Collaborative Planning Of Pre-hospital And In-hospital Emergency Resources Enabled By 5G Ambulances Networking

In recent years,the new 5G emergency mode characterized by "admission on board" is of great value and significance for building an end-to-end emergency rescue system and shortening the emergency demand response time and admission handover time.It is integrated with traditional ambulances through 5G communication technology,and is equipped with new mobile medical examination and monitoring equipment,which can realize the rapid diagnosis of patients’ conditions and real-time transmission of information.With the goal of minimizing patients’ waiting delay and life loss,the academic community has achieved fruitful results on the design of pre-hospital emergency network and the planning and allocation of in-hospital medical resources.However,the existing research mostly for two isolated system of pre-hospital emergency and in-hospital emergency treatment,rarely consider the planning of ambulance and hospital specialist medical ability of collaborative planning,which may restrict the emergency demand and emergency response ability matching efficiency,thus cause longer demand response and handover time,and emergency patient treatment delay.In view of this,considering the increasingly popular deployment of 5G ambulances and the good effects of the new emergency mode,this paper will carry out an in-depth study on the collaborative planning of pre-and-in hospital emergency resources under the condition of 5G connected ambulance.In reality,there are two serious problems in the process of pre-hospital emergency dispatch.On the one hand,in recent years,the phenomenon of empty ambulance running is serious,which seriously threatens the life safety of acute patients.At present,the proposed "5G emergency hierarchical dispatching system"method of verbally judging the critical condition when the call is reached mainly depends on the subjective judgment of the command personnel,and cannot fundamentally solve the problem of waste of ambulance resources.On the other hand,the latest emergency regulations clearly point out that patients have the right to choose the hospital by themselves.In the actual rescue process,the patient can follow the instructions of the medical staff to arrive at the designated hospital,or request to go to the hospital with their own preferences.Therefore,how to jointly optimize pre-and-in hospital emergency resources while reducing empty vehicle waste and satisfying patient choice behavior is a challenging problem.To this end,based on the queuing theory and the multinomial logit user-choice theory,this paper constructs a network traffic model based on the pre-hospital closed queuing network flow and the in-hospital medical capability single-server queuing model,and then build a two-stage stochastic programing model for joint planning of pre-and-in hospital resources under the demand occurrence uncertainty.In the event of unknown demand onset and empty ambulamce scenario,the planned pre-hospital resources can minimize the sum of the total pre-hospital waiting delay time and the queuing delay time and the in-hospital queuing failure loss.Specifically,this paper first describes the pre-hospital closed queuing network flow and the in-hospital queuing view,and constructs three two-stage stochastic planning models for the uncertainty of demand occurrence.The first model is the basic end-to-end stochastic system-optimal model,which aims to minimize the resource deployment costs and related system operation costs and realize the here-and-now decisions of resource planning and wait-and-see decisions of ambulance initial dispatch and secondary dispatch and patients admission allocation under steady state;The second model is to consider the hospital choice behavior of patients related to travel time,queuing delay and the probability of balking and construct an end-to-end user equilibrium choice bi-level planning model incorporated with the multinomial logit choice model.The third is to consider the pre-hospital and in-hospital resource collaborative planning model in the case of inter-hospital sharing of medical resources in 5G medical alliance.Since the multi-stage nonlinear model constructed in this paper belongs to NP-Hard problem,which is very difficult to solve it directly,and most of the existing studies use heuristic algorithm or approximate method to obtain approximate solutions,so the following three algorithms are proposed in this paper.Firstly we use piecewise linear approximation algorithm to solve these models approximatively and analyze the approximation error.Then designs the classical benders decomposition algorithm using the linear relaxation subproblem,and then further designs a non-convex nested generalized benders decomposition algorithmuse using the enhanced linear relaxation subproblem method according to the model characteristics to solve the model efficiently and accurately,which can effectively improve the decision-making efficiency of the joint planning of pre-and-in hospital resources.Finally,this paper makes a case analysis of the actual demand in Jinan city,applies the above proposed models and algorithms and verifies their effectiveness.It can be found that the nested generalized benders decomposition algorithm has obvious advantages in the solution speed and the solution quality compared with the piecewise linear approximation and the relaxed benders decomposition algorithms through the algorithm performance analysis,and also the validity and reliability of the three models are illustrated through model effect analysis and sensitivity analysis.Therefore,the proposed models and algorithms in this paper are of great significance for the collaborative planning of pre-and-in hospital resources in the context of 5G ambulance networking enabling.