Your browser doesn't support javascript.
Cope with the COVID-19 pandemic: Dynamic bed allocation and patient subsidization in a public healthcare system.
Ma, Xin; Zhao, Xue; Guo, Pengfei.
  • Ma X; Department of Management, Monash University, Melbourne, VIC3145, Australia.
  • Zhao X; Faculty of Business, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Guo P; Department of Management Sciences, City University of Hong Kong, Kowloon, Hong Kong.
Int J Prod Econ ; 243: 108320, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1446711
ABSTRACT
In many countries and territories, public hospitals play a major role in coping with the COVID-19 pandemic. For public hospital managers, on the one hand, they must best utilize their hospital beds to serve the COVID-19 patients immediately. On the other hand, they need to consider the need of bed resources from non-COVID-19 patients, including emergency and elective patients. In this work, we consider two control mechanisms for public hospital managers to maximize the overall utility of patients. One is the dynamic allocation of bed resources according to the evolution process of the COVID-19 pandemic. The other is the usage of a subsidy scheme to move elective patients from the public to private hospitals. We develop a dynamic programming model to study the allocation of isolation and ordinary beds and the effect of the subsidy policy in serving three types of patients, COVID-19, emergency, and elective-care. We first show that the dynamic allocation between isolation and ordinary beds can provide a better utilization of bed resources, by cutting down at least 33.5% of the total cost compared with the static policy (i.e., keeping a fixed number of isolation beds) when facing a medium pandemic alert. Our results further show that subsidizing elective patients and referring them to private hospitals is an efficient way to ease the overcrowded situation in public hospitals. Our results demonstrate that, by dynamically conducting bed allocation and subsidy scheme in different phases of the COVID-19 pandemic, patient overall utility can be greatly improved.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Int J Prod Econ Year: 2022 Document Type: Article Affiliation country: J.ijpe.2021.108320

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Int J Prod Econ Year: 2022 Document Type: Article Affiliation country: J.ijpe.2021.108320