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Analytical Approaches to Operating Room Management

Projects at Lucile Packard Children’s Hospital Stanford

Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS,volume 210)


In recent decades, healthcare has become increasingly expensive, creating pressure on healthcare providers to cut costs while maintaining or improving quality. Operations research can play an important role in supporting such efforts. A key challenge faced by hospital planners is scheduling and management of operating rooms, as operating rooms typically provide highly specialized care, require significant resources, and contribute significantly to a hospital’s bottom line. We describe recent work on hospital operating room management at Lucile Packard Children’s Hospital Stanford. We describe preliminary outcomes of three projects aimed at improving the efficiency of the hospital’s operating rooms: machine learning to improve surgical case length estimation; queuing analysis to improve operational efficiency; and integer programming to schedule cases to reduce surgical delays.


  • Healthcare
  • Operations management
  • Optimization
  • Machine learning
  • Queueing

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Correspondence to Margaret L. Brandeau .

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Scheinker, D., Brandeau, M.L. (2017). Analytical Approaches to Operating Room Management. In: Cappanera, P., Li, J., Matta, A., Sahin, E., Vandaele, N., Visintin, F. (eds) Health Care Systems Engineering. ICHCSE 2017. Springer Proceedings in Mathematics & Statistics, vol 210. Springer, Cham.

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