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Stress-testing the resilience of the Austrian healthcare system using agent-based simulation

Author

Listed:
  • Michaela Kaleta

    (Complexity Science Hub Vienna
    Medical University of Vienna, Section for Science of Complex Systems, CeMSIIS)

  • Jana Lasser

    (Complexity Science Hub Vienna
    Graz University of Technology, Institute for Interactive Systems and Data Science)

  • Elma Dervic

    (Complexity Science Hub Vienna
    Medical University of Vienna, Section for Science of Complex Systems, CeMSIIS)

  • Liuhuaying Yang

    (Complexity Science Hub Vienna)

  • Johannes Sorger

    (Complexity Science Hub Vienna)

  • D. Ruggiero Lo Sardo

    (Complexity Science Hub Vienna
    Medical University of Vienna, Section for Science of Complex Systems, CeMSIIS)

  • Stefan Thurner

    (Complexity Science Hub Vienna
    Medical University of Vienna, Section for Science of Complex Systems, CeMSIIS)

  • Alexandra Kautzky-Willer

    (Medical University of Vienna
    Gender Institute)

  • Peter Klimek

    (Complexity Science Hub Vienna
    Medical University of Vienna, Section for Science of Complex Systems, CeMSIIS)

Abstract

Patients do not access physicians at random but rather via naturally emerging networks of patient flows between them. As mass quarantines, absences due to sickness, or other shocks thin out these networks, the system might be pushed to a tipping point where it loses its ability to deliver care. Here, we propose a data-driven framework to quantify regional resilience to such shocks via an agent-based model. For each region and medical specialty we construct patient-sharing networks and stress-test these by removing physicians. This allows us to measure regional resilience indicators describing how many physicians can be removed before patients will not be treated anymore. Our model could therefore enable health authorities to rapidly identify bottlenecks in access to care. Here, we show that regions and medical specialties differ substantially in their resilience and that these systemic differences can be related to indicators for individual physicians by quantifying their risk and benefit to the system.

Suggested Citation

  • Michaela Kaleta & Jana Lasser & Elma Dervic & Liuhuaying Yang & Johannes Sorger & D. Ruggiero Lo Sardo & Stefan Thurner & Alexandra Kautzky-Willer & Peter Klimek, 2022. "Stress-testing the resilience of the Austrian healthcare system using agent-based simulation," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31766-7
    DOI: 10.1038/s41467-022-31766-7
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    References listed on IDEAS

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    1. Lee, B.Y. & McGlone, S.M. & Song, Y. & Avery, T.R. & Eubank, S. & Chang, C.C. & Bailey, R.R. & Wagener, D.K. & Burke, D.S. & Platt, R. & Huang, S.S., 2011. "Social network analysis of patient sharing among hospitals in Orange County, California," American Journal of Public Health, American Public Health Association, vol. 101(4), pages 707-713.
    2. Mr. Tobias Adrian & Mr. James Morsink & Miss Liliana B Schumacher, 2020. "Stress Testing at the IMF," IMF Departmental Papers / Policy Papers 2020/001, International Monetary Fund.
    3. Homer, J.B. & Hirsch, G.B., 2006. "System dynamics modeling for public health: Background and opportunities," American Journal of Public Health, American Public Health Association, vol. 96(3), pages 452-458.
    4. Woods, David D., 2015. "Four concepts for resilience and the implications for the future of resilience engineering," Reliability Engineering and System Safety, Elsevier, vol. 141(C), pages 5-9.
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    Cited by:

    1. Schuster, Hannah & Polleres, Axel & Wachs, Johannes, 2024. "Stress-testing road networks and access to medical care," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).

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