基于PMC指数模型的我国健康医疗大数据发展的政策环境研究

顾一纯; 何达; 黄佳妤; 孙辉; 王昊德

引用本文：顾一纯, 何达, 黄佳妤, 孙辉, 王昊德.基于PMC指数模型的我国健康医疗大数据发展的政策环境研究[J].中国卫生政策研究,2022,15(4):45-51

基于PMC指数模型的我国健康医疗大数据发展的政策环境研究

投稿时间：2021-10-11 修订日期：2022-03-29 PDF全文浏览 HTML全文浏览

顾一纯¹, 何达¹, 黄佳妤², 孙辉¹, 王昊德¹

1. 上海市卫生和健康发展研究中心上海 201199;
2. 上海健康医学院上海 201318

摘要:目的：分析目前我国健康医疗大数据发展的政策环境，并为我国健康行业决策制定和完善提供理论依据，为我国健康医疗大数据行业高质量发展提供方向指引。方法：以我国国家层面出台的与健康医疗大数据相关的政策为研究对象，采用文本挖掘的方法遴选出政策文本中的高频词，结合专家访谈结果构建PMC指数模型，对我国健康医疗大数据的相关政策进行量化评价。结果：PMC指数模型结果表明，我国9项健康医疗大数据政策PMC指数的平均值为4.72，其中2项政策表现良好，7项政策表现及格；国家层面健康医疗大数据政策整体质量良好，但仍有较大提升空间。结论：我国健康医疗大数据管理政策基本完善，政策在性质与功能上较为明确，本文着重从政策内容、激励约束和生命周期三方面进行具体分析并提出改进建议。

关键词:健康医疗大数据 PMC指数模型量化研究政策评价

Research on the policy environment of China's healthcare big data development based on PMC index model

GU Yi-chun¹, HE Da¹, HUANG Jia-yu², SUN Hui¹, WANG Hao-de¹

1. Shanghai Health Development Research Center, Shanghai 201199, China;
2. Department of Medical Instrumentation, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China

Abstract:Objective:To analyze the current policy environment of China's healthcare big data development, to provide theoretical basis for decision making and improvement of China's health industry, and to provide directional guidance for the high-quality development of China's healthcare big data industry. Methods:The policies related to big data in healthcare issued at the national level in China were taken as the research objects, and the high-frequency words in the policy texts were selected by the text mining method, and the PMC index model was constructed by combining the results of expert interviews to quantitatively evaluate the policies related to big data in healthcare in China. Results:The results of the PMC index model showed that the average value of PMC index of nine healthcare big data policies in China was 4.72, among which two policies performed well and seven policies performed passably; the overall quality of healthcare big data policies at the national level was good, but there was still much room for improvement. Conclusions:China's healthcare big data management policies are basically perfect, and the policies are clearer in nature and function. This paper focuses on specific analysis and improvement suggestions from three aspects:policy content, incentive constraints and life cycle.

Key words:Healthcare big data PMC index model Quantitative research Policy evaluation

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