1.安徽医科大学附属亳州医院药学部,安徽 亳州;236800
2.安徽医科大学药学科学学院,合肥 230032
3.中国科学技术大学附属第一医院药学部,合肥 230001
4.亳州市药品和医疗器械不良反应(事件)监测中心,安徽 亳州 236800
5.中国科学技术大学附属第一医院健康管理中心,合肥 230001
Received:14 August 2025,
Revised:2025-11-07,
Accepted:10 November 2025,
Published:15 December 2025
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王海坤,马自创,吴娜,等.博弈论组合赋权-TOPSIS-秩和比法评价临床科室/病区药品不良反应报告质量 [J].中国药房,2025,36(23):2969-2973.
WANG Haikun,MA Zichuang,WU Na,et al.Quality evaluation of adverse drug reaction reports in clinical departments based on game theory combinatorial weighting-TOPSIS-rank-sum ratio method[J].ZHONGGUO YAOFANG,2025,36(23):2969-2973.
王海坤,马自创,吴娜,等.博弈论组合赋权-TOPSIS-秩和比法评价临床科室/病区药品不良反应报告质量 [J].中国药房,2025,36(23):2969-2973. DOI: 10.6039/j.issn.1001-0408.2025.23.15.
WANG Haikun,MA Zichuang,WU Na,et al.Quality evaluation of adverse drug reaction reports in clinical departments based on game theory combinatorial weighting-TOPSIS-rank-sum ratio method[J].ZHONGGUO YAOFANG,2025,36(23):2969-2973. DOI: 10.6039/j.issn.1001-0408.2025.23.15.
目的
2
基于博弈论组合赋权-逼近理想解排序(TOPSIS)-秩和比(RSR)法综合评价临床科室或病区(后文简称“科室”)药品不良反应(ADR)的报告质量,为进一步规范ADR上报工作提供参考。
方法
2
参照相关文件及评分标准,对本团队前期制定的ADR报告质量评价标准进行修改,基于博弈论确定各评价指标的组合权重,构建博弈论组合赋权-TOPSIS-RSR模型。对安徽医科大学附属亳州医院各科室上报至药学部的原始ADR报告质量进行评价并分档。
结果
2
共纳入23个科室的222份ADR报告。博弈论组合赋权通过优化指标权重识别出ADR症状、体征,原患疾病描述,ADR时间等为管理的薄弱环节。TOPSIS-RSR法计算得出各科室相对贴近度的均值为0.401 7,整体报告质量处于中等至不合格水平。神经外科等3个科室的ADR报告质量为中等[估计贴近度(
Ĉ
i
)≥0.506
]
,呼吸科等2个科室为不合格(
Ĉ
i
<0.278),其余科室均为合格(0.278≤
Ĉ
i
<0.506)。
结论
2
本研究构建的博弈论组合赋权-TOPSIS-RSR法为ADR报告质量评价提供了一种兼顾主、客观权重且有利于科室间比较的有效方法;该院ADR报告质量尚需进一步提升。
OBJECTIVE
2
To comprehensively evaluate the quality of adverse drug reaction (ADR) reports in clinical departments or ward (hereinafter referred to as “department”) based on game theory combinatorial weighting-technique for order preference by similarity to ideal solution (TOPSIS)-rank-sum ratio (RSR) method, providing a reference for the further standardization of ADR reporting.
METHODS
2
Based on relevant documents and scoring criteria, the ADR report quality evaluation standards previously developed by our team were modified. Using game theory principles, the fusion of subjective and objective weights for each indicator was determined. A game theory combinatorial weighting-TOPSIS-RSR model was developed to evaluate and categorize the quality of raw ADR reports submitted by departments to the pharmacy department at Bozhou Hospital of Anhui Medical University.
RESULTS
2
A total of 222 ADR reports from 23 departments were included. The game theory combinatorial weighting method identifies weak points in management, such as ADR symptoms and signs, the description of underlying diseases, timing of ADR, by optimizing the weightings of the indicators. The TOPSIS-RSR method calculates that the mean relative closeness of the departments was 0.401 7, indicating that the overall report quality ranged from moderate to substandard. Three departments, including neurosurgery, demonstrated medium reporting quality [estinate closeness (
Ĉ
i
)≥0.506
]
, while two departments, such as the respiratory department, were rated as unqualified (
Ĉ
i
<0.278). The remaining departments were all deemed qualified (0.278≤
Ĉ
i
<0.506).
CONCLUSIONS
2
The developed game theory combinatorial weighting-TOPSIS-RSR method provides an effective approach for the quality evaluation of ADR reports, which not only balances subjective and objective weights but also facilitates comparisons among different departments. There is still room for improvement in the ADR report quality at the hospital.
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