研究动态
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识别与林奇综合征肿瘤筛查最佳实施相关的因素和因果链:巧合分析的应用。

Identifying factors and causal chains associated with optimal implementation of Lynch syndrome tumor screening: An application of coincidence analysis.

发表日期:2024 Jun 28
作者: Deborah Cragun, Zachary M Salvati, Jennifer L Schneider, Andrea N Burnett-Hartman, Mara M Epstein, Jessica Ezzell Hunter, Su-Ying Liang, Jan Lowery, Christine Y Lu, Pamala A Pawloski, Victoria Schlieder, Ravi N Sharaf, Marc S Williams, Alanna Kulchak Rahm
来源: MEDICINE & SCIENCE IN SPORTS & EXERCISE

摘要:

本研究比较了多个卫生系统(其中一些有两个或多个不同的 UTS 计划)的林奇综合征通用肿瘤筛查 (UTS),以了解可能影响复杂计划成功实施的多层次因素。使用了来自 66 个利益相关者访谈的数据进行多值重合分析 (mv-CNA),并确定始终对 UTS 计划是否在系统级别实施和优化产生影响的关键因素。所选 CNA 模型揭示了区分 4 个优化 UTS 计划的条件组合,10未优化程序,4个系统无程序。完全优化的悉尼科技大学项目既有维护冠军,也有积极的内部环境。两条独立的路径是非优化计划所特有的:1)积极的态度和混合的内部环境,或 2)有限的计划
This study compared Lynch syndrome universal tumor screening (UTS) across multiple health systems (some of which had two or more distinct UTS programs) to understand multi-level factors that may impact the successful implementation of complex programs.Data from 66 stakeholder interviews were used to conduct multi-value coincidence analysis (mv-CNA) and identify key factors that consistently make a difference in whether UTS programs were implemented and optimized at the system level.The selected CNA model revealed combinations of conditions that distinguish 4 optimized UTS programs, 10 non-optimized programs, and 4 systems with no program. Fully optimized UTS programs had both a maintenance champion and a positive inner setting. Two independent paths were unique to non-optimized programs: 1) positive attitudes and a mixed inner setting, or 2) limited planning & engaging among stakeholders. Negative views about UTS evidence or lack of knowledge about UTS led to a lack of planning and engaging, which subsequently prevented program implementation.The model improved our understanding of program implementation in health care systems and informed the creation of a toolkit to guide UTS implementation, optimization, and changes. Our findings and toolkit may serve as a use case to increase the successful implementation of other complex precision health programs.Copyright © 2024. Published by Elsevier Inc.