A DEA-Based Complexity of Needs Approach for Hospital Beds Evacuation during the COVID-19 Outbreak.
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.
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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