Department of Addictology, First Faculty of Medicine, Charles University and General Teaching Hospital in Prague, Prague, Czechia.
Department of Flight Training, Faculty of Aeronautics, Technical University of Košice, Košice, Slovakia.
Front Public Health. 2023 Aug 8;11:1222125. doi: 10.3389/fpubh.2023.1222125. eCollection 2023.
Our research aims to support decision-making regarding the financing of healthcare projects by structural funds with policies targeting reduction of the development gap among different regions and countries of the European Union as well as the achievement of economic and social cohesion. A fuzzy decision support model for the evaluation and selection of healthcare projects should rank the project applications for the selected region, accounting for the investor's wishes in the form of a regional coefficient in order to reduce the development gap between regions. On the one hand, our proposed model evaluates project applications based on selected criteria, which may be structured, weakly structured, or unstructured. On the other hand, it also incorporates information on the level of healthcare development in the region. The obtained ranking increases the degree of validity of the decision regarding the selection of projects for financing by investors, considering the level of development of the region where the project will be implemented. At the expense of European Union (EU) structural funds, a village, city, region, or state can receive funds for modernization and development of the healthcare sector and all related processes. To minimize risks, it is necessary to implement adequate support systems for decision-making in the assessment of project applications, as well as regional policy in the region where the project will be implemented. The primary goal of this study was to develop a complex fuzzy decision support model for the evaluation and selection of projects in the field of healthcare with the aim of reducing the development gap between regions. Based on the above description, we formed the following scientific hypothesis for this research: if the project selected for financing can successfully achieve its stated goals and increase the level of development of its region, it should be evaluated positively. This evaluation can be obtained using a complex fuzzy model constructed to account for the region's level of development in terms of the availability and quality of healthcare services in the region where the project will be implemented.
我们的研究旨在为以缩小欧盟不同地区和国家之间的发展差距以及实现经济和社会融合为目标的结构基金资助的医疗保健项目的决策提供支持。一个用于评估和选择医疗保健项目的模糊决策支持模型应该对所选地区的项目申请进行排名，通过地区系数的形式考虑投资者的意愿，以缩小地区之间的发展差距。一方面，我们提出的模型基于选定的标准评估项目申请，这些标准可以是结构化的、弱结构化的或非结构化的。另一方面，它还纳入了该地区医疗保健发展水平的信息。获得的排名提高了投资者在考虑项目实施地区的发展水平的情况下选择项目进行融资的决策的有效性。利用欧盟（EU）结构基金，一个村庄、城市、地区或州可以获得资金用于医疗保健部门的现代化和发展以及所有相关流程。为了最小化风险，有必要在评估项目申请以及实施项目的地区的区域政策中实施适当的决策支持系统。本研究的主要目标是开发一个用于评估和选择医疗保健领域项目的复杂模糊决策支持模型，以缩小地区之间的发展差距。基于上述描述，我们为这项研究形成了以下科学假设：如果为融资选择的项目能够成功实现其既定目标并提高其所在地区的发展水平，那么它应该得到积极的评价。可以使用为考虑项目实施地区的医疗保健服务的可用性和质量而构建的复杂模糊模型来获得这种评估。
