ArticleFrontiers in public health2024
Based on knowledge capital value for disease cost accounting of diagnosis related groups.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- The effect of diagnosis-related group policy on treatment cost and treatment efficiency of inpatients with coronary heart disease in Xinjiang: an interrupted time series analysis.Journal of global health · 2026Article
- The impact of DRG payment reform on stroke inpatient costs: a propensity score matching and difference-in-differences analysis of a large public hospital in Northeast China.BMC public health · 2025Article
- Deep learning for cardiovascular management: optimizing pathways and cost control under diagnosis-related group models.Frontiers in artificial intelligence · 2025Review
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4 authors.
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Abstract
Background: The National Health Commission and the other relevant departments in China have initiated testing of the Diagnosis Related Groups (DRGs) system in 30 pilot locations since 2019. In the process of DRG payment reform, accounting for the costs of diseases has become a highly challenging issue. The traditional method of disease accounting method overlooks the compensation for the knowledge capital value of medical personnel. Objective: The primary objective of this study is to analyze the cost accounting scheme of China's Diagnosis Related Groups (C-DRG), focusing on the value of knowledge capital. Methods: The study initially proposes a measurement index system for the value of knowledge-based capital, including the difficulty of disease treatment, labor intensity of disease treatment, risk of disease treatment, and operation/treatment time for diseases. The Analytic Hierarchy Process (AHP) is then utilized to weigh the features of medical workers' knowledge capital value. First, pairwise comparisons are conducted in this stage to develop a two-pair judgment matrix of the primary indicators. Second, the eigenvectors corresponding to the maximum eigenvalues of the matrix are calculated to generate the weight coefficient of each feature. The consistency test is carried out after this stage. An empirical analysis is conducted by collecting data, including the full costs of treating three types of diseases-hip replacement, acute simple appendicitis, and heart bypass surgery-from one public medical institution. Results: The empirical analysis examines whether this DRG costing accounting can address the issue of neglecting the value of medical workers' knowledge capital. The methods reconfigure the positive incentive mechanism, stimulate the endogenous motivation of the medical service system, foster independent changes in medical behavior, and achieve the goals of reasonable cost control. Conclusion: In the cost accounting system of C-DRG, the value of medical workers' knowledge capital is acknowledged. This acknowledgment not only boosts the enthusiasm and creativity of medical workers in optimizing and standardizing the diagnosis and treatment process but also improves the transparency and authenticity of DRG pricing. This is particularly evident in the optimization and standardization of the diagnosis and treatment processes within medical institutions and in monitoring inadequate medical practices within these institutions.
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