A Study On Appointment Scheduling Of Referral Patients And Two-Stage Optimization Of Equipment Allocation In Medical Consortium

In recent years,there has been a growing demand for efficient healthcare systems due to the increasing awareness of healthcare among people.However,medical and healthcare services around the world are experiencing a shortage of resources and an uneven distribution of medical resources.One potential solution to this problem is the establishment of medical consortium,which are alliances of hospitals comprising at least one upper-level hospital and several lower-level hospitals.Despite their potential benefits,studies have found that medical consortium are not functioning optimally in terms of referrals and balancing the utilization of medical resources.Critical medical resources,such as magnetic resonance imaging(MRI),are often better equipped in tertiary hospitals that receive more patients and funding,leading to an imbalance of critical resources within the consortium.Moreover,patients often need to travel long distances and wait for extended periods after making appointments for MRI services due to the consortium’s ineffective patient referral and triage function.Against this backdrop,this thesis aims to investigate the problem of the patient referral scheduling and two-stage optimization of medical equipment allocation in medical consortium.Specifically,the thesis first examines the problem of optimizing patient referrals in a medical consortium based on an enhanced hybrid genetic algorithm(EHGA)to obtain a referral scheme that improves the quality of patient services by scheduling patients with appointments in a day.The thesis defines patient service quality as the average waiting time of patients,which is the average of patients’ queuing time and traffic time,and uses it as an evaluation index of the patient referral allocation scheme.In addition,the thesis proposes a two-stage optimal allocation of medical equipment based on patient demand and proposes an equipment allocation optimization method based on patient referral rate.The thesis considers two scenarios of stock adjustment,i.e.,reallocation of existing equipment,and incremental allocation,i.e.,allocation of new equipment,of medical equipment within the medical consortium.To minimize the average patient waiting time,the thesis proposes the resource reallocation algorithm based on referral difference(RARD)and the resource reallocation algorithm based on patient appointments(RAPA)for solving the stock adjustment problem.The thesis also proposes the RARD-I and RAPA-I algorithms for the scenario for incremental allocation.The experimental results show that the EHGA algorithm proposed in this thesis outperforms the Gurobi solver in the small-scale case and significantly outperforms the five classical heuristic algorithms in all large-scale combinations of different hospital-patient sizes.Both resource allocation algorithms can significantly reduce the average patient waiting time under the original patient appointment scenario in both the stock adjustment and incremental allocation scenarios.The experimental analysis in the stock adjustment scenario proves that the algorithms greatly optimize the proportion of patients waiting for a long time and can achieve patient demand-oriented resource reallocation,demonstrating the effectiveness of the algorithms and the need for resource allocation optimization.Overall,the optimized resource allocation in both scenarios for patient referral scheduling is also improved compared to the pre-optimization scenario.However,the optimization is lower than the original patient appointment scenario,further proving the effectiveness of the referral system.In summary,the proposed algorithm and optimization method can be considered as an effective solution for optimizing the allocation of patient referrals and medical equipment in medical consortia,and can provide theoretical reference for the construction of medical association.