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Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

BACKGROUND: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. METHODS: In this po...

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Autores principales: Costello, Ruth E., Tazare, John, Piehlmaier, Dominik, Herrett, Emily, Parker, Edward P.K., Zheng, Bang, Mansfield, Kathryn E., Henderson, Alasdair D., Carreira, Helena, Bidulka, Patrick, Wong, Angel Y.S., Warren-Gash, Charlotte, Hayes, Joseph F., Quint, Jennifer K., MacKenna, Brian, Mehrkar, Amir, Eggo, Rosalind M., Katikireddi, Srinivasa Vittal, Tomlinson, Laurie, Langan, Sinéad M., Mathur, Rohini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331810/
https://www.ncbi.nlm.nih.gov/pubmed/37434746
http://dx.doi.org/10.1016/j.eclinm.2023.102077
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author Costello, Ruth E.
Tazare, John
Piehlmaier, Dominik
Herrett, Emily
Parker, Edward P.K.
Zheng, Bang
Mansfield, Kathryn E.
Henderson, Alasdair D.
Carreira, Helena
Bidulka, Patrick
Wong, Angel Y.S.
Warren-Gash, Charlotte
Hayes, Joseph F.
Quint, Jennifer K.
MacKenna, Brian
Mehrkar, Amir
Eggo, Rosalind M.
Katikireddi, Srinivasa Vittal
Tomlinson, Laurie
Langan, Sinéad M.
Mathur, Rohini
author_facet Costello, Ruth E.
Tazare, John
Piehlmaier, Dominik
Herrett, Emily
Parker, Edward P.K.
Zheng, Bang
Mansfield, Kathryn E.
Henderson, Alasdair D.
Carreira, Helena
Bidulka, Patrick
Wong, Angel Y.S.
Warren-Gash, Charlotte
Hayes, Joseph F.
Quint, Jennifer K.
MacKenna, Brian
Mehrkar, Amir
Eggo, Rosalind M.
Katikireddi, Srinivasa Vittal
Tomlinson, Laurie
Langan, Sinéad M.
Mathur, Rohini
author_sort Costello, Ruth E.
collection PubMed
description BACKGROUND: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. METHODS: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. FINDINGS: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. INTERPRETATION: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. FUNDING: 10.13039/100009660LSHTM COVID-19 Response Grant (DONAT15912).
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spelling pubmed-103318102023-07-11 Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform Costello, Ruth E. Tazare, John Piehlmaier, Dominik Herrett, Emily Parker, Edward P.K. Zheng, Bang Mansfield, Kathryn E. Henderson, Alasdair D. Carreira, Helena Bidulka, Patrick Wong, Angel Y.S. Warren-Gash, Charlotte Hayes, Joseph F. Quint, Jennifer K. MacKenna, Brian Mehrkar, Amir Eggo, Rosalind M. Katikireddi, Srinivasa Vittal Tomlinson, Laurie Langan, Sinéad M. Mathur, Rohini eClinicalMedicine Articles BACKGROUND: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. METHODS: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. FINDINGS: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. INTERPRETATION: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. FUNDING: 10.13039/100009660LSHTM COVID-19 Response Grant (DONAT15912). Elsevier 2023-06-29 /pmc/articles/PMC10331810/ /pubmed/37434746 http://dx.doi.org/10.1016/j.eclinm.2023.102077 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Articles
Costello, Ruth E.
Tazare, John
Piehlmaier, Dominik
Herrett, Emily
Parker, Edward P.K.
Zheng, Bang
Mansfield, Kathryn E.
Henderson, Alasdair D.
Carreira, Helena
Bidulka, Patrick
Wong, Angel Y.S.
Warren-Gash, Charlotte
Hayes, Joseph F.
Quint, Jennifer K.
MacKenna, Brian
Mehrkar, Amir
Eggo, Rosalind M.
Katikireddi, Srinivasa Vittal
Tomlinson, Laurie
Langan, Sinéad M.
Mathur, Rohini
Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform
title Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform
title_full Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform
title_fullStr Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform
title_full_unstemmed Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform
title_short Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform
title_sort ethnic differences in the indirect effects of the covid-19 pandemic on clinical monitoring and hospitalisations for non-covid conditions in england: a population-based, observational cohort study using the opensafely platform
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331810/
https://www.ncbi.nlm.nih.gov/pubmed/37434746
http://dx.doi.org/10.1016/j.eclinm.2023.102077
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