The encyclopedia · R&D & Science · Operational decision · 2013–2016
UT Medical Center scheduled NICU shifts to match doctors' preferences
A mixed-integer program rebuilt neonatal ICU shift schedules around individual physician preferences, lifting preference scores 6.3–8.5%.
University of Tennessee Medical Center
The solution
Hospital units must cover 24-7 shifts, and fairness is usually achieved by dividing shifts evenly by type among physicians — but even splits ignore who prefers nights, weekends or longer shifts.
The team modeled the problem as a binary mixed-integer program that keeps each physician's equality schedule as a baseline and maximizes preference gains subject to coverage and fairness constraints. A hybrid version lets some physicians keep equality schedules while others opt into preference-based ones.
Implemented with a neonatal intensive care group, the schedules improved preference for the opt-in physicians by 6.3–8.5% while maintaining full coverage.
Why it worked
- Fairness stays anchored as a constraint, so no one loses coverage or equity.
- Maximizing gains over each person's own equality schedule respects individual baselines.
- The hybrid model handles groups where not everyone wants to deviate.
- Optimization finds preference gains no manual scheduling process could.
What can be applied
Fairness can be a constraint, not the objective; anchor on the status-quo fair allocation and let optimization find Pareto-better alternatives no manual process would produce.
Aftermath
The approach was published in Interfaces (2016) and shows how optimization can improve both fairness and individual preference in physician scheduling.
Sources
- Physician Scheduling for Continuity: An Application in Pediatric Intensive Care
- Physician Scheduling for Continuity: An Application in Pediatric Intensive Care
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