Unlocking the full potential of digital endpoints for decision making: a novel modular evidence concept enabling re-use and advancing collaboration.

IF 1.8 4区 医学 Q3 HEALTH CARE SCIENCES & SERVICES Expert Review of Pharmacoeconomics & Outcomes Research Pub Date : 2024-07-01 Epub Date: 2024-05-15 DOI:10.1080/14737167.2024.2334347
Lada Leyens, John Batchelor, Erwin De Beuckelaer, Kai Langel, Bert Hartog
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Abstract

Introduction: Over the last decade increasing examples indicate opportunities to measure patient functioning and its relevance for clinical and regulatory decision making via endpoints collected through digital health technologies. More recently, we have seen such measures support primary study endpoints and enable smaller trials. The field is advancing fast: validation requirements have been proposed in the literature and regulators are releasing new guidances to review these endpoints. Pharmaceutical companies are embracing collaborations to develop them and working with academia and patient organizations in their development. However, the road to validation and regulatory acceptance is lengthy. The full value of digital endpoints cannot be unlocked until better collaboration and modular evidence frameworks are developed enabling re-use of evidence and repurposing of digital endpoints.

Areas covered: This paper proposes a solution by presenting a novel modular evidence framework -the Digital Evidence Ecosystem and Protocols (DEEP)- enabling repurposing of measurement solutions, re-use of evidence, application of standards and also facilitates collaboration with health technology assessment bodies.

Expert opinion: The integration of digital endpoints in healthcare, essential for personalized and remote care, requires harmonization and transparency. The proposed novel stack model offers a modular approach, fostering collaboration and expediting the adoption in patient care.

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释放数字终点在决策制定中的全部潜力:一种新颖的模块化证据概念,可实现重复使用并促进合作。
简介:在过去的十年中,越来越多的实例表明,通过数字医疗技术收集的终点,有机会测量患者的功能及其与临床监管决策的相关性:在过去十年中,越来越多的实例表明,通过数字健康技术收集的终点,有机会测量患者的功能及其与临床和监管决策的相关性。最近,我们看到此类测量方法支持主要研究终点,并使小型试验成为可能。这一领域正在快速发展:文献中提出了验证要求,监管机构也发布了新的指南来审查这些终点。制药公司正积极合作开发这些终点,并在开发过程中与学术界和患者组织开展合作。然而,验证和监管接受的道路是漫长的。只有加强合作并开发模块化证据框架,实现证据的重复使用和数字终点的重新利用,才能释放数字终点的全部价值:本文提出了一种解决方案,介绍了一种新颖的模块化证据框架--数字证据生态系统与协议(DEEP)--可实现测量解决方案的再利用、证据的再利用、标准的应用,同时还可促进与卫生技术评估机构的合作:医疗保健中数字终端的整合对于个性化和远程医疗保健至关重要,需要统一和透明。拟议的新型堆栈模型提供了一种模块化方法,可促进合作并加快在患者护理中的采用。
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
Expert Review of Pharmacoeconomics & Outcomes Research
Expert Review of Pharmacoeconomics & Outcomes Research HEALTH CARE SCIENCES & SERVICES-PHARMACOLOGY & PHARMACY
CiteScore
4.00
自引率
4.30%
发文量
68
审稿时长
6-12 weeks
期刊介绍: Expert Review of Pharmacoeconomics & Outcomes Research (ISSN 1473-7167) provides expert reviews on cost-benefit and pharmacoeconomic issues relating to the clinical use of drugs and therapeutic approaches. Coverage includes pharmacoeconomics and quality-of-life research, therapeutic outcomes, evidence-based medicine and cost-benefit research. All articles are subject to rigorous peer-review. The journal adopts the unique Expert Review article format, offering a complete overview of current thinking in a key technology area, research or clinical practice, augmented by the following sections: Expert Opinion – a personal view of the data presented in the article, a discussion on the developments that are likely to be important in the future, and the avenues of research likely to become exciting as further studies yield more detailed results Article Highlights – an executive summary of the author’s most critical points.
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