AI Operating Room Scheduling

Operating-room planning includes assigning cases to rooms and time blocks, estimating procedure durations, and coordinating preoperative and postoperative capacity. Optimization software may search for a feasible schedule under constraints such as surgeon availability, specialty, equipment, staffing, and bed capacity. AI may forecast duration or cancellation risk, but the final schedule must reflect clinical priority and operational judgment.

AHRQ-funded work on perioperative scheduling evaluates efficiency across the broader process, including patient flow, rather than only utilization within the operating room. A schedule that keeps a room busy can still create delays in preoperative holding, recovery, or inpatient beds. Predictions are uncertain because procedure complexity, patient condition, and urgent cases change. Teams need a process to revise schedules when assumptions fail, and should consider the impact of changes on patients and staff.

Before deployment, compare model estimates with local case data, check whether historical patterns disadvantage less common procedures, and include recovery capacity. Monitor cancellations, overtime, waiting, staff burden, and patient flow. Keep a human coordinator able to resolve conflicts and escalate urgent needs. Do not present an optimized schedule as a guarantee that a case will start at a precise time. Patients may be affected by fasting, travel, childcare, and preparation requirements when schedules shift. Departments should communicate expected timing and update families when delays occur. Record which operational constraints forced a change, and review whether urgent, complex, or less common cases are disproportionately displaced.