Applying an Empirical Taxonomy to Alert Malfunctions in a Pragmatic Trial for Hypertension Management in Chronic Kidney Disease

Abstract

Clinical decision support (CDS) systems have been widely adopted across clinical settings to promote evidence-based practice for clinicians. CDS malfunctions often affect the user experience and indirectly or directly interfere with patient care. To enhance optimal performance, it is critical to constantly monitor the performance of the tool and react promptly when malfunctions are identified.This study aimed to describe malfunctions identified in the development and implementation of a CDS alert as well as lessons learned.A pragmatic randomized controlled trial of a CDS alert for primary care patients with chronic kidney disease and uncontrolled blood pressure was conducted. The alert included prechecked default orders for medication initiation or titration, basic metabolic panel, and nephrology electronic consult. Alert monitoring involved retrospective chart review and review of alert firing reports.Eight CDS malfunctions were identified. The most common causes of malfunctions were due to conceptualization and build errors. Provider feedback and retrospective chart review were the primary methods of identifying the root cause of malfunctions.Our findings highlight the need for CDS interventions to be continuously monitored through chart review, alert firing reports, and opportunities for provider feedback. Lessons learned from CDS malfunctions can be implemented to improve provider trust in automated electronic health record-based alerts, reduce administrative burden, and prevent inappropriate alert recommendations that can negatively affect patient outcomes. This study is registered with Clinivaltrials.gov (identifier: NCT03679247).