职业与健康 ›› 2025, Vol. 41 ›› Issue (22): 3153-3158.

• 卫生管理与研究 • 上一篇    下一篇

基于PMC指数模型的省级职业病防治“十四五”规划政策文本量化对比分析

高美丽, 兰天, 王晓舜, 王陆阳, 毕明丽, 丁晓文   

  1. 北京市化工职业病防治院职业健康研究所 100189
  • 收稿日期:2025-04-05 修回日期:2025-04-24 发布日期:2025-12-15
  • 通信作者: 丁晓文,研究员,E-mail:dxwen1124@163.com
  • 作者简介:高美丽,女,副主任医师,主要从事职业健康教育与职业健康促进工作。
  • 基金资助:
    首都卫生发展科研专项项目(首发2024-2-3103)

Quantitative comparative analysis of provincial occupational disease prevention and control "14th Five-year plan" policy based on the PMC index model

GAO Meili, LAN Tian, WANG Xiaoshun, WANG Luyang, BI Mingli, DING Xiaowen   

  1. Institute of Occupational Health,Beijing Chemical Industry Occupational Disease Prevention and Control Institute,Beijing 100189,China
  • Received:2025-04-05 Revised:2025-04-24 Published:2025-12-15
  • Contact: DING Xiaowen,Researcher,E-mail:dxwen1124@163.com

摘要: 目的 以《国家职业病防治规划(2021—2025年)》为基础,分析目前我国各省级行政区制定的职业病防治“十四五”规划政策文本,寻找差异和先进做法,为今后职业病防治政策的优化和完善提供依据。方法 收集我国及各省级行政区制定的职业病防治“十四五”规划政策文本,通过文献查阅及专家访谈设计评价指标,采用ROSTCM 6.0软件对政策样本进行文本挖掘,并构建政策工具理论及政策一致性(policy modeling consistency,PMC)指数模型,在省级比较视域下对样本政策进行量化对比研究。结果 共纳入省级层面职业病防治“十四五”规划政策文本28项,其PMC指数均值为9.43,其中政策内容覆盖完美1项,优秀24项,良好3项。一级指标中,政策评价的PMC指数均值为0.60(可接受水平),其余均>0.90(优秀水平)。各省级行政区基本遵循国家规划的工作方针和思路,涉及危害防治、中小微企业、监管执法、科技创新等内容,在自主创新、背景描述、指标量化等7个二级指标中做法各有不同。结论 我国省级层面职业病防治“十四五”规划政策文本整体质量优秀,具有科学性、合理性。政策内容上,背景描述、指标量化、明确职责等方面可进一步制定,使其更具有指导性。各地可结合实际借鉴其他省级行政区好的经验做法寻找差距和突破点,为优化自身职业健康政策和制定职业病防治“十五五”规划奠定基础。

关键词: 职业健康, 职业病防治, 理论及政策一致性指数模型, 政策文本, 量化分析

Abstract: Objective Based on the “National Occupational Disease Prevention and Control Plan(2021-2025)”,the study analyzes the "14th Five-Year Plan" policy for occupational disease prevention and control formulated by various provincial administrative regions in China,identifies differences and advanced practices,and provides a basis for the optimization and improvement of future occupational disease prevention and control policies. Methods Policy documents for occupational disease prevention and control in the "14th Five-Year Plan" formulated by China and various provincial administrative regions were collected. Evaluation indicators were designed through literature review and expert interviews. Text mining was conducted on policy samples using ROSTCM 6.0 software,and a policy tool theory and policy modeling consistency(PMC) index model were constructed. Quantitative comparative research was conducted on sample policies from a provincial comparative perspective. Results A total of 28 policy documents for occupational disease prevention and control at the provincial level in the "14th Five-Year Plan" were included. The average PMC index was 9.43,with 1 document achieving perfect coverage,24 being excellent,and 3 being good. Among the first-level indicators,the PMC index for policy evaluation was 0.60(acceptable level),while the others were all above 0.90(excellent level). All provincial administrative regions basically followed the work guidelines and ideas of the national plan,covering aspects such as hazard prevention and control,small,medium,and micro enterprises,regulatory enforcement,and technological innovation. There were differences in seven second-level indicators,including independent innovation,background description,and indicator quantification. Conclusion The overall quality of policy for occupational disease prevention and control at the provincial level in the "14th Five-Year Plan" is excellent,demonstrating scientific and rationality. In terms of policy content,aspects such as background description,indicator quantification,and clear responsibilities can be further refined to enhance their guidance. Additionally,each region can draw on the good experiences and practices of other provincial administrative regions,identify gaps and breakthrough points,and lay the foundation for optimizing their own occupational health policies and formulating the "15th Five-Year Plan" for occupational disease prevention and control.

Key words: Occupational health, Occupational disease prevention and control, Theoretical and policy consistency index model, Policy documents, Quantitative analysis

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