AN INVESTIGATION INTO PERCEIVED QUALITY OF RECOMMENDATIONS MADE BY CLINICAL DECISION SUPPORT SYSTEMS
Date of Award
Fall 10-15-2024
Degree Type
Dissertation/Thesis
Degree Name
Ph.D.
Department
Coles College of Business - Department of Information Systems and Security
Committee Chair/First Advisor
Miloslava Plachkinova
Second Advisor
Saurabh Gupta
Third Advisor
Sweta Sneha
Abstract
While clinical decision support systems (CDSS) assist in clinical decision-making, providers often show suboptimal adherence to the diagnostic recommendations these systems generate. Concurrently, healthcare organizations face increased pressure to improve care quality, safety, and regulatory compliance. This study explores the factors affecting the perceived quality of CDSS-generated recommendations to enhance physicians’ decision-making. This study considers this concept through a theoretical lens and uses cognitive continuum theory to identify factors influencing the decision-making process, considering intuition and analytical perspectives. We propose a research model that examines the impact of decision antecedents such as clinical relevance, data trustworthiness, and providers’ intuition on the perceived quality of recommendations. The model was empirically tested using a quasi-experiment approach with vignette-based scenarios. The results of this study show the positive influence of clinical relevance, data trustworthiness, and providers’ intuition on the perceived quality of recommendations. Additionally, we found statistically significant differences between knowledge-based and non-knowledge-based technology-based CDSSs when used as decision-aid interventions in the clinical decision-making process. Overall, results reveal several important research directions and recommendations for healthcare providers and HIS researchers. This research provides a greater understanding of the role of antecedents in decision output from the perspective of decision-makers intuition and analytical thinking. This study can offer valuable insights for healthcare providers seeking to enhance the meaningful use of CDSS and improve the quality of diagnostic recommendations.