基于遗传算法与模拟退火分级诊疗改革的实证——以合肥市为案例

An Empirical Study of Hierarchical Diagnosis and Treatment Reform Based on Genetic Algorithm and Simulated Annealing:a Case Study of Hefei City

随着人民对医疗服务需求的迅速增加,有限的医疗资源与巨大的就医需求导致"看病难"成为困扰我国的一大民生问题,为此我国正在推行分级诊疗综合改革,以合理配置医疗资源。针对分级诊疗改革的推进,我们在现有医疗机构的基础上,通过对真实地区的实证分析,采取运用模拟退火与遗传算法,基于医疗资源优化问题进行研究,通过构造综合效益函数来评估不同情况下的拟合效果,最终给出应加快分级医疗体系的建立和推广的速度以完善医疗资源配置方式的建议。

Nowadays,＂ difficult to seek adequate medical care＂ is a major problem of peopleg livelihood in China. It can be attributed to limited medical resources and medical demand that has been increasing rapidly in recent years. To tackle this conundrum, China is adopting a comprehensive reform of grading clinics to rational allocation of medical resources. To promote the reform of grading clinics, we used simulated annealing and genetic algorithm, on the basis of existing medical institutions to optimizing medical resources through empirical analysis of several regions. And by using comprehensive benefit function which is to evaluate the fitting effect under different conditions, and finally the suggestions to speed up the establishment and promotion of the grading medical system to improve the allocation of medical resources are given.