Showing papers by "Carrie A. Redlich published in 2023"
TL;DR: In this paper , the authors evaluated COVID-19 risk factors among healthcare workers (HCWs) before vaccine-induced immunity and found that physicians with the least clinical training exhibited the highest odds of COVID19 antibodies early in the pandemic.
Abstract: Physicians with the least clinical training exhibited the highest odds of COVID-19 antibodies early in the pandemic. Prior to COVID-19 vaccine distribution, standard occupational health interventions including increased training and access to personal protective equipment eliminated the excess risk of COVID-19 among vulnerable healthcare workers. Objective The aim of the study is to evaluate COVID-19 risk factors among healthcare workers (HCWs) before vaccine-induced immunity. Methods We conducted a longitudinal cohort study of HCWs (N = 1233) with SARS-CoV-2 immunoglobulin G quantification by ELISA and repeated surveys over 9 months. Risk factors were assessed by multivariable-adjusted logistic regression and Cox proportional hazards models. Results SARS-CoV-2 immunoglobulin G was associated with work in internal medicine (odds ratio [OR], 2.77; 95% confidence interval [CI], 1.05–8.26) and role of physician-in-training (OR, 2.55; 95% CI, 1.08–6.43), including interns (OR, 4.22; 95% CI, 1.20–14.00) and resident physicians (OR, 3.14; 95% CI, 1.24–8.33). Odds were lower among staff confident in N95 use (OR, 0.55; 95% CI, 0.31–0.96) and decreased over the follow-up. Conclusions Excess COVID-19 risk observed among physicians-in-training early in the COVID-19 pandemic was reduced with improved occupational health interventions before vaccinations.
01 May 2023
TL;DR: In this article , the authors identified predictors of longer sick leave using linear regression analysis in a cross-sectional study design and found that older employees, nurses, and those who caught COVID-19 earlier in the pandemic were more likely to take longer leave days.
Abstract: BACKGROUND
Little has been published on predictors of prolonged sick leaves during the COVID-19 pandemic. This study aims to determine the rate of COVID-19 infections among healthcare workers (HCWs) as well as identify the predictors of longer sick leave days.
METHODS
We identified predictors of longer sick leave using linear regression analysis in a cross-sectional study design.
RESULTS
33% of the total workforce contracted COVID-19. On average, HCWs took 12.5 sick leave days following COVID-19 infection. The regression analysis revealed that older employees, nurses, and those who caught COVID-19 earlier in the pandemic were more likely to take longer sick leave.
CONCLUSION
Age, job position, and month of infection predicted sick leave duration among HCWs in our sample. Results imply that transmission was most likely community-based. Public health interventions should consider these factors when planning for future pandemics.
DOI•
TL;DR: In this article , the authors identified predictors of longer sick leave using linear regression analysis in a cross-sectional study design and found that older employees, nurses, and those who caught COVID-19 earlier in the pandemic were more likely to take longer sick leaves.
Abstract: The work produced by this manuscript can be used by hospitals and healthcare organizations to understand sick leave duration and its predictors among their workers. The results can inform improving and changing sick leave policies for HCWs during pandemics. Background Little has been published on predictors of prolonged sick leaves during the COVID-19 pandemic. This study aims to determine the rate of COVID-19 infections among healthcare workers (HCWs) and to identify the predictors of longer sick leave days. Methods We identified predictors of longer sick leave using linear regression analysis in a cross-sectional study design. Results Thirty-three percent of the total workforce contracted COVID-19. On average, HCWs took 12.5 sick leave days after COVID-19 infection. The regression analysis revealed that older employees, nurses, and those who caught COVID-19 earlier in the pandemic were more likely to take longer sick leave. Conclusions Age, job position, and month of infection predicted sick leave duration among HCWs in our sample. Results imply that transmission was most likely community-based. Public health interventions should consider these factors when planning for future pandemics.