基于PMC指数模型的浙江"惠民保"政策量化评价研究OA

Objective Taking Zhejiang Province as an example,this study aimed to quantitatively ana-lyze the policy texts of People-benefit Insurance and proposed targeted policy optimization paths,so as to promote the high-quality development of"People-benefit Insurance"and improve the multi-level medical insurance system in China.Methods Policy text mining was performed based on NVIVO12.0.Fully considering the policy syner-gy in various cities,we integrated innovatively policy texts within the same city,took them as cases,and used the PMC index model for policy evaluation.Results Among the 10 policy text cases included in the analysis,3 cases were rated as excellent and 6 cases good.The average PMC index was 7.54,indicating that the policy design was scientifically reasonable and could meet the development needs of"People-benefit Insurance".However,there were also problems such as the transient policy effectiveness,lack of long-term planning,and insufficient coverage of beneficiary groups.Conclusions It is vital for people-benefit insurance to optimize the top-level design and construct a long-term mechanism based on the analysis results,to strengthen risk prevention for its sustainable de-velopment,to improve the incentive and restraint system and enhance the implementation of policies,and to ex-pand the influence of policies and increase public participation.