Objective: To model the financial impact of policies governing the scheduling of overlapping surgeries, and to identify optimal solutions that maximize operating efficiency that satisfy the fiduciary duty to patients.
Background: Hospitals depend on procedural revenue to maintain financial health as the recent pandemic has revealed. Proposed policies governing the scheduling of overlapping surgeries may dramatically impact hospital revenue. To date, the potential financial impact has not been modeled.
Methods: A linear forecasting model based on a logic matrix decision tree enabled an analysis of surgeon productivity annualized over a fiscal year. The model applies procedural and operational variables to policy constraints limiting surgical scheduling. Model outputs included case and financial metrics modeled over 1000-surgeon-year simulations. case metrics included annual case volume, case mix, operating room (OR) utilization, surgeon utilization, idle time, and staff overtime hours. Financial outputs included annual revenue, expenses, and contribution margin.
Results: The model was validated against surgical data. case and financial metrics decreased as a function of increasingly restrictive scheduling scenarios, with the greatest contribution margin loses ($1,650,000 per surgeon-year) realized with the introduction of policies mandating that a second patient could not enter the OR until the critical portion of the first surgery was completed. We identify an optimal scheduling scenario that maximizes surgeon efficiency, minimizes OR idle time and revenue loses, and satisfies ethical obligations to patients.
Conclusions: Hospitals may expect significant financial loses with the introduction of policies restricting OR scheduling. We identify an optimal solution that maximizes efficiency while satisfying ethical duty to patients. This forecast is immediately relevant to any hospital system that depends upon procedural revenue.
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