Reimagining the IR Workflow for a Better Work-Life Balance

Abstract

Several workflow changes were implemented in a large academic interventional radiology practice, including separation of inpatient and outpatient services, early start times, and using an adaptive learning system to predict case length tailored to individual physicians. Metrics including procedural volume, on-time start, accuracy at predicting case length, and room shutdown time were assessed before and after the intervention. Considerable improvements were seen in accuracy of first case start times, predicting block times, and last case encounter ending times. It is proposed that with improved role clarity, interventional radiologists can regain control over their schedules, utilize work hours more efficiently, and improve work-life balance.