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Modeling COVID-19 hospital admissions and occupancy in the Netherlands

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  • Bekker, René
  • uit het Broek, Michiel
  • Koole, Ger

Abstract

We describe the models we built for predicting hospital admissions and bed occupancy of COVID-19 patients in the Netherlands. These models were used to make short-term decisions about transfers of patients between regions and for long-term policy making. For forecasting admissions we developed a new technique using linear programming. To predict occupancy we fitted residual lengths of stay and used results from queueing theory. Our models increased the accuracy of and trust in the predictions and helped manage the pandemic, minimizing the impact in terms of beds and maximizing remaining capacity for other types of care.

Suggested Citation

  • Bekker, René & uit het Broek, Michiel & Koole, Ger, 2023. "Modeling COVID-19 hospital admissions and occupancy in the Netherlands," European Journal of Operational Research, Elsevier, vol. 304(1), pages 207-218.
    • Handle: RePEc:eee:ejores:v:304:y:2023:i:1:p:207-218
    DOI: 10.1016/j.ejor.2021.12.044
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    References listed on IDEAS

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    1. Steven Littig & Mark Isken, 2007. "Short term hospital occupancy prediction," Health Care Management Science, Springer, vol. 10(1), pages 47-66, February.
    2. Marcel Goic & Mirko S Bozanic-Leal & Magdalena Badal & Leonardo J Basso, 2021. "COVID-19: Short-term forecast of ICU beds in times of crisis," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-24, January.
    3. Stef Baas & Sander Dijkstra & Aleida Braaksma & Plom Rooij & Fieke J. Snijders & Lars Tiemessen & Richard J. Boucherie, 2021. "Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units," Health Care Management Science, Springer, vol. 24(2), pages 402-419, June.
    4. R. Bekker & A. Bruin, 2010. "Time-dependent analysis for refused admissions in clinical wards," Annals of Operations Research, Springer, vol. 178(1), pages 45-65, July.
    5. Pengyi Shi & Mabel C. Chou & J. G. Dai & Ding Ding & Joe Sim, 2016. "Models and Insights for Hospital Inpatient Operations: Time-Dependent ED Boarding Time," Management Science, INFORMS, vol. 62(1), pages 1-28, January.
    6. Kortbeek, N. & Braaksma, A. & Burger, C.A.J. & Bakker, P.J.M. & Boucherie, R.J., 2015. "Flexible nurse staffing based on hourly bed census predictions," International Journal of Production Economics, Elsevier, vol. 161(C), pages 167-180.
    7. Nikolopoulos, Konstantinos & Punia, Sushil & Schäfers, Andreas & Tsinopoulos, Christos & Vasilakis, Chrysovalantis, 2021. "Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions," European Journal of Operational Research, Elsevier, vol. 290(1), pages 99-115.
    8. Samuel Davis & Nasser Fard, 2020. "Theoretical bounds and approximation of the probability mass function of future hospital bed demand," Health Care Management Science, Springer, vol. 23(1), pages 20-33, March.
    9. Broyles, James R. & Cochran, Jeffery K. & Montgomery, Douglas C., 2010. "A statistical Markov chain approximation of transient hospital inpatient inventory," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1645-1657, December.
    10. David Worthington & Martin Utley & Dan Suen, 2020. "Infinite-server queueing models of demand in healthcare: A review of applications and ideas for further work," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(8), pages 1145-1160, August.
    11. Zohar Feldman & Avishai Mandelbaum & William A. Massey & Ward Whitt, 2008. "Staffing of Time-Varying Queues to Achieve Time-Stable Performance," Management Science, INFORMS, vol. 54(2), pages 324-338, February.
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    Cited by:

    1. Michael R. Johnson & Hiten Naik & Wei Siang Chan & Jesse Greiner & Matt Michaleski & Dong Liu & Bruno Silvestre & Ian P. McCarthy, 2023. "Forecasting ward-level bed requirements to aid pandemic resource planning: Lessons learned and future directions," Health Care Management Science, Springer, vol. 26(3), pages 477-500, September.
    2. Dijkstra, Sander & Baas, Stef & Braaksma, Aleida & Boucherie, Richard J., 2023. "Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy," Omega, Elsevier, vol. 116(C).

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