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Leveraging Healthcare Facility Network Simulations for Capacity Planning and Facility Location in a Pandemic

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Document pages: 49 pages

Abstract: The COVID-19 pandemic has placed severe demands on healthcare facilities across the world, and in several countries, makeshift COVID-19 centres have been operationalised to handle patient overflow. In developing countries such as India, the public healthcare system (PHS) is organised as a hierarchical network with patient flows from lower-tier primary health centres (PHC) to mid-tier community health centres (CHC) and further downstream to district hospitals (DH). A network-based modelling and simulation (M&S) approach would (a) quantify the extent to which existing PHC, CHC and DH facilities can effectively cope with the forecasted COVID-19 patient load, whilst continuing to offer non-COVID-19 related care functions such as childbirth care, surgeries and outpatient clinics; (b) inform decisions on capacity at makeshift COVID-19 Care Centres (CCC) to handle patient overflows from the PHS; (c) enable identifying the optimal location of such makeshift facilities. We apply the network-based M&S approach to an empirical study of a local PHS comprising ten PHCs, three CHCs, one DH and one makeshift CCC, and report operational outcomes for existing PHS capacity and estimate the required capacity for the CCC under a specific pandemic response strategy. We identify the optimal location of the CCC through the combined application of the network simulation with a version of the stochastic ruler algorithm customized for this problem. Our work contributes to the literature on network modelling using simulation and optimisation approaches. Although this paper concerns COVID-19 operations management and CCC capacity planning, the approach could be used more generally in a pandemic situation.

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