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Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study
BACKGROUND: The impact of public health policy to reduce the spread of COVID-19 on access to surgical care is poorly defined. We aim to quantify the surgical backlog during the COVID-19 pandemic in the Brazilian public health system and determine the relationship between state-level policy response...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552244/ https://www.ncbi.nlm.nih.gov/pubmed/34725652 http://dx.doi.org/10.1016/j.lana.2021.100056 |
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author | Truche, Paul Campos, Letícia Nunes Marrazzo, Enzzo Barrozo Rangel, Ayla Gerk Bernardino, Ramon Bowder, Alexis N Buda, Alexandra M Faria, Isabella Pompermaier, Laura Rice, Henry E. Watters, David Dantas, Fernanda Lage Lima Mooney, David P. Botelho, Fabio Ferreira, Rodrigo Vaz Alonso, Nivaldo |
author_facet | Truche, Paul Campos, Letícia Nunes Marrazzo, Enzzo Barrozo Rangel, Ayla Gerk Bernardino, Ramon Bowder, Alexis N Buda, Alexandra M Faria, Isabella Pompermaier, Laura Rice, Henry E. Watters, David Dantas, Fernanda Lage Lima Mooney, David P. Botelho, Fabio Ferreira, Rodrigo Vaz Alonso, Nivaldo |
author_sort | Truche, Paul |
collection | PubMed |
description | BACKGROUND: The impact of public health policy to reduce the spread of COVID-19 on access to surgical care is poorly defined. We aim to quantify the surgical backlog during the COVID-19 pandemic in the Brazilian public health system and determine the relationship between state-level policy response and the degree of state-level delays in public surgical care. METHODS: Monthly estimates of surgical procedures performed per state from January 2016 to December 2020 were obtained from Brazil's Unified Health System Informatics Department. Forecasting models using historical surgical volume data before March 2020 (first reported COVID-19 case) were constructed to predict expected monthly operations from March through December 2020. Total, emergency, and elective surgical monthly backlogs were calculated by comparing reported volume to forecasted volume. Linear mixed effects models were used to model the relationship between public surgical delivery and two measures of health policy response: the COVID-19 Stringency Index (SI) and the Containment & Health Index (CHI) by state. FINDINGS: Between March and December 2020, the total surgical backlog included 1,119,433 (95% Confidence Interval 762,663–1,523,995) total operations, 161,321 (95%CI 37,468–395,478) emergent operations, and 928,758 (95%CI 675,202–1,208,769) elective operations. Increased SI and CHI scores were associated with reductions in emergent surgical delays but increases in elective surgical backlogs. The maximum government stringency (score = 100) reduced emergency delays to nearly zero but tripled the elective surgical backlog. INTERPRETATION: Strong health policy efforts to contain COVID-19 ensure minimal reductions in delivery of emergent surgery, but dramatically increase elective backlogs. Additional coordinated government efforts will be necessary to specifically address the increased elective backlogs that accompany stringent responses. |
format | Online Article Text |
id | pubmed-8552244 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-85522442021-10-28 Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study Truche, Paul Campos, Letícia Nunes Marrazzo, Enzzo Barrozo Rangel, Ayla Gerk Bernardino, Ramon Bowder, Alexis N Buda, Alexandra M Faria, Isabella Pompermaier, Laura Rice, Henry E. Watters, David Dantas, Fernanda Lage Lima Mooney, David P. Botelho, Fabio Ferreira, Rodrigo Vaz Alonso, Nivaldo Lancet Reg Health Am Research Paper BACKGROUND: The impact of public health policy to reduce the spread of COVID-19 on access to surgical care is poorly defined. We aim to quantify the surgical backlog during the COVID-19 pandemic in the Brazilian public health system and determine the relationship between state-level policy response and the degree of state-level delays in public surgical care. METHODS: Monthly estimates of surgical procedures performed per state from January 2016 to December 2020 were obtained from Brazil's Unified Health System Informatics Department. Forecasting models using historical surgical volume data before March 2020 (first reported COVID-19 case) were constructed to predict expected monthly operations from March through December 2020. Total, emergency, and elective surgical monthly backlogs were calculated by comparing reported volume to forecasted volume. Linear mixed effects models were used to model the relationship between public surgical delivery and two measures of health policy response: the COVID-19 Stringency Index (SI) and the Containment & Health Index (CHI) by state. FINDINGS: Between March and December 2020, the total surgical backlog included 1,119,433 (95% Confidence Interval 762,663–1,523,995) total operations, 161,321 (95%CI 37,468–395,478) emergent operations, and 928,758 (95%CI 675,202–1,208,769) elective operations. Increased SI and CHI scores were associated with reductions in emergent surgical delays but increases in elective surgical backlogs. The maximum government stringency (score = 100) reduced emergency delays to nearly zero but tripled the elective surgical backlog. INTERPRETATION: Strong health policy efforts to contain COVID-19 ensure minimal reductions in delivery of emergent surgery, but dramatically increase elective backlogs. Additional coordinated government efforts will be necessary to specifically address the increased elective backlogs that accompany stringent responses. Elsevier 2021-08-24 /pmc/articles/PMC8552244/ /pubmed/34725652 http://dx.doi.org/10.1016/j.lana.2021.100056 Text en © 2021 The Author(s). Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Truche, Paul Campos, Letícia Nunes Marrazzo, Enzzo Barrozo Rangel, Ayla Gerk Bernardino, Ramon Bowder, Alexis N Buda, Alexandra M Faria, Isabella Pompermaier, Laura Rice, Henry E. Watters, David Dantas, Fernanda Lage Lima Mooney, David P. Botelho, Fabio Ferreira, Rodrigo Vaz Alonso, Nivaldo Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study |
title | Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study |
title_full | Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study |
title_fullStr | Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study |
title_full_unstemmed | Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study |
title_short | Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study |
title_sort | association between government policy and delays in emergent and elective surgical care during the covid-19 pandemic in brazil: a modeling study |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552244/ https://www.ncbi.nlm.nih.gov/pubmed/34725652 http://dx.doi.org/10.1016/j.lana.2021.100056 |
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