TY - JOUR
T1 - Evolutionary game theory on over-treatment behavior under drug-proportion regulation
AU - Wu, Xiaodan
AU - Liu, Yifan
AU - Li, Juan
AU - Chu, Chao Hsien
N1 - Funding Information:
National Social Science Foundation of China (17BGL087).
Publisher Copyright:
© 2019, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Drug-proportion regulation is on implementing following the price regulation and the elimination of markups on pharmaceuticals to curb the over-treatment, which is an important issue for Chinese healthcare reform. Based on that, we propose an evolutionary game model of doctor-patient behavior under drug-proportion regulation. Theoretically, it founds that there exists behavioral evolutionary law and stable strategies between physicians and patients according to replicator dynamics equation. Then treatment strategies are analyzed by considering normal treatment costs, the ratio of over-treatment to normal treatment costs, physician performance coefficient, and the severity of illness. The results show that drug-proportion regulation does not always inhibit over-treatment, which depends on a transition point. Physicians prefer to choose overtreatment while the drug-proportion is lower than the transition point. It is worth noting that the severity of illness affects over-treatment under the drug-proportion regulation. Physicians are prefer to over-treatment when patients are less ill. These conclusions are beneficial for drugproportion setting, light-illness monitoring, hierarchical diagnosis, and information disclosure mechanism. Finally, related healthcare policy suggestions are provided.
AB - Drug-proportion regulation is on implementing following the price regulation and the elimination of markups on pharmaceuticals to curb the over-treatment, which is an important issue for Chinese healthcare reform. Based on that, we propose an evolutionary game model of doctor-patient behavior under drug-proportion regulation. Theoretically, it founds that there exists behavioral evolutionary law and stable strategies between physicians and patients according to replicator dynamics equation. Then treatment strategies are analyzed by considering normal treatment costs, the ratio of over-treatment to normal treatment costs, physician performance coefficient, and the severity of illness. The results show that drug-proportion regulation does not always inhibit over-treatment, which depends on a transition point. Physicians prefer to choose overtreatment while the drug-proportion is lower than the transition point. It is worth noting that the severity of illness affects over-treatment under the drug-proportion regulation. Physicians are prefer to over-treatment when patients are less ill. These conclusions are beneficial for drugproportion setting, light-illness monitoring, hierarchical diagnosis, and information disclosure mechanism. Finally, related healthcare policy suggestions are provided.
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U2 - 10.12011/1000-6788-2018-1930-13
DO - 10.12011/1000-6788-2018-1930-13
M3 - Article
AN - SCOPUS:85079329559
SN - 1000-6788
VL - 39
SP - 3163
EP - 3175
JO - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
JF - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
IS - 12
ER -