| As an important part of the national public health system,health supervision plays an important role in implementing the Healthy China strategy and safeguarding people’s health rights.With the construction and development of health supervision informatization work in Yunnan,the investment scale,structure of information infrastructure and resource construction are becoming more and more complete.How to use big data to assist health supervision decision-making,drive health supervision from extensive to refined,precise and predictive,which will become the research focus of health supervision informatization development in Yunnan.Based on the existing research results,combined with the actual situation of health supervision informatization in Yunnan,this research focuses on the theory of data governance,and constructs an informatization evaluation model from the three elements of infrastructure construction,informatization application effect and data quality.Take the health supervision agencies of each region as the evaluation samples,the research used the traditional DEA model to carry out the evaluation of Yunnan’s health supervision informatization in 2021.First of all,The evaluation group includes DEA effective,DEA approximately effective,and DEA invalid.The development level of health supervision informatization in various regions is not balanced.Second,some regions have not made full use of the current informatization resources,or the resource allocation is not reasonable.Third,there are three input-output types of regional informatization,include“high input and high output”,“low input and low output”,“low input and high output”.The last,there are four types of information technology and scale efficiency,include“high-tech high-scale”,“low-tech low-scale”,“high-tech low-tech” and “low-tech high-scale”.Combining the dimensions of evaluation indicators and evaluation conclusions,the following suggestions for informatization development are put forward: first,make full use of current resources to improve the efficiency of informatization;second,improve the application level of informatization to meet the requirements of data governance;third,optimize data quality to laying a solid foundation for data governance;the fourth is to mine the value of data to promoting the development of data governance. |
