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A DEA-Based Complexity of Needs Approach for Hospital Beds Evacuation during the COVID-19 Outbreak.
Nepomuceno, Thyago C C; Silva, Wilka M N; Nepomuceno, Késsia T C; Barros, Isloana K F.
  • Nepomuceno TCC; Sapienza University of Rome, Dipartimento Di Ingegneria Informatica Automatica e Gestionale "Antonio Ruberti", Via Ariosto, 25, Roma 00185, Italy.
  • Silva WMN; Federal University of Pernambuco, Núcleo De Tecnologia, Av. Marielle Franco, s/n-Km 59-Nova Caruaru, Recife, Brazil.
  • Nepomuceno KTC; Federal University of Pernambuco, Departamento De Bioquímica, Avenida Prof. Moraes Rego, s/n-Cidade Universitária, CEP: 50.670-420-Recife/PE, Recife, Brazil.
  • Barros IKF; Federal University of Pernambuco, Centro De Informática, Av. J. Anibal Fernandes, s/n, Cidade Universitária, CEP: 50.740-560-Recife/PE, Recife, Brazil.
J Healthc Eng ; 2020: 8857553, 2020.
Artículo en Inglés | MEDLINE | ID: covidwho-841226
ABSTRACT
Data envelopment analysis (DEA) is a powerful nonparametric engineering tool for estimating technical efficiency and production capacity of service units. Assuming an equally proportional change in the output/input ratio, we can estimate how many additional medical resource health service units would be required if the number of hospitalizations was expected to increase during an epidemic outbreak. This assessment proposes a two-step methodology for hospital beds vacancy and reallocation during the COVID-19 pandemic. The framework determines the production capacity of hospitals through data envelopment analysis and incorporates the complexity of needs in two categories for the reallocation of beds throughout the medical specialties. As a result, we have a set of inefficient healthcare units presenting less complex bed slacks to be reduced, that is, to be allocated for patients presenting with more severe conditions. The first results in this work, in collaboration with state and municipal administrations in Brazil, report 3772 beds feasible to be evacuated by 64% of the analyzed health units, of which more than 82% are moderate complexity evacuations. The proposed assessment and methodology can provide a direction for governments and policymakers to develop strategies based on a robust quantitative production capacity measure.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Neumonía Viral / Lechos / Infecciones por Coronavirus / Pandemias / Hospitales Tipo de estudio: Estudio observacional / Estudio pronóstico Límite: Humanos País/Región como asunto: America del Sur / Brasil Idioma: Inglés Revista: J Healthc Eng Año: 2020 Tipo del documento: Artículo País de afiliación: 2020

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Neumonía Viral / Lechos / Infecciones por Coronavirus / Pandemias / Hospitales Tipo de estudio: Estudio observacional / Estudio pronóstico Límite: Humanos País/Región como asunto: America del Sur / Brasil Idioma: Inglés Revista: J Healthc Eng Año: 2020 Tipo del documento: Artículo País de afiliación: 2020