Abstract
Artificial Intelligence (AI) techniques assist clinicians and physicians in making more effective and well-informed decisions for their patients. Clinical decision support systems (CDSS) offer extreme promise for integrating AI into the healthcare industry. To learn and extend the work done by researchers in the past, this research presents a meta-analysis of literature reviews focusing on acceptance, adoption, avoidance, and resistance of CDSS. The investigation spanned various academic databases from January 2016 to April 2021. A conceptual model guided the classification of literature into the dimensions of People, Process, and Technology. The analysis revealed the range and evolution of research relating to CDSS and clarifies trends for practitioners and Information Systems (IS) researchers. The study concludes with recommendations to further advance CDSS acceptance, adoption, avoidance, and resistance by focusing on the People, Process, and Technology dimensions. We found that 1) technology has been identified as the main component in the studies more often than people and process and 2) adoption and acceptance have been constructed as the focus of the theoretical frameworks much more than avoidance and resistance.
Recommended Citation
Noteboom, Cherie; Behrens, Andrew; Crandall, Kalee; and Zeng, David, "PEOPLE, PROCESS, AND TECHNOLOGY IN CLINICAL DECISION SUPPORT SYSTEMS: A META-ANALYSIS" (2022). SAIS 2022 Proceedings. 4.
https://aisel.aisnet.org/sais2022/4