使用 AHP-TOPSIS 方法,根据驾驶指标评估选定医科大学的治疗绩效

Abbasali Dehghani Tafti, Mehdi Raadabadi, A. Mehrparvar, Maryam Shayegh, Mehdi Khayatan, Hossein Abolhosseini
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摘要

背景:医学院校作为医疗卫生服务的主要机构之一,其绩效评价具有重要意义。在这方面,治疗领域的指标在促进健康指标中起着基础性的作用,影响着医科大学的整体绩效。本研究基于AHP-TOPSIS方法的治疗驱动指数评估了伊朗一所选定的医学科学大学的表现。方法:本研究采用定性与定量相结合的方法。本研究首先对驱动指标进行识别和加权,然后根据这些指标进行绩效分析。该研究的统计人口包括验证和加权阶段的关键专家,以及最后阶段与伊朗一所医科大学有关的九年资料。研究中使用的工具是索引收集表。利用Expert Choice和Excel,采用层次分析法对指标进行排序。采用TOPSIS模型进行性能评价。结果:第一步采用回顾性研究,确定了111个指标,在验证阶段,选择了10个治疗域指标。然后,对各权重指标进行分层分析和两两比较,得出护理人员总数占可用床位比例指标权重最高,为0.161;自然分娩指标权重最低,为0.049。根据TOPSIS方法,被选中的大学在2014年的表现最高(0.228),在2017年的表现最低(0.006)。结论:综合考虑治疗副的战略措施,随着时间的推移对科研指标进行改进和管理,可以提高高校的绩效。因此,应定期并按优先顺序对各项指标进行监测,这样在保持效率的同时,特别是在人力资源相关指标方面,也可以提高措施的有效性,包括改善治疗领域的功能指标。
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Assessment of the Therapeutic Performance of a Selected Medical University Based On Driving Indices Using the AHP-TOPSIS Approach
Background: The assessment of the performance of medical universities as one of the main organizations providing healthcare services is of utmost significance. In this regard, the indices of treatment domain play a fundamental role in promoting health indices and affect the overall performance of the medical university. The present study evaluated the performance of a selected university of medical sciences in Iran based on treatment driving indices with the AHP-TOPSIS approach. Methods: This research applied a combination of qualitative and quantitative methods. In this study, first the driving indices were identified and weighted, and then the performance was analyzed according to the indices. The statistical population of the research consisted of key experts in the validation and weighting phase and of nine years of information pertaining to one of the medical universities of Iran in the final phase. The instrument used in the study was the Index Collection Form. Prioritization of indices was done by AHP method using Expert Choice and Excel. TOPSIS model were used to evaluate performance. Results: In the first step, using a review study, 111 indices were identified, and in the validation stage, 10 indices of treatment domain were selected. Then, based on hierarchical analysis and pairwise comparisons in the weighted indices, the highest weight or priority pertained to the index of the ratio of the total nursing staff to the available beds with a weight of 0.161 and the lowest weight or priority related to the index of natural delivery to all deliveries with a weight of 0.049. According to the TOPSIS method, the selected university showed the highest performance (0.228) in 2014 and the lowest performance (0.006) in 2017. Conclusion: Considering strategic measures in the deputy of treatment simultaneously to improve and manage research indices over time can improve the performance of universities. Thus, it is appropriate to monitor the indices periodically and in the order of priority, so that in addition to maintaining the efficiency, especially in the indices related to human resources, the effectiveness of the measures, including the improvement of the functional indices of the treatment domain, can also be improved.
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