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Modelling the flow of congestive heart failure patients through a hospital system

Author

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  • B Shaw

    (Queen's University of Belfast)

  • A H Marshall

    (Queen's University of Belfast)

Abstract

The number of hospital admissions in England due to heart failure is projected to increase by over 50% during the next 25 years. This will incur greater pressures on hospital managers to allocate resources in an effective manner. A reliable indicator for measuring the quantity of resources consumed by hospital patients is their length of stay (LOS) in care. This paper proposes modelling the length of time heart failure patients spend in hospital using a special type of Markov model, where the flow of patients through hospital can be thought of as consisting of three stages of care—short-, medium- and longer-term care. If it is assumed that new admissions into the ward are replacements for discharges, such a model may be used to investigate the case-mix of patients in hospital and the expected patient turnover during some specified period of time. An example is illustrated by considering hospital admissions to a Belfast hospital in Northern Ireland, between 2000 and 2004.

Suggested Citation

  • B Shaw & A H Marshall, 2007. "Modelling the flow of congestive heart failure patients through a hospital system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 212-218, February.
    • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:2:d:10.1057_palgrave.jors.2602240
    DOI: 10.1057/palgrave.jors.2602240
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    References listed on IDEAS

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    1. E. El‐Darzi & C. Vasilakis & T. Chaussalet & P.H. Millard, 1998. "A simulation modelling approach to evaluating length of stay, occupancy, emptiness and bed blocking in a hospital geriatric department," Health Care Management Science, Springer, vol. 1(2), pages 143-149, October.
    2. C Vasilakis & A H Marshall, 2005. "Modelling nationwide hospital length of stay: opening the black box," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(7), pages 862-869, July.
    3. Etzioni, Ruth D. & Feuer, Eric J. & Sullivan, Sean D. & Lin, Danyu & Hu, Chengcheng & Ramsey, Scott D., 1999. "On the use of survival analysis techniques to estimate medical care costs," Journal of Health Economics, Elsevier, vol. 18(3), pages 365-380, June.
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    Cited by:

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    3. Harper, P.R. & Knight, V.A. & Marshall, A.H., 2012. "Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities," European Journal of Operational Research, Elsevier, vol. 219(3), pages 522-530.
    4. Casucci, Sabrina & Lin, Li & Nikolaev, Alexander, 2018. "Modeling the impact of care transition programs on patient outcomes and 30 day hospital readmissions," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 70-79.

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