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Study on the optimization of emergency medical staff regional dispatch considering the ratio of doctors and nurses
3rd International Symposium on Artificial Intelligence for Medical Sciences, ISAIMS 2022 ; : 369-375, 2022.
Article in English | Scopus | ID: covidwho-2194145
ABSTRACT
Public health emergencies will pose an enormous challenge to healthcare service systems. As COVID-19 rage across the globe, we realize that COVID-19 exposes the problem of inadequate research on the dispatch of emergency medical personnel in response to a major epidemic outbreak. In the face of major public health emergencies, failure in timely satisfaction of healthcare demands by local healthcare professionals necessitates human resource support from other regions. To address this issue, further research is needed to gain better insights into interregional emergency human resource allocation. This paper aims to offer attention to patients' medical needs and suppose that there are support hubs outside the outbreak region offering an external supply of medical personnel. The hospitals in these support hubs are categorized based on variables such as capacity, medical capability, and the number of dispatched personnel per day. An interregional emergency allocation model was established to consider the proper doctor-patient ratio and nurse-patient ratio in emergency response using methods such as mathematical programming. And relevant management suggestions were then offered via analysis. Research in this paper provides allocation models and proposals that healthcare professionals can refer to when making resource allocation decisions in emergency response. © 2022 ACM.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd International Symposium on Artificial Intelligence for Medical Sciences, ISAIMS 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd International Symposium on Artificial Intelligence for Medical Sciences, ISAIMS 2022 Year: 2022 Document Type: Article