Abstract

In China, 10% of medical resource are general hospital which treat 86% patients. This will lead the health resources in these hospitals become insufficient and exhaust, even if the resources in other hospitals idle. Previous studies have indicated that the scattering resource systems will result in significant imbalances if it lacks stable and effective match. To deal with Two-Sided Matching (TSM) problem in hierarchical medical system, a matching decision-making approach based on multiple scenarios was proposed. The algorithm was designed to adapt four kinds of scenarios, it analyzed multi-context matching satisfaction degree of these cooperation situations in different forms of environment respectively and specifically.By comparing the examples, the multi - scenario dynamic matching method is superior to the random matching algorithm and the “F-Y” algorithm (improved G - S algorithm), and it is effective to obtain the stable and feasible solution. This paper showed a multi-scenarios dynamic matching algorithm for hierarchical treatment system by modifying comprehensive satisfaction integration function and differential adjustment function. This paper concentrated on the stability and total satisfaction goals of system matching. This method serves as a decision-making reference for the bilateral matching encountered in the problem of “hierarchical treatment system” around the world.

Highlights

  • Medical administration departments around the world are facing increasing pressure to improve the quantity and quality of healthcare services

  • To solve the problem of medical resource matching in Hierarchical Treatment Systems, the result of the random matching algorithm is the worst: total satisfaction is often the lowest (14.1181, 13.9122, 20.2765, and 21.6092), and there exists μ- hinder matching pair leading to unstable matching

  • In complex scenarios (c) and (d), linear weighting is used to transform the multi-objective problem into a single objective scheme in "F-Y" matching algorithm

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Summary

Introduction

Medical administration departments around the world are facing increasing pressure to improve the quantity and quality of healthcare services. It aims to deepen the reform of the medical and health system, effectively allocate medical resources and promote the equalization of basic medical and health services [1]. The results show that the Chinese government has done most of the measures it can do, and the number of per capita medical resources is growing rapidly, the data close to moderately developed countries such as Italy, Spain, Japan and South Korea (Department of Health Statistics, 2016). Increasing numbers of patients visiting hospitals every year (total attendance has risen at 7.8 billion in 2016 according to Chinese Health and Family Planning Development Statistical Bulletin (2017)), and evidences of some hospitals taking special actions to avoid overcrowding while other hospital's medical resources are often idle, suggests that optimal allocation of medical resources is still a high priority. The purpose is to determine the optimal match between Superior hospitals, Subordinate hospitals, and patients so as to meet the largest resource utilization and highest total system satisfaction in different scenes

Related Works
Definitions
Unilateral Satisfaction Matrix
Influence Weight
Solving Methods
Decision making Steps
Case Study
Results algorithm
Algorithms Results
Discussions
Conclusions
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