管理公共健康保险服务的生产力

Q4 Business, Management and Accounting International Journal of Multicriteria Decision Making Pub Date : 2014-01-01 DOI:10.1504/IJMCDM.2014.066869
I. Mitropoulos, P. Mitropoulos, A. Sissouras
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引用次数: 0

摘要

近年来,使用数据包络分析方法(DEA)来确定公共组织和公共服务单位的效率得到了相当大的重视,该方法评估被检查单位的相对效率。在其结构中对定量和定性因素进行建模的能力扩展了该方法的实用性。此外,由于DEA最初是作为非营利性情况的有效测量工具而开发的,并且由于此类情况通常表现出“软因素”,因此处理此类因素的能力成为医疗保健系统领域的必要条件。在这项研究中,我们评估了希腊主要公共保险提供者社会保障研究所(IKA)的初级医疗保健单位的效率。
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Managing productivity of public health insurance services
In recent years, considerable emphasis has been given to the determination of the efficiency of public organisations and public service units using the data envelopment analysis method (DEA), which evaluates the relative efficiency of the units under examination. The ability to model both quantitative and qualitative factors in its structure extends the usefulness of the method. Moreover since DEA was initially developed as an efficient measurement tool for non-for-profit situation and since such situations commonly exhibit 'soft factors', the capability to handle such factors becomes a necessity in the field of healthcare system. In this study, we assess the efficiency of the primary healthcare units of the principal Greek public insurance provider the Social Security Institute (IKA).
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来源期刊
International Journal of Multicriteria Decision Making
International Journal of Multicriteria Decision Making Business, Management and Accounting-Strategy and Management
CiteScore
0.70
自引率
0.00%
发文量
9
期刊介绍: IJMCDM is a scholarly journal that publishes high quality research contributing to the theory and practice of decision making in ill-structured problems involving multiple criteria, goals and objectives. The journal publishes papers concerning all aspects of multicriteria decision making (MCDM), including theoretical studies, empirical investigations, comparisons and real-world applications. Papers exploring the connections with other disciplines in operations research and management science are particularly welcome. Topics covered include: -Artificial intelligence, evolutionary computation, soft computing in MCDM -Conjoint/performance measurement -Decision making under uncertainty -Disaggregation analysis, preference learning/elicitation -Group decision making, multicriteria games -Multi-attribute utility/value theory -Multi-criteria decision support systems and knowledge-based systems -Multi-objective mathematical programming -Outranking relations theory -Preference modelling -Problem structuring with multiple criteria -Risk analysis/modelling, sensitivity/robustness analysis -Social choice models -Theoretical foundations of MCDM, rough set theory -Innovative applied research in relevant fields
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