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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
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.
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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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