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A system dynamics-based simulation study for managing clinical governance and pathways in a hospital

Author

Listed:
  • M Maliapen

    (University of Central Lancashire)

  • B C Dangerfield

    (University of Salford)

Abstract

This paper examines the development of clinical pathways (CP) in a hospital in Australia based on empirical clinical data of patient episodes. A system dynamics (SD)-based decision support system is developed and analysed for this purpose. The study highlights the scenarios that will help hospital administrators to redistribute caseloads among admitting clinicians with a focus on multiple diagnostic-related groups (DRGs) as the means to improve the patient turnaround and hospital throughput without compromising quality patient care. DRGs are the best known classification system used in a casemix funding model. Casemix is a DRG-based government funding model for hospitals with a mix of performance measures aiming to reward initiatives that increase efficiencies in hospitals. The classification system groups inpatient stays into clinically meaningful categories of similar levels of complexity that consume similar amounts of resources. Policy explorations reveal various combinations of the dominant policies that hospital management can adopt. With the use of visual interfaces, executives can manipulate the DSS to test various scenarios. Experimental evidence based on focus groups demonstrated that it can enhance group learning processes and improve decision making. The findings are supported by other recent studies of CP implementation on various DRGs. These showed substantial reduction in length of stay, costs and resource utilization.

Suggested Citation

  • M Maliapen & B C Dangerfield, 2010. "A system dynamics-based simulation study for managing clinical governance and pathways in a hospital," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 255-264, February.
    • Handle: RePEc:pal:jorsoc:v:61:y:2010:i:2:d:10.1057_jors.2008.134
    DOI: 10.1057/jors.2008.134
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    Cited by:

    1. Armenia, Stefano & Franco, Eduardo & Iandolo, Francesca & Maielli, Giuliano & Vito, Pietro, 2024. "Zooming in and out the landscape: Artificial intelligence and system dynamics in business and management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    2. Yasar A. Ozcan & Elena Tànfani & Angela Testi, 2017. "Improving the performance of surgery-based clinical pathways: a simulation-optimization approach," Health Care Management Science, Springer, vol. 20(1), pages 1-15, March.
    3. Federico Cosenz & Guido Noto, 2016. "Applying System Dynamics Modelling to Strategic Management: A Literature Review," Systems Research and Behavioral Science, Wiley Blackwell, vol. 33(6), pages 703-741, November.
    4. Tippong, Danuphon & Petrovic, Sanja & Akbari, Vahid, 2022. "A review of applications of operational research in healthcare coordination in disaster management," European Journal of Operational Research, Elsevier, vol. 301(1), pages 1-17.
    5. Willis, Graham & Cave, Siôn & Kunc, Martin, 2018. "Strategic workforce planning in healthcare: A multi-methodology approach," European Journal of Operational Research, Elsevier, vol. 267(1), pages 250-263.

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