A Review of Statistical Model Applications in Health Economics Research

Shi Tao; Wang Qingyun; Zhang Zhishuo; Li Qian; Cao Yangdong; Deng Wenbei; Wei Gang

Abstract：Objective:To review the application status of statistical models in health economics from 2010 to 2024,revealing model classification,evolution trends,integration characteristics,and development directions,thereby providing references for health economics study and methodological innovation.Methods:Based on bibliometric methods,363 journal articles were screened.A six-dimensional classification framework of"efficiency evaluation,influencing factors,economic relationships,comprehensive evaluation,policy assessment,artificial intelligence"was constructed.Model application characteristics were quantified and integration patterns were summarized through frequency statistics,case deconstruction,and trend analysis.Results:Mainstream models included data envelopment analysis,structural equation modeling,and panel data models,the application of the coupling coordination degree model in health resource allocation research grew rapidly,while spatial econometric and machine learning models developed significantly.Model integration enhanced explanatory power and predictive accuracy through complementary advantages,and big data technology is shifting the research paradigm from"post-hoc analysis"towards"real-time intervention".Conclusion:Health economics research is transitioning from a single-model approach to a"multi-model integration+big data-driven"paradigm.Future efforts should focus on constructing standardized integration frameworks,overcoming bottlenecks in data governance and algorithm fairness,and promoting the translation of methodological innovations into health system performance.