Abstract
IntroductionArtificial intelligence (AI), the simulation of human intelligence processes by machines, is being increasingly leveraged to facilitate clinical decision-making. AI-based clinical decision support (CDS) tools can improve the quality of care and appropriate use of healthcare resources, and decrease healthcare provider burnout. Understanding the determinants of implementing AI-based CDS tools in healthcare delivery is vital to reap the benefits of these tools. The objective of this scoping review is to map and synthesise determinants (barriers and facilitators) to implementing AI-based CDS tools in healthcare.Methods and analysisThis scoping review will follow the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic reviews and Meta-Analysis extension for Scoping Reviews checklist. The search terms will be tailored to each database, which includes MEDLINE, Embase, CINAHL, APA PsycINFO and the Cochrane Library. Grey literature and references of included studies will also be searched. The search will include studies published from database inception until 10 May 2022. We will not limit searches by study design or language. Studies that either report determinants or describe the implementation of AI-based CDS tools in clinical practice or/and healthcare settings will be included. The identified determinants (barriers and facilitators) will be described by synthesising the themes using the Theoretical Domains Framework. The outcome variables measured will be mapped and the measures of effectiveness will be summarised using descriptive statistics.Ethics and disseminationEthics approval is not required because all data for this study have been previously published. The findings of this review will be published in a peer-reviewed journal and presented at academic conferences. Importantly, the findings of this scoping review will be widely presented to decision-makers, health system administrators, healthcare providers, and patients and family/caregivers as part of an implementation study of an AI-based CDS for the treatment of coronary artery disease.
Funder
Alberta Innovates
Canadian Institutes for Health Research
Reference53 articles.
1. Wikipedia . Artificial intelligence. Available: https://en.wikipedia.org/wiki/Artificial_intelligence [Accessed 02 Dec 2022].
2. High-performance medicine: the convergence of human and artificial intelligence
3. Holzinger A , Langs G , Denk H , et al . Causability and explainability of artificial intelligence in medicine. Wiley Interdiscip Rev Data Min Knowl Discov 2019;9:e1312. doi:10.1002/widm.1312
4. Artificial intelligence in healthcare;Yu;Nat Biomed Eng,2018
5. Clinical chemistry laboratory automation in the 21st century-amat Victoria curam (victory loves careful preparation);Armbruster;Clin Biochem Rev,2014
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