Evidence map›Paper›PMID 37614458›Full record

ArticleFrontiers in public health2023

A fuzzy decision support model for the evaluation and selection of healthcare projects in the framework of competition.

Beata Gavurova, Miroslav Kelemen, Volodymyr Polishchuk, Tawfik Mudarri, Volodymyr Smolanka

Abstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Beata GavurovaDepartment of Addictology, First Faculty of Medicine, Charles University and General Teaching Hospital in Prague, Prague, Czechia.
Miroslav KelemenDepartment of Flight Training, Faculty of Aeronautics, Technical University of Košice, Košice, Slovakia.
Volodymyr PolishchukDepartment of Software Systems, Faculty of Information Technology, Uzhhorod National University, Uzhhorod, Ukraine.
Tawfik MudarriTechnical University of Košice, Faculty of Mining, Ecology, Process Control and Geotechnologies, Košice, Slovakia.
Volodymyr SmolankaDepartment of Neurology, Neurosurgery and Psychiatry, Faculty of Medicine, Uzhhorod National University, Uzhhorod, Ukraine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Delivery of Health CarePolicyDecision Support TechniquesEuropean Uniondecision-makingEuropean Green Dealexpert evaluationfuzzy setshealthy citiesindustry 5.0projects

Identifiers

PMID37614458
PMCPMC10442559

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.