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A queuing-based decision support methodology to estimate hospital inpatient bed demand

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  • J K Cochran

    (Arizona State University)

  • K Roche

    (Arizona State University)

Abstract

Hospital inpatient bed capacity might be better described as evolved than planned. At least two challenges lead to this behaviour: different views of patient demand implied by different data sets in a hospital and limited use of scientific methods for capacity estimation. In this paper, we statistically examine four distinct hospital inpatient data sets for internal consistency and potential usefulness for estimating true patient bed demand. We conclude that posterior financial data, billing data, rather than the census data commonly relied upon, yields true hospital bed demand. Subsequently, a capacity planning tool, based upon queuing theory and financial data only, is developed. The delivery mechanism is an Excel spreadsheet. One adjusts input parameters including patient volume and mix and instantaneously monitors the effect on bed needs across multiple levels of care. A case study from a major hospital in Phoenix, Arizona, USA is used throughout to demonstrate the methodologies.

Suggested Citation

  • J K Cochran & K Roche, 2008. "A queuing-based decision support methodology to estimate hospital inpatient bed demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(11), pages 1471-1482, November.
  • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:11:d:10.1057_palgrave.jors.2602499
    DOI: 10.1057/palgrave.jors.2602499
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    References listed on IDEAS

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    1. Lapierre, Sophie D. & Goldsman, David & Cochran, Roger & DuBow, Janice, 1999. "Bed allocation techniques based on census data," Socio-Economic Planning Sciences, Elsevier, vol. 33(1), pages 25-38, March.
    2. Kim, Seung-Chul & Horowitz, Ira & Young, Karl K. & Buckley, Thomas A., 1999. "Analysis of capacity management of the intensive care unit in a hospital," European Journal of Operational Research, Elsevier, vol. 115(1), pages 36-46, May.
    3. Ridge, J. C. & Jones, S. K. & Nielsen, M. S. & Shahani, A. K., 1998. "Capacity planning for intensive care units," European Journal of Operational Research, Elsevier, vol. 105(2), pages 346-355, March.
    4. P R Harper & A K Shahani, 2002. "Modelling for the planning and management of bed capacities in hospitals," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(1), pages 11-18, January.
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    Cited by:

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    6. Jie Bai & Andreas Fügener & Jan Schoenfelder & Jens O. Brunner, 2018. "Operations research in intensive care unit management: a literature review," Health Care Management Science, Springer, vol. 21(1), pages 1-24, March.
    7. Fermín Mallor & Cristina Azcárate & Julio Barado, 2016. "Control problems and management policies in health systems: application to intensive care units," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 62-89, June.
    8. Fanwen Meng & Jin Qi & Meilin Zhang & James Ang & Singfat Chu & Melvyn Sim, 2015. "A Robust Optimization Model for Managing Elective Admission in a Public Hospital," Operations Research, INFORMS, vol. 63(6), pages 1452-1467, December.

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