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The self-regulating nature of occupancy in ICUs: stochastic homoeostasis

Author

Listed:
  • Josephine Varney

    (Flinders University
    University of Adelaide)

  • Nigel Bean

    (University of Adelaide
    University of Adelaide)

  • Mark Mackay

    (Flinders University)

Abstract

As pressure on the health system grows, intensive care units (ICUs) are increasingly operating close to their capacity. This has led a number of authors to describe a link between admission and discharge behaviours, labelled variously as: ‘bumping’, ‘demand-driven discharge’, ‘premature discharge’ etc. These labels all describe the situation that arises when a patient is discharged to make room for the more acute arriving patient. This link between the admission and discharge behaviours, and other potential occupancy-management behaviours, can create a correlation between the arrival process and LOS distribution. In this paper, we demonstrate the considerable problems that this correlation structure can cause capacity models built on queueing theory, including discrete event simulation (DES) models; and provide a simple and robust solution to this modelling problem. This paper provides an indication of the scope of this problem, by showing that this correlation structure is present in most of the 37 ICUs in Australia. An indication of the size of the problem is provided using one ICU in Australia. By incorrectly assuming that the arrival process and LOS distribution are independent (i.e. that the correlation structure does not exist) for an occupancy DES model, we show that the crucial turn-away rates are markedly inaccurate, whilst the mean occupancy remains unaffected. For the scenarios tested, the turn-away rates were over-estimated by up to 46 days per year. Finally, we present simple and robust methods to: test for this correlation, and account for this correlation structure when simulating the occupancy of an ICU.

Suggested Citation

  • Josephine Varney & Nigel Bean & Mark Mackay, 2019. "The self-regulating nature of occupancy in ICUs: stochastic homoeostasis," Health Care Management Science, Springer, vol. 22(4), pages 615-634, December.
    • Handle: RePEc:kap:hcarem:v:22:y:2019:i:4:d:10.1007_s10729-018-9448-4
    DOI: 10.1007/s10729-018-9448-4
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    References listed on IDEAS

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    1. Carri W. Chan & Vivek F. Farias & Nicholas Bambos & Gabriel J. Escobar, 2012. "Optimizing Intensive Care Unit Discharge Decisions with Patient Readmissions," Operations Research, INFORMS, vol. 60(6), pages 1323-1341, December.
    2. Wharton, Frank, 1996. "On the risk of premature transfer from coronary care units," Omega, Elsevier, vol. 24(4), pages 413-423, August.
    3. 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.
    4. Fermín Mallor & Cristina Azcárate, 2014. "Combining optimization with simulation to obtain credible models for intensive care units," Annals of Operations Research, Springer, vol. 221(1), pages 255-271, October.
    5. 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.
    6. Barer, Morris L. & Evans, Robert G. & Hertzman, Clyde & Lomas, Jonathan, 1987. "Aging and health care utilization: New evidence on old fallacies," Social Science & Medicine, Elsevier, vol. 24(10), pages 851-862, January.
    7. Nico Dijk & Nikky Kortbeek, 2008. "On Dimensioning Intensive Care Units," Operations Research Proceedings, in: Jörg Kalcsics & Stefan Nickel (ed.), Operations Research Proceedings 2007, pages 291-296, Springer.
    8. 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.
    9. Md Asaduzzaman & Thierry Chaussalet & Nicola Robertson, 2010. "A loss network model with overflow for capacity planning of a neonatal unit," Annals of Operations Research, Springer, vol. 178(1), pages 67-76, July.
    10. 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.
    11. J D Griffiths & N Price-Lloyd & M Smithies & J E Williams, 2005. "Modelling the requirement for supplementary nurses in an intensive care unit," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(2), pages 126-133, February.
    12. Eren Demir & Reda Lebcir & Shola Adeyemi, 2014. "Modelling length of stay and patient flows: methodological case studies from the UK neonatal care services," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(4), pages 532-545, April.
    13. Litvak, Nelly & van Rijsbergen, Marleen & Boucherie, Richard J. & van Houdenhoven, Mark, 2008. "Managing the overflow of intensive care patients," European Journal of Operational Research, Elsevier, vol. 185(3), pages 998-1010, March.
    14. Gregory Dobson & Hsiao-Hui Lee & Edieal Pinker, 2010. "A Model of ICU Bumping," Operations Research, INFORMS, vol. 58(6), pages 1564-1576, December.
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