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Capacity planning for a network of community health services

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  • Mohammadi Bidhandi, Hadi
  • Patrick, Jonathan
  • Noghani, Pedram
  • Varshoei, Peyman

Abstract

Community care services are becoming increasingly important to health delivery as patients live longer but with chronic disease. In this research, we propose a queuing network approach to capacity planning for a network of services. We take advantage of existing heuristics that calculate the probability of blocking for a given capacity plan and utilize the output of these heuristics to run a simulated annealing approach to optimize capacity allocation across the network subject to a performance guarantee related to the sum of the blocking probabilities. We apply this model to a local health region with a network of six services – acute care, long term care, assisted living, home care, rehabilitation and chronic care. We test the results of the optimization model through a simulation that incorporates more realism than is possible in the queuing model and that also allows us to determine the transient behaviour of the system as it transitions from current capacity levels to the those proposed by the optimization model.

Suggested Citation

  • Mohammadi Bidhandi, Hadi & Patrick, Jonathan & Noghani, Pedram & Varshoei, Peyman, 2019. "Capacity planning for a network of community health services," European Journal of Operational Research, Elsevier, vol. 275(1), pages 266-279.
    • Handle: RePEc:eee:ejores:v:275:y:2019:i:1:p:266-279
    DOI: 10.1016/j.ejor.2018.11.008
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    References listed on IDEAS

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    Cited by:

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    2. Seokjun Youn & H. Neil Geismar & Michael Pinedo, 2022. "Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4407-4423, December.
    3. Wu, Xiaodan & Li, Juan & Chu, Chao-Hsien, 2019. "Modeling multi-stage healthcare systems with service interactions under blocking for bed allocation," European Journal of Operational Research, Elsevier, vol. 278(3), pages 927-941.
    4. Li Li & Jinjuan Yang & Shaoguo Zhai & Dan Li, 2022. "Determinants of Differences in Health Service Utilization between Older Rural-to-Urban Migrant Workers and Older Rural Residents: Evidence from a Decomposition Approach," IJERPH, MDPI, vol. 19(10), pages 1-16, May.
    5. Mahsa Pahlevani & Majid Taghavi & Peter Vanberkel, 2024. "A systematic literature review of predicting patient discharges using statistical methods and machine learning," Health Care Management Science, Springer, vol. 27(3), pages 458-478, September.

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