背景:生活方式医学(LM)是使用治疗性生活方式的改变(包括全食物,植物为主的饮食模式;定期的体育锻炼;恢复性睡眠;压力管理;避免危险物质;和积极的社交联系)以预防和治疗慢性病。尽管有越来越多的证据,LM仍未在医疗机构中广泛实施。实施研究综合框架(CFIR)在实施科学中通常被引用,可用于确定促进者和实施障碍。LM实施的潜在挑战包括缺乏临床医生培训,人员配置问题,以及LM服务与按服务收费报销的错位;但尚未了解促进或阻碍其实施和长期成功的全部因素。学习成功和失败的重要教训,了解不同LM程序的经验至关重要。
目的:本文的目的是深入描述用于识别影响卫生系统实施LM的障碍和促进因素的协议。
方法:研究小组由ACLM工作人员和具有公共卫生专业知识的研究人员组成,LM,和定性研究。我们招募了ACLM卫生系统委员会成员的卫生系统。在15个自我提名的卫生系统中,我们选择了七个来代表地理位置的多样性,type,尺寸,专业知识,资金,病人,和LM服务。研究的一部分,我们又招募了一个对比鲜明的卫生系统作为阴性病例。对于每种情况,我们进行了深入采访,文件审查,实地考察(由于新冠肺炎大流行而受到限制),和研究小组汇报。面试持续了45-90分钟,并遵循半结构化的面试指南,松散地基于CFIR模型。我们正在为每个卫生系统构建详细的病例叙述报告,随后在跨案例分析中使用,以开发对各种预先确定的和紧急的主题的上下文丰富和详细的理解。跨案例分析将借鉴各种方法,包括深入的案例熟悉和归纳/演绎编码,以识别交叉主题。
结果:研究小组已经完成了所有八个参与卫生系统的数据收集,包括68次采访和一次实地考察。我们目前正在起草描述性案例叙述,它将传播给参与的卫生系统,供成员检查,并作为应用小插曲广泛分享。我们还在进行跨案例分析,以确定关键的促进者和障碍,探索临床医生培训策略,以促进LM的实施,并建立一个解释模型,将从业者对LM的采用和职业倦怠的经验联系起来。
结论:本协议文件提供了对研究方法和实践的真实见解,以确定在卫生系统中实施LM的障碍和促进者。研究结果可以建议跨各种卫生系统上下文的LM实施。方法的局限性和经验教训可以指导其他类似方法的研究的执行。
背景:
BACKGROUND: Lifestyle medicine (LM) is the use of therapeutic lifestyle changes (including a whole-food, plant-predominant eating pattern; regular physical activity; restorative sleep; stress management; avoidance of risky substances; and positive social connection) to prevent and treat chronic illness. Despite growing evidence, LM is still not widely implemented in health care settings. Potential challenges to LM implementation include lack of clinician training, staffing concerns, and misalignment of LM services with fee-for-service reimbursement, but the full range of factors facilitating or obstructing its implementation and long-term success are not yet understood. To learn important lessons for success and failure, it is crucial to understand the experiences of different LM programs.
OBJECTIVE: This study aims to describe in depth the protocol used to identify barriers and facilitators impacting the implementation of LM in health systems.
METHODS: The study team comprises team members at the American College of Lifestyle Medicine (ACLM), including staff and researchers with expertise in public health, LM, and qualitative research. We recruited health systems that were members of the ACLM Health Systems Council. From among 15 self-nominating health systems, we selected 7 to represent a diversity of geographic location, type, size, expertise, funding, patients, and LM services. Partway through the study, we recruited 1 additional contrasting health system to serve as a negative
case. For each
case, we conducted in-depth interviews, document reviews, site visits (limited due to the COVID-19 pandemic), and study team debriefs. Interviews lasted 45-90 minutes and followed a semistructured interview guide, loosely based on the Consolidated Framework for Implementation Research (CFIR) model. We are constructing detailed
case narrative
reports for each health system that are subsequently used in cross-case analyses to develop a contextually rich and detailed understanding of various predetermined and emergent topics. Cross-
case analyses will draw on a variety of methodologies, including in-depth
case familiarization, inductive or deductive coding, and thematic analysis, to identify cross-cutting themes.
RESULTS: The study team has completed data collection for all 8 participating health systems, including 68 interviews and 1 site visit. We are currently drafting descriptive
case narratives, which will be disseminated to participating health systems for member checking and shared broadly as applied vignettes. We are also conducting cross-case analyses to identify critical facilitators and barriers, explore clinician training strategies to facilitate LM implementation, and develop an explanatory model connecting practitioner adoption of LM and experiences of burnout.
CONCLUSIONS: This protocol paper offers real-world insights into research methods and practices to identify barriers and facilitators to the implementation of LM in health systems. Findings can advise LM implementation across various health system contexts. Methodological limitations and lessons learned can guide the execution of other studies with similar methodologies.
UNASSIGNED: DERR1-10.2196/51562.