Optimization referral rate design for hierarchical diagnosis and treatment system based on accessibility-utilization efficiency bi-objective collaboration: A case study of China

Zhongyu Wei, Jianjun Bai and Ruitao Feng

Social Science & Medicine, 2023, vol. 322, issue C

Abstract: The hierarchical diagnosis and treatment reform of China can guide residents to seek medical treatment in an orderly manner and improve access to medical treatment. Most existing studies on hierarchical diagnosis and treatment used accessibility as the evaluation index to determine the referral rate between hospitals. However, the blind pursuit of accessibility will cause the problem of uneven utilization efficiency of hospitals at different levels. In response to this, we constructed a bi-objective optimization model based on the perspective of residents and medical institutions. This model can give the optimal referral rate for each province considering the accessibility of residents and the utilization efficiency of hospitals, to improve the utilization efficiency and equality of access for hospitals. The results showed that the applicability of bi-objective optimization model is good, and the optimal referral rate based on the model can ensure the maximum benefit of the two optimization goals. In the optimal referral rate model, residents' medical accessibility is relatively balanced overall. In terms of obtaining high-grade medical resources, the accessibility is better in the eastern and central regions, but poorer in the western China. According to the current allocation of medical resources in China, the medical tasks undertaken by high-grade hospitals account for 60%–78%, which are still the main force of medical services. In this way, there is a big gap in realizing the “serious diseases do not leave the county” goal of hierarchical diagnosis and treatment reform.

Keywords: Hierarchical diagnosis and treatment system (HDTS); Bi-objective optimization model; Optimal referral rate; China (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.socscimed.2023.115827

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