Multi-criteria decision-making for collaborative COVID-19 surge management and inter-hospital patients' transfer optimisation

The rapid spread of the COVID-19 virus and the massive influx of patients exceeded the intensive care units capacity limit. Hospitals have engaged community partners to request resources or transfer patients to facilities with available resources. This setting fosters the need for rationing decisions to allocate scarce resources consistently, rather than basing decisions on clinicians' intuition in the heat of the moment. In this paper, we identify the inter-hospital COVID-19 patients' transfer criteria, and we apply a multi-criteria decision-making methodology to classify and rank these criteria in order to determine the transfer priority scores between hospitals. We then develop an optimisation model for patient systematic referral from saturated to recipient hospitals with contingency capacity expansion and a ventilator donation scheme. To deal with the uncertainty related to the number of ill patients requesting beds in hospitals, a two-stage stochastic model is presented and solved using the sample average approximation. A case with real data related to the COVID-19 French context is presented, which allows us to assess the resilience of the hospital network under the proposed solutions. The results show how local and regional coalitions can avert the saturation of the hospital system and reduce the number of rejected patients.