Evidence map›Paper›PMID 38077527›Full record

ArticlePeerJ. Computer science2023

Determination of server location in emergency care systems: an index proposal using data envelopment analysis and the hypercube queuing model.

Enzo Barberio Mariano, Regiane Máximo Siqueira, Caio Vitor Beojone, Octaviano Rojas Luiz, João Victor Rojas Luiz, Hugo Henrique Dos Santos

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Article in PeerJ. Computer science, 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

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Enzo Barberio MarianoDepartment of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
Regiane Máximo SiqueiraDepartment of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
Caio Vitor BeojoneUrban Transport Systems Laboratory (LUTS), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Octaviano Rojas LuizDepartment of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
João Victor Rojas LuizDepartment of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.
Hugo Henrique Dos SantosDepartment of Production Engineering, College of Engineering, São Paulo State University (UNESP), Bauru, São Paulo, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objective of this article is to propose a new composite index (CI) that helps to determine the most effective location of servers in an Emergency Care System (ECS), using Benefit of the Doubt (BoD)/Data Envelopment Analysis (DEA) and the Hypercube queuing model. The CI proposed was developed in four stages: (1) definition of a number of possible ECS configurations through the application of mathematical partitions and permutations; (2) application of the hypercube queuing model to determine performance parameters for each ECS configuration; (3) application of DEA/BoD to build the CI and generate performance rankings, and (4) evaluation of the rankings obtained to define the best configuration for the ECS analyzed. Data from two real cases from Brazil were used to assess the CI proposal. The results obtained confirm that: (a) the hypercube model could, relatively quickly, determine the configuration parameters generated; (b) the application of an appropriate DEA/BoD model enabled the different configurations to be ranked with good discrimination; (c) a pattern in the relationship between ambulance concentration and configuration effectiveness could be identified; and (d) the CI proposed would benefit ECS managers who are making resource location decisions.

Indexed as

Benefit of the doubtData envelopment analysisEmergency care systemsHypercube queuing modelLocation problemsQueuing theory

Identifiers

PMID38077527
PMCPMC10703110

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LicenceCC BY
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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.