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What is the best workflow for an operating room? A simulation study of five scenarios

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Abstract

Parallel induction of anesthesia improves operating room (OR) efficiency. To support decision-making as to optimal facilities and optimal use of resources, we compared the cost-efficiency of several workflow models of parallel induction to that of the traditional model, using discrete-event simulation. For each scenario, average number of procedures performed, surgery time, daily over- and under-utilized time, and staffing costs per operation were assessed. We also studied whether scheduling short and long procedures in separate rooms would amplify the effects of the parallel processing. All parallel work-flow models demonstrated better cost-efficiency than the traditionally sequenced working pattern. Staffing costs per procedure were 7% lower in the best induction model than in the traditional model. When short procedures were scheduled separately, differences between induction models were small.

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Authors and Affiliations

  1. Department of Anesthesia and Intensive Care Medicine, Helsinki University Central Hospital, Helsinki, Finland

    Riitta A. Marjamaa

  2. Helsinki University of Technology, Espoo, Finland

    Paulus M. Torkki

  3. Department of Orthopedics and Traumatology, Helsinki University Central Hospital, Helsinki, Finland

    Eero J. Hirvensalo

  4. Department of Anesthesia and Intensive Care Medicine, Helsinki University Central Hospital, Helsinki, Finland

    Olli A. Kirvelä

  5. P.O. Box 900, 00029, HUS, Finland

    Riitta A. Marjamaa

Authors
  1. Riitta A. Marjamaa
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  2. Paulus M. Torkki
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  3. Eero J. Hirvensalo
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  4. Olli A. Kirvelä
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Corresponding author

Correspondence to Riitta A. Marjamaa.

Additional information

Supported by a Government Grant for Health Care Research, Helsinki, Finland, and the National Technology Agency of Finland, Helsinki, Finland.

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Marjamaa, R.A., Torkki, P.M., Hirvensalo, E.J. et al. What is the best workflow for an operating room? A simulation study of five scenarios. Health Care Manag Sci 12, 142–146 (2009). https://doi.org/10.1007/s10729-008-9073-8

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  • DOI: https://doi.org/10.1007/s10729-008-9073-8

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