Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Aug 16, 2021
Date Accepted: Oct 25, 2022
The Gap between AI to Bedside: Examining the barriers to the integration of early-stage digital health and AI technology into clinical practice
ABSTRACT
Background:
Despite enormous enthusiasm, machine learning/AI, and digital healthcare technologies from early-stage healthcare technology companies there is not much evidence of their economic, quality, and clinical impact. It can take up to 12-24 months to integrate machine learning/AI and digital healthcare technologies into clinical practice. In addition to the slow sales and iteration cycles, the integration of digital health technologies from early-stage ventures is plagued with many challenges.
Objective:
The study aims to describe the unique barriers digital medicine and healthcare AI entrepreneurs face in the rapid integration of their early-stage digital health and AI solutions into clinical healthcare systems and operations.
Methods:
A semi-structured stakeholders’ focus group workshop was conducted with a sample of 10 early-stage digital medicine and healthcare technology entrepreneurs. Populations of interest included: Digital Medicine entrepreneurs, healthcare AI entrepreneurs, digital medicine focused venture capitalists, and physician entrepreneurs.
Results:
We identified four categories of barriers in the rapid integration of early-stage digital medicine innovations into clinical healthcare systems and operations: 1) Lack of knowledge on 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 between early-stage digital health companies and large technology conglomerates
Conclusions:
Early-stage digital medicine and healthcare technology entrepreneurs identified numerous barriers to integrating their digital health solutions into clinical healthcare systems. Mitigation initiatives should create opportunities for early digital health technology companies, & healthcare providers and systems to interact and develop relationships and make use of evidence-based research and best practices during early-stage startup healthcare procurement and evaluation processes.
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Copyright
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