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Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients
Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic exposed and exacerbated health disparities between socioeconomic groups. Our purpose was to determine if age, sex, race, insurance, and comorbidities predicted patients' length of stay (LOS) in the hospital and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cureus
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9651930/ https://www.ncbi.nlm.nih.gov/pubmed/36381875 http://dx.doi.org/10.7759/cureus.30224 |
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author | Delora, Adam Mills, Ashlynn Jacobson, David Cornett, Brendon Peacock, William F Datta, Anita Jenks, Shane P |
author_facet | Delora, Adam Mills, Ashlynn Jacobson, David Cornett, Brendon Peacock, William F Datta, Anita Jenks, Shane P |
author_sort | Delora, Adam |
collection | PubMed |
description | Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic exposed and exacerbated health disparities between socioeconomic groups. Our purpose was to determine if age, sex, race, insurance, and comorbidities predicted patients' length of stay (LOS) in the hospital and in-hospital mortality in patients diagnosed with coronavirus disease 2019 (COVID-19) during the early pandemic. Methods Utilizing retrospective, secondarily sourced electronic health record (EHR) data for patients who tested positive for COVID-19 from HCA Healthcare facilities, predictors of LOS and in-hospital mortality were assessed using regression. LOS and in-hospital mortality were assessed using logistic regression and negative binomial regression, respectively. All models included age, insurance status, and sex, while additional covariates were selected using the least absolute shrinkage and selection operator (LASSO) regression. LOS data were presented as incidence rate ratios (IRR), and in-hospital mortality was presented as odds ratios (OR), followed by their 95% confidence intervals (CI). Results There were 111,849 qualifying patient records from March 1, 2020, to August 23, 2020. After excluding those with missing data (n = 7), without clinically confirmed COVID-19 (n = 27,225), and those from a carceral environment (n = 1,861), there were 84,624 eligible patients. Compared to the population of the United States of America, our COVID-19 cohort had a larger proportion of African American patients (23.17% versus 13.4%). The African American patients were more likely to have private insurance providers (28.52% versus 23.68%) and shorter LOS (IRR = 0.88, 95% CI = 0.86-0.90) than the White patient cohort. In addition, the African American versus White patients did not have increased odds (OR = 0.98, 95% CI = 0.96-1.00) of in-hospital mortality. Patients on Medicaid (OR = 1.04, 95% CI = 1.01-1.07) and self-pay (OR = 1.07, 95% CI = 1.00-1.14, noninclusive endpoints) had higher in-hospital mortality than private insurance. Several comorbidities were predictive of an increased LOS, including anxiety (IRR = 1.94, 95% CI = 1.87-2.01) and sedative abuse (IRR = 2.07, 95% CI = 1.63-2.64). Conclusions Race was not associated with increased LOS or in-hospital mortality in patients with COVID-19 infections during the early pandemic. Insurance type, psychiatric comorbidities, and medical comorbidities significantly impacted outcomes in patients with COVID-19. This research and future research in the field should help to determine rational public policies to help mitigate the risk of diseases and their impact on future pandemics. |
format | Online Article Text |
id | pubmed-9651930 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-96519302022-11-14 Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients Delora, Adam Mills, Ashlynn Jacobson, David Cornett, Brendon Peacock, William F Datta, Anita Jenks, Shane P Cureus Public Health Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic exposed and exacerbated health disparities between socioeconomic groups. Our purpose was to determine if age, sex, race, insurance, and comorbidities predicted patients' length of stay (LOS) in the hospital and in-hospital mortality in patients diagnosed with coronavirus disease 2019 (COVID-19) during the early pandemic. Methods Utilizing retrospective, secondarily sourced electronic health record (EHR) data for patients who tested positive for COVID-19 from HCA Healthcare facilities, predictors of LOS and in-hospital mortality were assessed using regression. LOS and in-hospital mortality were assessed using logistic regression and negative binomial regression, respectively. All models included age, insurance status, and sex, while additional covariates were selected using the least absolute shrinkage and selection operator (LASSO) regression. LOS data were presented as incidence rate ratios (IRR), and in-hospital mortality was presented as odds ratios (OR), followed by their 95% confidence intervals (CI). Results There were 111,849 qualifying patient records from March 1, 2020, to August 23, 2020. After excluding those with missing data (n = 7), without clinically confirmed COVID-19 (n = 27,225), and those from a carceral environment (n = 1,861), there were 84,624 eligible patients. Compared to the population of the United States of America, our COVID-19 cohort had a larger proportion of African American patients (23.17% versus 13.4%). The African American patients were more likely to have private insurance providers (28.52% versus 23.68%) and shorter LOS (IRR = 0.88, 95% CI = 0.86-0.90) than the White patient cohort. In addition, the African American versus White patients did not have increased odds (OR = 0.98, 95% CI = 0.96-1.00) of in-hospital mortality. Patients on Medicaid (OR = 1.04, 95% CI = 1.01-1.07) and self-pay (OR = 1.07, 95% CI = 1.00-1.14, noninclusive endpoints) had higher in-hospital mortality than private insurance. Several comorbidities were predictive of an increased LOS, including anxiety (IRR = 1.94, 95% CI = 1.87-2.01) and sedative abuse (IRR = 2.07, 95% CI = 1.63-2.64). Conclusions Race was not associated with increased LOS or in-hospital mortality in patients with COVID-19 infections during the early pandemic. Insurance type, psychiatric comorbidities, and medical comorbidities significantly impacted outcomes in patients with COVID-19. This research and future research in the field should help to determine rational public policies to help mitigate the risk of diseases and their impact on future pandemics. Cureus 2022-10-12 /pmc/articles/PMC9651930/ /pubmed/36381875 http://dx.doi.org/10.7759/cureus.30224 Text en Copyright © 2022, Delora et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Public Health Delora, Adam Mills, Ashlynn Jacobson, David Cornett, Brendon Peacock, William F Datta, Anita Jenks, Shane P Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients |
title | Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients |
title_full | Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients |
title_fullStr | Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients |
title_full_unstemmed | Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients |
title_short | Socioeconomic and Comorbid Factors Affecting Mortality and Length of Stay in COVID-19 Patients |
title_sort | socioeconomic and comorbid factors affecting mortality and length of stay in covid-19 patients |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9651930/ https://www.ncbi.nlm.nih.gov/pubmed/36381875 http://dx.doi.org/10.7759/cureus.30224 |
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