Evidence map›Paper›PMID 29164424›Full record

ArticleHealth care management science2019

Service quality benchmarking via a novel approach based on fuzzy ELECTRE III and IPA: an empirical case involving the Italian public healthcare context.

Concetta Manuela La Fata, Toni Lupo, Tommaso Piazza

Abstract read
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Article in Health care management science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

6 citing papers in PubMed.

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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

3 authors.

Concetta Manuela La FataDipartimento dell'Innovazione Industriale e Digitale (DIID) - Ingegneria Chimica, Gestionale, Informatica, Meccanica, Università degli Studi di Palermo, Viale delle Scienze, 90128, Palermo, Italy. concettamanuela.lafata@unipa.it.ORCID http://orcid.org/0000-0002-0250-9201
Toni LupoDipartimento dell'Innovazione Industriale e Digitale (DIID) - Ingegneria Chimica, Gestionale, Informatica, Meccanica, Università degli Studi di Palermo, Viale delle Scienze, 90128, Palermo, Italy.
Tommaso PiazzaUniversità Ca' Foscari, Rio Nuovo - Dorsoduro, 3861 30123, Venezia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel fuzzy-based approach which combines ELECTRE III along with the Importance-Performance Analysis (IPA) is proposed in the present work to comparatively evaluate the service quality in the public healthcare context. Specifically, ELECTRE III is firstly considered to compare the service performance of examined hospitals in a noncompensatory manner. Afterwards, IPA is employed to support the service quality management to point out improvement needs and their priorities. The proposed approach also incorporates features of the Fuzzy Set Theory so as to address the possible uncertainty, subjectivity and vagueness of involved experts in evaluating the service quality. The model is applied to five major Sicilian public hospitals, and strengths and criticalities of the delivered service are finally highlighted and discussed. Although several approaches combining multi-criteria methods have already been proposed in the literature to evaluate the service performance in the healthcare field, to the best of the authors' knowledge the present work represents the first attempt at comparing service performance of alternatives in a noncompensatory manner in the investigated context.

Indexed as

Quality of Health CareBenchmarkingFuzzy LogicHumansItalyModels, OrganizationalQuality Assurance, Health CareELECTRE IIIFuzzy set theoryHealthcare qualityIPAService quality benchmarkingService quality management

Identifiers

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.