Article ; Online: Estimating Brazilian states' demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model.
Sao Paulo medical journal = Revista paulista de medicina
2021 Volume 139, Issue 2, Page(s) 178–185
Abstract: ... on the provision of intensive care unit and clinical beds for Brazilian states, using an integrated model ... on the historical records of Brazilian states was developed to estimate the need for hospital beds during the COVID ... hospital beds for Brazilian states, of which 38.95% were ICU beds, and 61.05% were clinical beds ...
| 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. |
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| MeSH term(s) | Bed Occupancy/statistics & numerical data ; Brazil/epidemiology ; COVID-19 ; Hospitals ; Humans ; Intensive Care Units/statistics & numerical data ; Pandemics ; SARS-CoV-2 |
| Language | English |
| Publishing date | 2021-03-04 |
| Publishing country | Brazil |
| Document type | Journal Article |
| ZDB-ID | 1203171-9 |
| ISSN | 1806-9460 ; 1516-3180 ; 0035-0362 |
| ISSN (online) | 1806-9460 |
| ISSN | 1516-3180 ; 0035-0362 |
| DOI | 10.1590/1516-3180.2020.0517.R1.0212020 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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