Association between government policy and delays in emergent and elective surgical care during the COVID-19 pandemic in Brazil: a modeling study

Abstract

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.

Keywords: COVID-19; Elective surgery; Emergency surgery; Global health; Health policy; Pandemics; Surgery.

Fig. 1

The monthly total, emergent, and elective operations performed in Brazil from January 2016 to January 2021. The monthly total, emergent, and elective operations performed in Brazil from January 2016 to January 2021. This Figure. depicts the number of operations over time and shows a dramatic decrease in operations in 2020.

Fig. 2

Expected vs performed operations during the COVID-19 pandemic in Brazil for A) total, B) emergent, and C) elective operations. ARIMA models of surgical procedures in Brazil for A) total, B) emergent, and C) elective operations. Solid black represents historical data, dashed line represents true surgical operations between January 2016 and January 2021. Light grey (90%), and dark grey (95%) represent confidence intervals for predicted number of operations based on historical trends. All panels show a reduction in operations compared to expected rates based on historical data, however this decrease is mainly driven by elective procedures as seen in Panel C.

Fig. 3

Brazilian population-adjusted surgical backlog per 100,000 by state for A) total, B) emergent, and C) elective delayed procedures This series of maps shows Brazilian population-adjusted surgical backlog per 100,000 population by state for A) total, B) emergent, and C) elective delayed procedures. The map displays the population-adjusted backlog using the equal quantile distribution in four groups.

Fig. 4

Relationship between total surgical backlog and government policy response Estimated marginal means were performed to plot the relationship of the stringency index and containment and health index and the A) total surgical backlog B) emergent surgical backlog and C) elective surgical backlog. As stringency increases, the total backlog and emergent backlog decreases, while the elective backlog increases for both COVID-19 policy indices.