速度，支持和影响了决策和公共卫生战略，利用了伙伴关系，增强了信心和保证，并挑战了错误信息。与该倡议的长期成果有关的主题包括加强协调、提高认识，并利用良好的判断和规划，将CEST可持续地纳入卫生系统。结论该形成性评价表明，CEST是一个有价值的项目，也是萨斯喀彻温省一个有前景的LHS模式。未来的方向包括解决在萨斯喀彻温省将该模型作为功能性LHS实施的计划建议。

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引用次数: 1