The Gap Between AI and Bedside: Participatory Workshop on the Barriers to the Integration, Translation, and Adoption of Digital Health Care and AI Startup Technology Into Clinical Practice.
The Gap Between AI and Bedside: Participatory Workshop on the Barriers to the Integration, Translation, and Adoption of Digital Health Care and AI Startup Technology Into Clinical Practice.
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人工智能和床头之间的差距：有关集成，翻译和采用数字医疗保健和AI创业技术进入临床实践的障碍的参与式研讨会。
DOI：
10.2196/32962
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发表时间：
2023-05-02
影响因子：
7.4
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中科院分区：
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人工智能(AI)和数字健康技术创新来自创业公司，用于临床实践，可以产生更好的健康结果，降低医疗成本，并改善患者的体验。然而，将这些技术整合、翻译和应用到临床实践中受到许多挑战的困扰，而且是滞后的。此外，对临床翻译障碍的解释在很大程度上是未知的，也没有从人工智能和数字医疗初创公司创始人和高管的角度进行系统研究。本文的目的是从数字健康和医疗保健AI创始人和高管的角度描述在临床实践和医疗保健系统中整合早期技术的障碍。以10名早期数字健康和医疗保健AI创始人和高管为样本，举办了利益相关者焦点小组研讨会。数字健康、医疗保健人工智能、专注于数字健康的风险资本家和医生高管出席了会议。采用归纳式主题分析方法，对成绩单进行组织、查询和分析，以求主题趋同。我们确定了将早期数字健康创新整合到临床实践和医疗保健系统中的以下四类障碍：(1)缺乏对医疗系统技术采购协议和最佳实践的了解，(2)苛刻的监管和验证要求，(3)医疗系统技术采购过程中的挑战，以及(4)早期数字健康公司与大型科技集团相比的劣势。研究参与者的建议也被综合起来，以创建一个路线图，以减少在临床实践中整合早期或新的数字健康技术的障碍。早期数字健康和医疗保健AI创业者发现了将数字健康解决方案整合到临床实践中的无数障碍。缓解举措应为早期阶段的数字健康技术公司和医疗保健提供者创造机会，在医疗保健技术采购和评估过程中互动、发展关系并使用循证研究和最佳实践。
Artificial intelligence (AI) and digital health technological innovations from startup companies used in clinical practice can yield better health outcomes, reduce health care costs, and improve patients' experience. However, the integration, translation, and adoption of these technologies into clinical practice are plagued with many challenges and are lagging. Furthermore, explanations of the impediments to clinical translation are largely unknown and have not been systematically studied from the perspective of AI and digital health care startup founders and executives. The aim of this paper is to describe the barriers to integrating early-stage technologies in clinical practice and health care systems from the perspectives of digital health and health care AI founders and executives. A stakeholder focus group workshop was conducted with a sample of 10 early-stage digital health and health care AI founders and executives. Digital health, health care AI, digital health–focused venture capitalists, and physician executives were represented. Using an inductive thematic analysis approach, transcripts were organized, queried, and analyzed for thematic convergence. We identified the following four categories of barriers in the integration of early-stage digital health innovations into clinical practice and health care systems: (1) lack of knowledge of health system technology procurement protocols and best practices, (2) demanding regulatory and validation requirements, (3) challenges within the health system technology procurement process, and (4) disadvantages of early-stage digital health companies compared to large technology conglomerates. Recommendations from the study participants were also synthesized to create a road map to mitigate the barriers to integrating early-stage or novel digital health technologies in clinical practice. Early-stage digital health and health care AI entrepreneurs identified numerous barriers to integrating digital health solutions into clinical practice. Mitigation initiatives should create opportunities for early-stage digital health technology companies and health care providers to interact, develop relationships, and use evidence-based research and best practices during health care technology procurement and evaluation processes.