Wang Quansheng, Han Guoqing, Huang Lansong
Law School, Shandong University, Weihai, China.
Digit Health. 2025 May 25;11:20552076251346238. doi: 10.1177/20552076251346238. eCollection 2025 Jan-Dec.
To understand the internal and external characteristics of the big data policy of healthcare in China. This paper discusses the focus and shortcomings of policy objectives and related policies. This study provides a reference for optimizing China's big data-related healthcare policies.
In this study, NVivo 12 was used for qualitative and quantitative analyses of the combination of the software policy. The policy documents included in the study were coded, and the statistical description method was used to analyze the relevant policy tools.
Among the basic types of policy instruments, supply-oriented, environmental, and demand-oriented policy instruments accounted for 58.9%, 24.2%, and 16.9%, respectively. The use of specific tools for different types of policy is also very uneven.
The policy is dominated by the government; its use is insufficient; some are neglected, and the system is quite different. It is suggested to improve the precision of policy targeting, optimize the internal structure of policies, actively cultivate market players, and enhance the use of information technology.
了解我国医疗大数据政策的内外特征。本文探讨政策目标及相关政策的重点与不足。本研究为优化我国医疗大数据相关政策提供参考。
本研究采用NVivo 12软件对政策组合进行定性和定量分析。对纳入研究的政策文件进行编码,并采用统计描述方法分析相关政策工具。
在政策工具的基本类型中,供给型、环境型和需求型政策工具分别占58.9%、24.2%和16.9%。不同类型政策具体工具的使用也很不均衡。
政策以政府主导为主;使用不足;部分被忽视,体系差异较大。建议提高政策靶向精准度,优化政策内部结构,积极培育市场主体,加强信息技术运用。