Accepted for/Published in: JMIR Research Protocols
Date Submitted: Aug 25, 2021
Open Peer Review Period: Aug 25, 2021 - Oct 20, 2021
Date Accepted: Feb 9, 2022
(closed for review but you can still tweet)
A framework synthesis of stakeholder perspectives on clinical decision support tools to inform clinical AI implementation: a qualitative evidence synthesis protocol
ABSTRACT
Background:
Quantitative systematic reviews have identified clinical artificial intelligence (AI) enabled tools with adequate performance for real-world implementation. To our knowledge, no published report or protocol synthesizes the full breadth of stakeholder perspectives. The absence of such a rigorous foundation perpetuates the ‘AI chasm’ which continues to delay patient benefit.
Objective:
To synthesize stakeholder perspectives of computerized clinical decision support tools (CCDST) in any healthcare setting. Synthesized findings will inform future research and the implementation of AI into healthcare services.
Methods:
The search strategy will use MEDLINE (Ovid), Scopus, CINAHL (EBSCO), ACM Digital Library and Science Citation Index (Web of Science). Following deduplication, title, abstract and full text screening will be performed by two independent reviewers with a third topic expert arbitrating. The quality of included studies will be appraised to support interpretation. Best-fit framework synthesis will be performed, with line-by-line coding completed by two independent reviewers. Where appropriate, these findings will be assigned to one of 22 a-priori themes defined by the Non-Adoption, Abandonment, Scale-Up, Spread and Sustainability (NASSS) framework. New domains will be inductively generated for outlying findings. The placement of findings within themes will be reviewed iteratively by a study advisory group including patient and lay representatives.
Results:
Study registration was obtained from PROSPERO (ID 248025) in May 2021. Final searches were executed in April and screening is ongoing at the time of writing. Full text data analysis is due to be completed in October 2021. We anticipate that the study will be submitted for open-access publication in late 2021 .
Conclusions:
This paper describes the protocol for a qualitative evidence synthesis aiming to define barriers and facilitators to the implementation of CCDSTs from all relevant stakeholders. The results of this study are intended to expedite the delivery of patient benefit from AI enabled clinical tools. Clinical Trial: PROSPERO ID 248025
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Copyright
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