Evaluating Digital Health Interventions Key Questions and Approaches
Evaluating Digital Health Interventions Key Questions and Approaches
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DOI：
10.1016/j.amepre.2016.06.008
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发表时间：
2016-11-01
影响因子：
5.5
通讯作者：
Wyatt, Jeremy C.
中科院分区：
文献类型：
--
作者：
Murray, Elizabeth;Hekler, Eric B.;Wyatt, Jeremy C.
数字健康干预措施具有巨大的潜力，可以作为可扩展的工具，通过提高有效性、效率、可访问性、安全性和个性化来改善健康和医疗保健服务。实现这些改进需要积累知识库，为数字健康干预措施的开发和部署提供信息。然而，数字健康干预措施的评估提出了特殊的挑战。本文旨在研究这些挑战，并概述了评估这些干预措施所需的研究问题方面的评估战略。由于它们处于生物医学，行为，计算和工程研究的交叉点，因此需要从所有这些学科中提取的方法。相关的研究问题包括定义问题和数字健康干预的可能益处，这反过来又需要建立干预的可能范围和吸收，因果模型描述干预如何实现其预期的益处，关键组件以及它们如何相互作用，并从有效性，成本效益和危害方面估计整体效益。虽然随机对照试验对于评价有效性和成本效益很重要，但只有在以下情况下才能进行：（1）干预及其交付方案稳定;（2）这些方案可以高保真实施;（3）总体获益具有临床意义的合理可能性（改善结局或以较低成本获得等同结局）。扩大研究问题和评价方法的组合将有助于发展必要的知识基础，为政策、实践和研究决策提供信息。(C)2016年美国预防医学杂志。爱思唯尔公司出版All rights reserved.
Digital health interventions have enormous potential as scalable tools to improve health and healthcare delivery by improving effectiveness, efficiency, accessibility, safety, and personalization. Achieving these improvements requires a cumulative knowledge base to inform development and deployment of digital health interventions. However, evaluations of digital health interventions present special challenges. This paper aims to examine these challenges and outline an evaluation strategy in terms of the research questions needed to appraise such interventions. As they are at the intersection of biomedical, behavioral, computing, and engineering research, methods drawn from all of these disciplines are required. Relevant research questions include defining the problem and the likely benefit of the digital health intervention, which in turn requires establishing the likely reach and uptake of the intervention, the causal model describing how the intervention will achieve its intended benefit, key components, and how they interact with one another, and estimating overall benefit in terms of effectiveness, cost effectiveness, and harms. Although RCTs are important for evaluation of effectiveness and cost effectiveness, they are best undertaken only when: (1) the intervention and its delivery package are stable; (2) these can be implemented with high fidelity; and (3) there is a reasonable likelihood that the overall benefits will be clinically meaningful (improved outcomes or equivalent outcomes at lower cost). Broadening the portfolio of research questions and evaluation methods will help with developing the necessary knowledge base to inform decisions on policy, practice, and research. (C) 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.