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. 2018 Jan/Feb;40(1):e1-e8.
doi: 10.1097/01.JHQ.0000462686.55382.

Optimizing Surgical Capacity for a Rural Hospital Through Monte Carlo Simulation

Optimizing Surgical Capacity for a Rural Hospital Through Monte Carlo Simulation

Rachel Ozer et al. J Healthc Qual. 2018 Jan/Feb.

Erratum in

  • Erratum.
    [No authors listed] [No authors listed] J Healthc Qual. 2022 Nov-Dec 01;44(6):373. doi: 10.1097/JHQ.0000000000000368. J Healthc Qual. 2022. PMID: 36305636 No abstract available.

Abstract

This article describes the application of Monte Carlo simulation to evaluate operating room (OR) utilization at a small rural hospital in the province of Ontario, Canada. Using input factors that include the duration of procedures, the number of days of operation, and the shift duration, the simulation identifies ways of improving the capacity of the hospital's OR. The analysis was used to implement changes that led to a 38% increase in the number of procedures completed. The hospital also has created capacity for further growth and is adding both new service types and additional revenue-generating contract services. Moreover, based on the success of the analytic model, hospital staff have continued collecting real-time data on OR utilization to enable additional analysis. The findings suggest that rural hospitals can indeed apply currently available data to improve process flow. Furthermore, the lack of analytic resources inside the hospital should not be a barrier because it is possible to create partnerships with educational institutions.

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