Apps don't work for patients who don't use them: Towards frameworks for digital therapeutics adherence

IF 3.4 3区医学 Q1 HEALTH POLICY & SERVICES Health Policy and Technology Pub Date : 2024-06-01 DOI:10.1016/j.hlpt.2024.100848

David G. Schwartz , Sivan Spitzer , Michael Khalemsky , Arturo Heyner Cano-Bejar , Soumya Ray , Jeng-Yuan Chiou , Rizan Sakhnini , Raya Lanin , Menachem M. Meir , Ming-Che Tsai

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Abstract

Objectives

Digital therapeutics such as mobile health applications (mHealth apps) are becoming part of patients’ treatment programs. Ensuring patients actually use (adhere to) an app as prescribed, effectively measuring and interpreting usage, and detecting clinical non-compliance are fundamental to effective treatment. Clinicians are not currently prepared to deal with issues of patients’ adherence to digital therapeutics (DTx). This study proposes and analyses potential frameworks for clinician-patient dialogue about DTx adherence.

Methods

Purposive sampling is used to select three leading adherence frameworks, one at each of the micro (patient), mesa (physician), and macro (system) levels of healthcare. The ABC taxonomy of adherence stages; Osterberg and Blaschke's medication adherence framework; and the Morisky Medication Adherence Scale-8 (MMAS8). Each framework is deconstructed and analysed from the perspective of DTx adherence.

Results

Modifications to ABC can improve suitability to conceptualize DTx adherence whilst maintaining the overall framework. Osterberg and Blaschke's framework provides many metrics adaptable to app assessment alongside some that are inapplicable. Significant modification of MMAS-8 appears necessary to build relevance to DTx adherence reporting. Specific reconceptualizations of each framework element are presented.

Conclusions

A strong basis for studying and measuring DTx adherence exists in existing treatment adherence research and practice, and can help guide policy. However, important adaptations are needed to ensure the development of methods for use in clinical environments.

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对于不使用应用程序的患者来说，应用程序不起作用：建立数字治疗依从性框架

目的：移动医疗应用程序（mHealth 应用程序）等数字疗法正在成为患者治疗计划的一部分。确保患者按照处方实际使用（坚持使用）应用程序、有效测量和解释使用情况以及检测临床违规行为是有效治疗的基础。目前，临床医生还没有准备好处理患者对数字疗法（DTx）的依从性问题。本研究提出并分析了临床医生与患者就数字疗法依从性进行对话的潜在框架：方法：本研究采用有目的的抽样方法，从医疗保健的微观（患者）、中观（医生）和宏观（系统）三个层面各选择一个主要的依从性框架。这三个框架分别是：坚持用药阶段的 ABC 分类法；Osterberg 和 Blaschke 的坚持用药框架；以及 Morisky Medication Adherence Scale-8 (MMAS8)。从 DTx 依从性的角度对每个框架进行了解构和分析：结果：在保持整体框架的前提下，对 ABC 进行修改可提高 DTx 依从性概念化的适用性。Osterberg和Blaschke的框架提供了许多适用于应用评估的指标，同时也提供了一些不适用的指标。对 MMAS-8 进行重大修改似乎是必要的，这样才能建立与 DTx 报告的相关性。本文介绍了对每个框架要素的具体重新认识：现有的治疗依从性研究和实践为研究和测量 DTx 依从性奠定了坚实的基础，有助于为政策提供指导。然而，还需要进行重要的调整，以确保开发出适用于临床环境的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Health Policy and Technology Medicine-Health Policy

CiteScore

9.20

自引率

3.30%

发文量

审稿时长

88 days

期刊介绍： Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments. HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology. Topics covered by HPT will include: - Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems - Cross-national comparisons on health policy using evidence-based approaches - National studies on health policy to determine the outcomes of technology-driven initiatives - Cross-border eHealth including health tourism - The digital divide in mobility, access and affordability of healthcare - Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies - Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies - Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making - Stakeholder engagement with health technologies (clinical and patient/citizen buy-in) - Regulation and health economics