Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

Abstract

COVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

Simulasi Sistem Pelayanan Rawat Jalan Pasien menggunakan Simulasi Kejadian Diskrit (Des)

“…2018) [6], Melman, dkk. (2021) [7], Melakukan penelitian di rumah sakit Addenbrooke di Inggris, dimana penelitian ini menggunakan model DES untuk mengevaluasi dampak keputusan alokasi sumber daya rumah sakit pada pasien COVID-19 dan non-COVID-19. Pembahasan lain mengenai simulasi yang menggunakan pemodelan DES dilakukan pada Rumah Sakit Umum Avisena Cimahi pada sistem rawat jalan [8].…”

Introduction to the special issue: Management Science in the Fight Against Covid-19

“…In order to ensure timely turn-around, we have only taken papers which we could accept with minor revisions; as a result, we have had to reject many promising manuscripts. We are pleased to have been able to accept 12 papers [1][2][3][4][5][6][7][8][9][10][11][12]. We are particularly proud to be able to highlight that "From predictions to prescriptions: A data-driven response to COVID-19" by Dimitris J Bertsimas and colleagues [1] has been awarded the Pierskalla Best Paper Award for 2020 by the INFORMS Health Applications Society.…”

On the role of data, statistics and decisions in a pandemic

“…the model jumps from the time of one event to the time of the next) and that events are discrete (mutually exclusive) . Model applications in COVID-19 include optimizations of processes with scarce resources such as bed capacities (Melman et al, 2021) or testing stations (Saidani et al, 2021) and laboratory processes (Gralla, 2020).…”