Understanding Economic Decision-Making in Digital Therapeutics Development: Qualitative Approach.

IF 6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Yoann Sapanel, L Martin Cloutier, Alec Morton, Sapphire Lin, Gyula Seres, Dean Ho
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引用次数: 0

Abstract

Background: Digital therapeutics (DTx) represent a transformative shift in health care delivery, offering software-driven, evidence-based therapeutic interventions. Despite their potential, adoption remains low across health care systems, partly due to insufficient economic evidence. Significant knowledge gaps persist regarding stakeholders' approaches to economic decisions in DTx development, with prior studies also indicating limited consideration of economic factors in early DTx development stages, particularly from researchers.

Objective: This study investigates how researchers approach decision-making regarding factors that influence the economic impact of DTx during technological development and clinical validation phases, examining the underlying mechanisms and contextual conditions that shape these processes.

Methods: Using a critical realism philosophical stance, 17 semistructured interviews were conducted with researchers involved in DTx development, including research engineers (n=5), health systems and social science researchers (n=6), clinician-researchers (n=4), and practitioner-researchers (n=2). The research approach combined deductive and inductive coding, followed by abductive and retroductive inference processes to identify generative mechanisms underlying observed decision-making patterns. Qualitative system dynamics modeling was applied to visualize causal loop relationships through triangulated data sources.

Results: Three interrelated generative mechanisms were identified that shape researchers' decision-making regarding economic considerations: (1) the professional norms, operating through reinforcing loops that systematically prioritize clinical validation while marginalizing economic considerations; (2) the researcher experience, revealing how professional training and limited economic literacy create cognitive biases that obscure economic factors; and (3) the DTx adoption uncertainties, demonstrating how implementation concerns influence development decisions through both reinforcing and balancing feedback loop dynamics. These mechanisms explain why, despite growing recognition of the importance of economic evidence, economic considerations remain peripheral in researchers' decision frameworks.

Conclusions: This study reveals complex interactions between institutional structures, intrapersonal factors, and implementation uncertainties that systematically deprioritize economic considerations in DTx development. The identified mechanisms provide valuable intervention points for strengthening the development process toward a more comprehensive assessment of clinical, technical, and economic value throughout the DTx lifecycle to ultimately enhance their adoption in health care systems.

理解数字治疗发展中的经济决策:定性方法。
背景:数字治疗(DTx)代表了医疗保健服务的变革,提供了软件驱动的、基于证据的治疗干预措施。尽管它们具有潜力,但整个卫生保健系统的采用率仍然很低,部分原因是经济证据不足。关于DTx开发中利益相关者的经济决策方法,存在重大的知识差距,先前的研究也表明,在早期DTx开发阶段,特别是研究人员对经济因素的考虑有限。目的:本研究探讨了在技术开发和临床验证阶段,研究人员如何对影响DTx经济影响的因素进行决策,并研究了影响这些过程的潜在机制和背景条件。方法:采用批判现实主义哲学立场,对参与DTx开发的研究人员进行了17次半结构化访谈,包括研究工程师(n=5)、卫生系统和社会科学研究人员(n=6)、临床研究人员(n=4)和执业研究人员(n=2)。研究方法结合演绎和归纳编码,其次是溯因和溯因推理过程,以确定观察到的决策模式的生成机制。定性系统动力学建模应用于通过三角数据源可视化因果循环关系。结果:研究发现了三个相互关联的生成机制,影响了研究人员在经济考虑方面的决策:(1)专业规范,通过强化循环系统地优先考虑临床验证,同时边缘化经济考虑;(2)研究人员的经验,揭示了专业培训和有限的经济素养如何造成模糊经济因素的认知偏差;(3) DTx采用的不确定性,展示了实施问题如何通过加强和平衡反馈循环动态来影响开发决策。这些机制解释了为什么尽管人们越来越认识到经济证据的重要性,但经济因素在研究人员的决策框架中仍然处于次要地位。结论:本研究揭示了制度结构、个人因素和实施不确定性之间复杂的相互作用,这些因素系统性地降低了DTx发展中经济考虑的优先级。已确定的机制为加强开发过程提供了有价值的干预点,以便在整个DTx生命周期中对临床、技术和经济价值进行更全面的评估,最终提高其在卫生保健系统中的采用。
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
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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