TY - JOUR
T1 - Artificial-Intelligence-Based Clinical Decision Support Systems in Primary Care
T2 - A Scoping Review of Current Clinical Implementations
AU - Gomez-Cabello, Cesar A.
AU - Borna, Sahar
AU - Pressman, Sophia
AU - Haider, Syed Ali
AU - Haider, Clifton R.
AU - Forte, Antonio J.
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/3
Y1 - 2024/3
N2 - Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based Clinical Decision Support Systems (AI-CDSSs) in Primary Healthcare (PHC). Following the PRISMA-ScR guidelines, we systematically searched five databases, PubMed, Scopus, CINAHL, IEEE, and Google Scholar, and manually searched related articles. Only CDSSs powered by AI targeted to physicians and tested in real clinical PHC settings were included. From a total of 421 articles, 6 met our criteria. We found AI-CDSSs from the US, Netherlands, Spain, and China whose primary tasks included diagnosis support, management and treatment recommendations, and complication prediction. Secondary objectives included lessening physician work burden and reducing healthcare costs. While promising, the outcomes were hindered by physicians’ perceptions and cultural settings. This study underscores the potential of AI-CDSSs in improving clinical management, patient satisfaction, and safety while reducing physician workload. However, further work is needed to explore the broad spectrum of applications that the new AI-CDSSs have in several PHC real clinical settings and measure their clinical outcomes.
AB - Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based Clinical Decision Support Systems (AI-CDSSs) in Primary Healthcare (PHC). Following the PRISMA-ScR guidelines, we systematically searched five databases, PubMed, Scopus, CINAHL, IEEE, and Google Scholar, and manually searched related articles. Only CDSSs powered by AI targeted to physicians and tested in real clinical PHC settings were included. From a total of 421 articles, 6 met our criteria. We found AI-CDSSs from the US, Netherlands, Spain, and China whose primary tasks included diagnosis support, management and treatment recommendations, and complication prediction. Secondary objectives included lessening physician work burden and reducing healthcare costs. While promising, the outcomes were hindered by physicians’ perceptions and cultural settings. This study underscores the potential of AI-CDSSs in improving clinical management, patient satisfaction, and safety while reducing physician workload. However, further work is needed to explore the broad spectrum of applications that the new AI-CDSSs have in several PHC real clinical settings and measure their clinical outcomes.
KW - artificial intelligence
KW - clinical decision support systems
KW - machine learning
KW - primary healthcare
UR - http://www.scopus.com/inward/record.url?scp=85188808060&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85188808060&partnerID=8YFLogxK
U2 - 10.3390/ejihpe14030045
DO - 10.3390/ejihpe14030045
M3 - Review article
AN - SCOPUS:85188808060
SN - 2174-8144
VL - 14
SP - 685
EP - 698
JO - European Journal of Investigation in Health, Psychology and Education
JF - European Journal of Investigation in Health, Psychology and Education
IS - 3
ER -