Learning Health System study designs for the evaluation of workforce interventions to cultivate eudaimonia (flourishing)

IF 2.6 Q2 HEALTH POLICY & SERVICES
Michael R. Cauley, Anna E. Berry, Carolyn M. Porta, Rachel K. Apple, Sunil Kripalani, Mark Linzer, Emily C. O'Brien, Russell L. Rothman, Christianne L. Roumie
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引用次数: 0

Abstract

Background

The Learning Health System (LHS) framework is designed to enhance healthcare by systematically integrating internal data and external evidence to promote quality, safety, and efficiency, aligning science, informatics, incentives, and culture for continuous improvement, innovation, and equity.

Methods

The Agency for Healthcare Research and Quality (AHRQ) also outlined key LHS learning goals structured around four interconnected approaches: (1) evidence generation to create new knowledge, (2) evidence adoption to translate findings into practice, (3) evidence dissemination to share best practices across systems, and (4) evidence management to integrate internal and external insights using technology and informatics. We propose this model can also enhance workforce well-being (also termed “flourishing” or eudaimonia by Aristotle) through system-level changes informed by rigorously collected local data.

Findings

Healthcare workers who flourish realize their purpose, improve patient health, and align themselves through daily decisions and actions toward this end. However, excessive workload, documentation burden, and unsupported caregiving responsibilities can detract from this goal. A wide range of LHS methods can be applied to address healthcare worker well-being and result in LHS cycles of learning and improvement. We present four examples demonstrating how LHS-concordant research methods align with AHRQ's learning goals to transition from mitigating burnout to actively promoting flourishing.

Contribution

Together, the application of the AHRQ learning goals forms a continuous feedback loop that facilitates mutual enhancement between healthcare delivery and research, advancing clinician well-being and system-wide improvement. This change in focus offers a new method for the design and evaluation of workforce well-being interventions, can restore excellence in patient care, and contributes to creating sustainable, human-centered healthcare systems.

Abstract Image

学习卫生系统研究设计评估劳动力干预培养幸福感(繁荣)
学习健康系统(LHS)框架旨在通过系统地整合内部数据和外部证据来提高质量、安全性和效率,将科学、信息、激励和文化相结合,以实现持续改进、创新和公平,从而提高医疗保健水平。美国卫生保健研究与质量局(AHRQ)还概述了LHS的主要学习目标,这些目标围绕四种相互关联的方法构建:(1)证据生成以创造新知识;(2)证据采纳以将发现转化为实践;(3)证据传播以跨系统共享最佳实践;(4)证据管理以利用技术和信息学整合内部和外部见解。我们提出,该模型还可以通过严格收集的本地数据提供的系统级变化来提高劳动力福祉(亚里士多德也称之为“繁荣”或幸福)。蓬勃发展的医护人员实现了他们的目标,改善了患者的健康,并通过日常决策和行动来实现这一目标。然而,过度的工作量、文档负担和不受支持的护理责任可能会减损这一目标。广泛的LHS方法可用于解决卫生保健工作者的福祉,并导致LHS的学习和改进周期。我们提供了四个例子来证明LHS-concordant研究方法如何与AHRQ的学习目标相一致,从减轻倦怠到积极促进繁荣。AHRQ学习目标的应用形成了一个持续的反馈循环,促进了医疗保健服务和研究之间的相互增强,促进了临床医生的福祉和系统范围的改进。这种重点的变化为设计和评估劳动力福利干预措施提供了一种新方法,可以恢复患者护理的卓越性,并有助于创建可持续的、以人为本的医疗保健系统。
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来源期刊
Learning Health Systems
Learning Health Systems HEALTH POLICY & SERVICES-
CiteScore
5.60
自引率
22.60%
发文量
55
审稿时长
20 weeks
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