Assessing Medication CDS Usability: Pilot Results from 10 Outpatient Clinics - Co, Zoe; Bates, David W.; Cole, Jessica M.; Ratwani, Raj; Classen, David C. (Applied Clinical Informatics, 2025)
This study aimed to develop a human factors assessment for medication-related clinical decision support (CDS) based on a previously validated tool that assessed the integration of human factors principles in CDS, the instrument for evaluating human factors principles in medication-related decision support alerts (I-MeDeSA), and pilot it with 10 outpatient clinics across the United States.The human factors assessment was developed based on past validations of I-MeDeSA. Examples included changing the wording of questions and reformatting answer choices to check-box options, allowing for multiple answer choices. We also added a section about how clinicians resolved alerts. Clinics received a percentage score based on how well their CDS adhered to human factors principles. To take the assessment, testing teams at each clinic triggered a high-severity drug–drug interaction (DDI) alert, and then took the human factors assessment. This assessment was piloted in 10 outpatient clinics, each of which used a different commercial electronic health record (EHR) system.The final assessment included five sections and twelve questions related to aspects like the timing, visual aspect, severity, content, and actions within the DDI alert. The mean overall percentage score was 62%. The sections regarding the timing and visual aspects of the alert were ones where clinics' EHRs performed the best. However, in the “actions” section, 40% of the clinics could bypass high severity alerts without any safeguards in place.We found substantial variability in the integration of human factors principles in the design and delivery of DDI alerts among the outpatient clinics, and some lacked important medication safeguards. This assessment can be used by outpatient clinics for safety improvement initiatives.
Keywords: medication safety; quality of care; psychological burnout; ambulatory care; electronic health record; human factors; usability; artificial intelligence