Title: A novel decision-making scheme for hospital emergency services based on plant growth simulation algorithm

Authors: Long Chen; Qinming Liu; Chunming Ye; Jiaxiang Li

Addresses: Department of Industrial Engineering, Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China ' Department of Industrial Engineering, Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China ' Department of Industrial Engineering, Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China ' Department of Industrial Engineering, Business School, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China

Abstract: A novel decision model of hospital services decision-making based on cumulative prospect theory and plant growth simulation algorithm (PGSA) is proposed. First, this paper considers the bias of psychological behaviour characteristics of hospital emergency services decision-makers, and the selection of patient emergency solutions is designed as a nonlinear programming model. Then, the integrated value of hospital scenarios under emergencies is calculated based on the loss and gain values of patient injury severity and emergency resource utilisation, and the cumulative prospect values of each emergency scenario are calculated based on interval probability and cumulative prospect theory. PGSA is used to weigh the accumulated prospect value vector of each decision maker. Finally, the data description shows that the decision process can make the hospital emergency services scenarios optimal under emergencies, it makes emergency decision making more in line with the actual situation and thus improves scientific and effective decision making.

Keywords: hospital services; emergency resources; cumulative prospect theory; emergency services decision making; plant growth simulation algorithm; PGSA.

DOI: 10.1504/IJIMS.2024.140226

International Journal of Internet Manufacturing and Services, 2024 Vol.10 No.2/3, pp.112 - 131

Received: 17 Aug 2022
Accepted: 04 Sep 2022
Published online: 31 Jul 2024 *

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