数字健康干预经济评估中的分析框架和结果测量:方法系统回顾。

IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Valerio Benedetto, Luís Filipe, Catherine Harris, Joseph Spencer, Carmel Hickson, Andrew Clegg
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引用次数: 2

摘要

背景:数字卫生干预(DHIs)可以改善卫生保健服务的提供。为了在经济评价中充分考虑其影响,以衡量与健康有关的生活质量为基础的传统方法可能不合适,因为非健康和过程结果也可能相关。目的:本系统综述识别、评估和综合了在DHIs经济评估中使用的分析框架和结果测量的论点。结果为今后的经济评价提供了建议。数据来源:我们在多个数据库中进行了搜索,并辅以灰色文献和前后引文搜索。研究选择:我们纳入了包含与使用分析框架和结果测量方法进行DHIs经济评估相关的理论和实证论点的记录。经过标题/摘要和全文筛选,我们的最终分析包括15项研究。数据提取:我们提取的论点与分析框架(14项研究)、通用结果测量(5项研究)、用于得出效用值的技术(3项研究)以及特定疾病的结果测量和收集健康状态数据的工具(均来自2项研究)有关。数据综合:我们不是评估研究的质量,而是批判性地评估和综合提取的论点。在此综合基础上,我们制定了一套分为三个阶段的建议,其中我们鼓励使用影响矩阵和公平影响分析来整合传统的经济评估方法。局限性:我们的综述和建议探讨了但未完全涵盖超出我们范围的经济评估的其他潜在重要方面。结论:这是第一个系统综述,总结了如何在经济评估中衡量DHIs的影响的论点。我们的建议将有助于设计未来的经济评估。重点:在数字卫生干预措施的经济评估中,使用基于健康相关生活质量的传统结果度量(如质量调整生命年)可能不合适,因为这可能引发非健康和过程结果。这是研究如何在经济评估中衡量数字卫生干预措施的影响的第一个系统综述。我们从文献中提取并综合了不同的论点,概述了用于衡量数字健康干预效果的不同方法的优缺点。我们提出了一套方法建议,其中1)我们建议研究人员考虑使用影响矩阵和成本后果分析,2)我们讨论了经济评估中可用的分析框架和结果测量的适用性,3)我们强调了分析公平影响的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review.

Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review.

Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review.

Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review.

Background: Digital health interventions (DHIs) can improve the provision of health care services. To fully account for their effects in economic evaluations, traditional methods based on measuring health-related quality of life may not be appropriate, as nonhealth and process outcomes are likely to be relevant too.

Purpose: This systematic review identifies, assesses, and synthesizes the arguments on the analytical frameworks and outcome measures used in the economic evaluations of DHIs. The results informed recommendations for future economic evaluations.

Data sources: We ran searches on multiple databases, complemented by gray literature and backward and forward citation searches.

Study selection: We included records containing theoretical and empirical arguments associated with the use of analytical frameworks and outcome measures for economic evaluations of DHIs. Following title/abstract and full-text screening, our final analysis included 15 studies.

Data extraction: The arguments we extracted related to analytical frameworks (14 studies), generic outcome measures (5 studies), techniques used to elicit utility values (3 studies), and disease-specific outcome measures and instruments to collect health states data (both from 2 studies).

Data synthesis: Rather than assessing the quality of the studies, we critically assessed and synthesized the extracted arguments. Building on this synthesis, we developed a 3-stage set of recommendations in which we encourage the use of impact matrices and analyses of equity impacts to integrate traditional economic evaluation methods.

Limitations: Our review and recommendations explored but not fully covered other potentially important aspects of economic evaluations that were outside our scope.

Conclusions: This is the first systematic review that summarizes the arguments on how the effects of DHIs could be measured in economic evaluations. Our recommendations will help design future economic evaluations.

Highlights: Using traditional outcome measures based on health-related quality of life (such as the quality-adjusted life-year) may not be appropriate in economic evaluations of digital health interventions, which are likely to trigger nonhealth and process outcomes.This is the first systematic review to investigate how the effects of digital health interventions could be measured in economic evaluations.We extracted and synthesized different arguments from the literature, outlining advantages and disadvantages associated with different methods used to measure the effects of digital health interventions.We propose a methodological set of recommendations in which 1) we suggest that researchers consider the use of impact matrices and cost-consequence analysis, 2) we discuss the suitability of analytical frameworks and outcome measures available in economic evaluations, and 3) we highlight the need for analyses of equity impacts.

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来源期刊
Medical Decision Making
Medical Decision Making 医学-卫生保健
CiteScore
6.50
自引率
5.60%
发文量
146
审稿时长
6-12 weeks
期刊介绍: Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.
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