健康指数构建的统计分析流程及实现

  目的  基于综合评价理论探索并归纳健康指数构建的统计分析流程，开发相关R包用于软件实现，为健康指数研究开发一套快捷高效的评价工具，实现一键生成高度集成的综合指数及评价结果，以期为监管部门提供科学可靠的评价信息与决策依据。  方法  使用R 4.1.3软件开发EvaModels包，结合健康指数构建的统计分析流程对EvaModels包内各项函数进行整体介绍与参数解释，分析比较各类方法的适用场景，并以公立医院持续发展指数构建为例进行演示分析。  结果  健康指数构建包括确定指数研究主题、构建评价指标体系、多指标综合评价及评价结果可视化四大流程。所开发的EvaModels包共内置九个函数，通过多种方法实现指标筛选、数据标准化、指标赋权和综合评价等功能，可满足多种评价问题的分析需求，基本覆盖健康指数构建的统计分析流程。  结论  EvaModels包通过一组函数将健康指数构建中涉及统计分析的工作流程自动化、简单化，过程与代码易于解读与调用，提高了健康指数构建的便捷性和可操作性。

Statistical analysis process of health index construction and its implementation

  Objective  Based on the comprehensive evaluation theory, this paper explores and summarizes the statistical analysis process of health index construction, and develops relevant R packages for software implementation. In this way, a set of fast and efficient evaluation tools for health index research can be further developed, and a highly integrated comprehensive index and evaluation results can be generated with one click. We hope to provide scientific and reliable evaluation information and a decision-making basis for regulatory authorities.  Methods  R 4.1.3 software was used to develop the EvaModels package. Combined with the statistical analysis process of health index construction, this paper introduced and explained the functions of the EvaModels package as a whole. Moreover, we analyzed and compared the applicable scenarios of various methods, and takes the construction of a sustainable development index of public hospitals as an example for demonstration and analysis.  Results  Health index construction included four processes. Namely, determining the research theme of the index, constructing an evaluation indicator system, multi-indicator comprehensive evaluation, and visualization of evaluation results. The developed EvaModels package has nine built-in functions to realize the functions of indicator screening, data standardization, index weighting and comprehensive evaluation through a variety of methods. Also, it can meet the analysis needs of a variety of evaluation problems and cover the statistical analysis process of health index construction.  Conclusion  The EvaModels package automates and simplifies the workflow involved in statistical analysis in health index construction through a set of functions. With procedures and codes that are easy to interpret and call, it can improve the convenience and operability of health index construction.