Clinical Decision Support for Surgery: A Mixed Methods Study on Design and Implementation Perspectives from Urologists

Objectives To assess urologist attitudes toward clinical decision support embedded into the electronic health record and define design needs to facilitate implementation and impact. With recent advances in big data and artificial intelligence, enthusiasm for personalized, data-driven tools to improve surgical decision-making has grown, but the impact of current tools remains limited. Methods A sequential explanatory mixed methods study from 2019-2020 was performed. First, survey responses from the 2019 American Urological Association annual census evaluated attitudes toward an automatic clinical decision support tool that would display risk/benefit data. This was followed by the purposeful sampling of 25 urologists and qualitative interviews assessing perspectives on clinical decision support impact and design needs. Bivariable, multivariable, and coding-based thematic analysis were applied and integrated. Results Among a weighted sample of 12,366 practicing urologists, the majority agreed clinical decision support would help decision-making (70.9%, 95% CI 68.7–73.2%), aid patient counseling (78.5%, 95% CI 76.5–80.5%), save time (58.1%, 95% CI 55.7–60.5%), and improve patient outcomes (42.9%, 95% CI 40.5–45.4%). More years in practice was negatively associated with agreement (p<0.001). Urologists described how clinical decision support could bolster evidence-based care, personalized medicine, resource utilization, and patient experience. They also identified multiple implementation barriers and provided suggestions on form, functionality, and visual design to improve usefulness and ease of use. Conclusions Urologists have favorable attitudes toward the potential for clinical decision support in the electronic health record. Smart design will be critical to ensure effective implementation and impact.