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Construction of a three-stage TOPSIS-RSR-Markov chain model and its application in evaluating the service capacity of public traditional Chinese medicine hospitals in Shanxi Province
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Jue WANG1, Rui-feng LIANG1, 2, 3, Ya-juan SUN4, Wei NIU4, Hu-ze LIU4
Modern Preventive Medicine | 2026, 53(5) : 885 - 890
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Modern Preventive Medicine | 2026, 53(5): 885-890
• Health Policy and Management •
Construction of a three-stage TOPSIS-RSR-Markov chain model and its application in evaluating the service capacity of public traditional Chinese medicine hospitals in Shanxi Province
Full
Jue WANG1, Rui-feng LIANG1, 2, 3, Ya-juan SUN4, Wei NIU4, Hu-ze LIU4
Affiliations
  • Department of Environmental Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030619, China
Published: 2026-03-10 doi: 10.20043/j.cnki.MPM.202507391
Outline
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Objective

To construct a TOPSIS-RSR-Markov chain model to comprehensively evaluate the current situation of traditional Chinese medicine service ability in Shanxi Province and predict the dynamic evolution trend.

Methods

Based on the data of public traditional Chinese medicine hospitals in 11 prefecture-level cities in Shanxi Province from 2021 to 2023, an evaluation system containing two first-class and ten second-class indicators was constructed. TOPSIS method and RSR method were used to rank the ability, and Markov model was used to predict the change trend from 2024 to 2025.

Results

TOPSIS showed that Yuncheng (C=0.88), Jinzhong (C=0.75), Taiyuan (C=0.75) ranked the top three, and Shuozhou (C=0.10) ranked the bottom. The RSR method ranked Taiyuan (RSR=0.818) and Changzhi (RSR=0.75) in the highest grade. The two methods were moderately consistent (Spearman r=0.56). Markov prediction showed that the short-term capacity differentiation, the head agglomeration effect was enhanced, and some low- and medium-level cities were at risk of being downgraded. The proportion of low-level cities was stable at 25%. Sensitivity analysis confirmed that the core conclusions were robust, optimistic and structural optimization scenarios could increase the proportion of high-level cities, and pessimistic scenarios exacerbated the Matthew effect.

Conclusion

The service ability of traditional Chinese medicine in Shanxi Province is characterized by “dynamic evolution in gradient differentiation”. It is necessary to implement the differentiation strategy of “leading by the head city-breakthrough by the central city-bottom out by the tail city” to accelerate the development of traditional Chinese medicine in Shanxi Province.

TOPSIS method  /  Rank sum ratio method  /  Markov chain  /  Traditional Chinese medicine service capability  /  Regional differences
王珏, 梁瑞峰, 孙亚娟, 牛玮, 刘虎则. TOPSIS-RSR-马尔可夫链的三阶段模型构建及其在山西省公立中医院中医药服务能力评估中的应用. 现代预防医学, 2026 , 53 (5) : 885 -890 . DOI: 10.20043/j.cnki.MPM.202507391
Jue WANG, Rui-feng LIANG, Ya-juan SUN, Wei NIU, Hu-ze LIU. Construction of a three-stage TOPSIS-RSR-Markov chain model and its application in evaluating the service capacity of public traditional Chinese medicine hospitals in Shanxi Province[J]. Modern Preventive Medicine, 2026 , 53 (5) : 885 -890 . DOI: 10.20043/j.cnki.MPM.202507391
Year 2026 volume 53 Issue 5
22
12
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doi: 10.20043/j.cnki.MPM.202507391
  • Receive Date:2025-07-22
  • Online Date:2026-11-02
  • Published:2026-03-10
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  • Received:2025-07-22
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    Department of Environmental Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi 030619, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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