Using RE-AIM metrics to evaluate diabetes self-management support interventions
Using RE-AIM metrics to evaluate diabetes self-management support interventions
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DOI：
10.1016/j.amepre.2005.08.037
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发表时间：
2006-01-01
影响因子：
5.5
通讯作者：
King, DK
中科院分区：
文献类型：
--
作者：
Glasgow, RE;Nelson, CC;King, DK
背景：目前的医疗保健证据依赖于相对狭窄的疗效数据来决定计划的影响。本文阐述了应用影响指数来自RE-AIM（范围、有效性、采用、实施和维护）框架，该框架采用更广泛的视角，并包括对决策者重要的问题，如范围、采用和成本。复合RE-AIM指数总结了个体参与者和设置水平的影响和成本效率，用于比较两种不同的糖尿病自我治疗，管理支持方法。一项名为糖尿病优先（DP）计划的研究涉及来自30个初级保健办公室的886名糖尿病患者，并依赖于常规的临床工作人员执行计划。另一项研究，糖尿病健康连接（DHC），涉及335名糖尿病患者在HMO和收费的服务设置，并使用健康教育staff.Results：DP执行更好的设置水平的影响指数，但程序产生类似的结果对个人水平的影响。DP的覆盖范围更大（50% vs 38%）;在初始随访时更有效（中位效应量[ES]=0.23 vs 0.17）;在不同人群中具有更大的影响一致性。DHC在几个指标上表现更好，包括更高的医生办公室采用率。（20%对6%）和员工采用率（79%对70%），干预人员在方案实施方面的差异较小（中值ES=0.0对0.50）。更多地使用关注公共卫生和外部有效性标准的指数可以帮助确定最有可能对以下方面产生有意义影响的项目：人口健康和适应当地环境和优先事项。
Background: Current healthcare evidence relies on relatively narrow efficacy data to make decisions about program impact. This paper illustrates the application of impact indices derived from the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework that takes a broader perspective and includes issues important to decision makers, such as reach, adoption, and cost.Methods: Composite RE-AIM indices that summarize impact and cost efficiency at the individual participant and setting levels are used to compare two different diabetes self-management support approaches. One study, the Diabetes Priority (DP) program, involved 886 diabetes patients from 30 primary care offices, and relied on usual clinical staff for program implementation. The other study, Diabetes Health Connection (DHC), involved 335 diabetes patients in both HMO and fee-for-service settings, and used health education staff.Results: The DP performed better on the setting-level impact index, but the programs produced similar results on individual-level impact. The DP had a greater reach (50% vs 38%); was more effective at the initial follow-up (median effect size [ES]=0.23 vs 0.17); and had greater impact consistency across various populations. The DHC performed better oil several indices, including higher physician office adoption (20% vs 6%) and staff adoption (79% vs 70%), and there was less variability among intervention staff on protocol implementation (median ES=0.0 vs 0.50).Conclusions: Greater use of indices focused on public health and external validity criteria could help identify programs most likely to have a meaningful impact on population health and to fit local settings and priorities.