Reed Julie E, Green Stuart, Howe Cathy
National Institute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) Northwest London, Chelsea and Westminster Hospital, Imperial College London, London, UK.
Int J Qual Health Care. 2019 Apr 1;31(3):173-182. doi: 10.1093/intqhc/mzy158.
An increasing number of implementation and improvement frameworks seek to describe and explain how change is made in healthcare. This paper aims to explore how existing frameworks conceptualize the influence of complexity in translating evidence into practice in healthcare.
A database was interrogated using a search strategy to identify publications that present frameworks and models for implementation and improvement.
Ten popular implementation and improvement frameworks were purposively selected.
Comparative analysis was conducted using an analytical framework derived from SHIFT-Evidence, a framework that conceptualizes complexity in implementation and improvement initiatives.
Collectively the frameworks accounted for key concepts of translating evidence in complex systems: understanding the uniqueness of each setting; the interdependency of practices/processes and the need to respond to unpredictable events and emergent learning. The analysis highlighted heterogeneity of the frameworks in their focus on different aspects of complexity. Differences include the extent to which problems and solutions are investigated or assumed; whether endpoints are defined as the uptake of interventions or achievement of goals; and emphasis placed on fixed-term interventions versus continual improvement. None of the individual frameworks reviewed incorporated all the implications of complexity, as described by SHIFT-Evidence.
This research identifies the differences in how implementation and improvement frameworks consider complexity, suggesting that SHIFT-Evidence offers a more comprehensive overview compared with the other frameworks. The similarity of concepts across the frameworks suggests growing consensus in the literature, with SHIFT-Evidence providing a conceptual bridge between the implementation and improvement fields.
越来越多的实施与改进框架试图描述和解释医疗保健领域的变革是如何发生的。本文旨在探讨现有框架如何将复杂性对医疗保健领域证据转化为实践的影响概念化。
使用搜索策略查询数据库，以识别展示实施与改进框架及模型的出版物。
有目的地挑选了十个常用的实施与改进框架。
使用源自SHIFT-Evidence的分析框架进行比较分析，该框架将实施与改进举措中的复杂性概念化。
这些框架共同涵盖了复杂系统中证据转化的关键概念：理解每个环境的独特性；实践/流程的相互依存性以及应对不可预测事件和突发学习的必要性。分析突出了这些框架在关注复杂性不同方面时的异质性。差异包括对问题和解决方案的研究或假设程度；终点是定义为干预措施的采用还是目标的实现；以及对定期干预与持续改进的重视程度。所审查的单个框架均未纳入SHIFT-Evidence所描述的复杂性的所有影响。
本研究确定了实施与改进框架在考虑复杂性方面的差异，表明与其他框架相比，SHIFT-Evidence提供了更全面的概述。各框架之间概念的相似性表明文献中正在形成越来越多的共识，SHIFT-Evidence在实施与改进领域之间架起了一座概念桥梁。
