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Estimating Brazilian states demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model
Almeida, João Flávio de Freitas; Conceição, Samuel Vieira; Pinto, Luiz Ricardo; Horta, Cláudia Júlia Guimarães; Magalhães, Virgínia Silva; Campos, Francisco Carlos Cardoso de.
  • Almeida, João Flávio de Freitas; Universidade Federal de Minas Gerais. Department of Industrial Engineering. Belo Horizonte. BR
  • Conceição, Samuel Vieira; Universidade Federal de Minas Gerais. Department of Industrial Engineering. Belo Horizonte. BR
  • Pinto, Luiz Ricardo; Universidade Federal de Minas Gerais. Department of Industrial Engineering. Belo Horizonte. BR
  • Horta, Cláudia Júlia Guimarães; Fundação João Pinheiro. Science and Technology Researcher. Belo Horizonte. BR
  • Magalhães, Virgínia Silva; Universidade Federal de Minas Gerais. School of Medicine. Belo Horizonte. BR
  • Campos, Francisco Carlos Cardoso de; Universidade Federal de Minas Gerais. School of Medicine. Belo Horizonte. BR
São Paulo med. j ; 139(2): 178-185, Mar.-Apr. 2021. tab, graf
Article in English | LILACS | ID: biblio-1181003
ABSTRACT
ABSTRACT

BACKGROUND:

The fragility of healthcare systems worldwide had not been exposed by any pandemic until now. The lack of integrated methods for bed capacity planning compromises the effectiveness of public and private hospitals' services.

OBJECTIVES:

To estimate the impact of the COVID-19 pandemic on the provision of intensive care unit and clinical beds for Brazilian states, using an integrated model. DESIGN AND

SETTING:

Experimental study applying healthcare informatics to data on COVID-19 cases from the official electronic platform of the Brazilian Ministry of Health.

METHODS:

A predictive model based on the historical records of Brazilian states was developed to estimate the need for hospital beds during the COVID-19 pandemic.

RESULTS:

The proposed model projected in advance that there was a lack of 22,771 hospital beds for Brazilian states, of which 38.95% were ICU beds, and 61.05% were clinical beds.

CONCLUSIONS:

The proposed approach provides valuable information to help hospital managers anticipate actions for improving healthcare system capacity.
Subject(s)


Full text: Available Index: LILACS (Americas) Main subject: Bed Occupancy / Pandemics / COVID-19 / Intensive Care Units Type of study: Prognostic study / Risk factors Limits: Humans Country/Region as subject: South America / Brazil Language: English Journal: São Paulo med. j Journal subject: Cirurgia Geral / Ciˆncia / Ginecologia / Medicine / Medicina Interna / Obstetr¡cia / Pediatria / Sa£de Mental / Sa£de P£blica Year: 2021 Type: Article Affiliation country: Brazil Institution/Affiliation country: Fundação João Pinheiro/BR / Universidade Federal de Minas Gerais/BR

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Full text: Available Index: LILACS (Americas) Main subject: Bed Occupancy / Pandemics / COVID-19 / Intensive Care Units Type of study: Prognostic study / Risk factors Limits: Humans Country/Region as subject: South America / Brazil Language: English Journal: São Paulo med. j Journal subject: Cirurgia Geral / Ciˆncia / Ginecologia / Medicine / Medicina Interna / Obstetr¡cia / Pediatria / Sa£de Mental / Sa£de P£blica Year: 2021 Type: Article Affiliation country: Brazil Institution/Affiliation country: Fundação João Pinheiro/BR / Universidade Federal de Minas Gerais/BR