An engineering approach to reducing physician fatigue and enhancing learning

Abstract

Medical intern schedules frequently involve 24-hour shifts, leading to systemic fatigue and potential medical errors. This study applies Lean Six Sigma and operations research to optimize scheduling by treating fatigue as a predictable process variable. A multi-objective model was developed to minimize cumulative fatigue and workload variability for 18 interns. Fatigue was quantified via a weighted composite score across 24-hour, 16-hour, and 12-hour shift scenarios, maintaining ACGME compliance and hospital coverage. Analysis of the 24-hour model showed a near-perfect correlation between hours worked and fatigue (R2 = 0.9988), with a mean normalized fatigue of 1.44 (44% above baseline). Transitioning to a simulated 16-hour model reduced normalized fatigue to 1.20 and reduced workload variability. Fatigue was shown to be a predictable output of schedule design. Transitioning to 16-hour shifts mitigates systemic "defects," optimizing patient safety and resident well-being through data-driven process stability.