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A multi-phase DES modelling framework for patient-centred care

Author

Listed:
  • Jennifer Gillespie

    (University of Ulster)

  • Sally McClean

    (University of Ulster)

  • Lalit Garg

    (University of Malta)

  • Maria Barton

    (University of Ulster)

  • Bryan Scotney

    (University of Ulster)

  • Ken Fullerton

    (Queen’s University Belfast)

Abstract

We provide a framework for simulating the entire patient journey across different phases (such as diagnosis, treatment, rehabilitation and long-term care) and different sectors (such as GP, hospital, social and community services), with the aim of providing better understanding of such processes and facilitating evaluation of alternative clinical and care strategies. A phase-type modelling approach is used to promote better modelling and management of the specific elements of a patient pathway, using performance measures such as clinical outcomes, patient quality of life, and cost. The approach is illustrated using stroke disease. Approximately 5% of the United Kingdom National Health Service budget is spent treating stroke disease each year. There is an urgent need to assess whether existing services are cost-effective or new interventions could increase efficiency. This assessment can be made using models across primary and secondary care; in particular we evaluate the cost-effectiveness of thrombolysis (clot busting therapy), using discrete event simulation. Using our model, patient quality of life and the costs of thrombolysis are compared under different regimes. In addition, our simulation framework is used to illustrate the impact of internal discharge queues, which can develop while patients are awaiting placement. Probabilistic Sensitivity Analysis of the value parameters is also carried out.

Suggested Citation

  • Jennifer Gillespie & Sally McClean & Lalit Garg & Maria Barton & Bryan Scotney & Ken Fullerton, 2016. "A multi-phase DES modelling framework for patient-centred care," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(10), pages 1239-1249, October.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:10:d:10.1057_jors.2015.114
    DOI: 10.1057/jors.2015.114
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    References listed on IDEAS

    as
    1. Mark Fackrell, 2009. "Modelling healthcare systems with phase-type distributions," Health Care Management Science, Springer, vol. 12(1), pages 11-26, March.
    2. Jennifer Gillespie & Sally McClean & Bryan Scotney & Lalit Garg & Maria Barton & Ken Fullerton, 2011. "Costing hospital resources for stroke patients using phase-type models," Health Care Management Science, Springer, vol. 14(3), pages 279-291, September.
    3. Griffiths, J.D. & Williams, J.E. & Wood, R.M., 2013. "Modelling activities at a neurological rehabilitation unit," European Journal of Operational Research, Elsevier, vol. 226(2), pages 301-312.
    4. Arnoud Bruin & A. Rossum & M. Visser & G. Koole, 2007. "Modeling the emergency cardiac in-patient flow: an application of queuing theory," Health Care Management Science, Springer, vol. 10(2), pages 125-137, June.
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    Cited by:

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    2. Jesús Isaac Vázquez-Serrano & Rodrigo E. Peimbert-García & Leopoldo Eduardo Cárdenas-Barrón, 2021. "Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review," IJERPH, MDPI, vol. 18(22), pages 1-20, November.
    3. Ortiz-Barrios, Miguel & Arias-Fonseca, Sebastián & Ishizaka, Alessio & Barbati, Maria & Avendaño-Collante, Betty & Navarro-Jiménez, Eduardo, 2023. "Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study," Journal of Business Research, Elsevier, vol. 160(C).
    4. Carter, Michael W., 2018. "High-fidelity whole-system patient flow modeling to assess health care transformation policiesAuthor-Name: Esensoy, Ali Vahit," European Journal of Operational Research, Elsevier, vol. 266(1), pages 221-237.
    5. Miguel Ortiz-Barrios & Juan-José Alfaro-Saiz, 2020. "An integrated approach for designing in-time and economically sustainable emergency care networks: A case study in the public sector," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-28, June.

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