Multi-stage emergency medicine logistics system optimization based on survival probability

doi:10.15302/J-FEM-2017020

Front. Eng

2017, Vol. 4

Issue (2) : 221-228 https://doi.org/10.15302/J-FEM-2017020

RESEARCH ARTICLE

Multi-stage emergency medicine logistics system optimization based on survival probability

Ke WANG, Yixin LIANG, Lindu ZHAO(

)

School of Economics and Management, Southeast University, Nanjing 210096, China

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Abstract

Using sudden cardiac deaths as an example and maximizing survival rate as the goal, this paper studies the influence of multi-stage medical logistics system optimization on the survival rate of sudden illness. A distribution model of survival is built, drone and ambulance arrival probability over time are discussed, a formula is proposed for maximum possible survival rate based on the probability of emergency medical logistics reaching the patient, and the results are analyzed using empirical data fitting distribution and numerical experiments performed with the model. The model is discussed as a reference point for management decision making by changing model parameters. Results show that compared to using current ambulance vehicles, ambulance drones delivering medical equipment for first aid on-site in emergencies can significantly increase survival rate, and the effect of collaborative multi-stage logistics optimization is better than that of any single stage logistics response optimization. Simulation results show that the medical rescue logistics service radius, speed, loading capacity and performance of ambulance drones impact the probability of survival, and there is an optimal service radius depending on the shape of probability distribution, which provides new information for management decisions.

Keywords emergency medicine logistics ambulance drone survival probability critical illness

Corresponding Author(s): Lindu ZHAO

Just Accepted Date: 19 June 2017 Online First Date: 06 July 2017 Issue Date: 17 July 2017

Cite this article:

Ke WANG,Yixin LIANG,Lindu ZHAO. Multi-stage emergency medicine logistics system optimization based on survival probability[J]. Front. Eng, 2017, 4(2): 221-228.

URL:

https://academic.hep.com.cn/fem/EN/10.15302/J-FEM-2017020
https://academic.hep.com.cn/fem/EN/Y2017/V4/I2/221

Fig.1 Survival curve fitting

Fig.2 Survival rate improvement by the ambulance drone

Average time, $μ 2$ /min	Lack of ambulance drone		Application of ambulance drone
Average time, $μ 2$ /min	Max(P_sa)	P_L		Max(P_sda)	P_L
15	Near 0	Near 0		0.22	0.09
10	0.16	0.02		0.45	0.31
5	0.54	0.35		0.64	0.55

Tab.1 Survive rate optimization results of different

μ 2

Assignment

Fig.3 Survive rate optimization results of different

μ 2

assignment

Fig.4 Different

σ 1

assignment

Fig.5 Different

σ 2

assignment

Fig.6 Different r assignment

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