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      Racial Disparities in COVID-19 Testing and Outcomes : Retrospective Cohort Study in an Integrated Health System

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          Abstract

          In a retrospective cohort study based on data from adult members of a large integrated health system, the authors assessed the contribution of age, sex, race/ethnicity, neighborhood of residence, comorbidities, and measures of acute physiology to rates of COVID-19 testing, infection, hospitalization, mortality, and other health outcomes.

          Abstract

          Visual Abstract. COVID-19 Racial Disparities in an Integrated Health System. In a retrospective cohort study based on data from adult members of a large integrated health system, the authors assessed the contribution of age, sex, race/ethnicity, neighborhood of residence, comorbidities, and measures of acute physiology to rates of COVID-19 testing, infection, hospitalization, mortality, and other health outcomes.
          Visual Abstract.
          COVID-19 Racial Disparities in an Integrated Health System.

          In a retrospective cohort study based on data from adult members of a large integrated health system, the authors assessed the contribution of age, sex, race/ethnicity, neighborhood of residence, comorbidities, and measures of acute physiology to rates of COVID-19 testing, infection, hospitalization, mortality, and other health outcomes.

          Abstract

          Background:

          Racial disparities exist in outcomes after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

          Objective:

          To evaluate the contribution of race/ethnicity in SARS-CoV-2 testing, infection, and outcomes.

          Design:

          Retrospective cohort study (1 February 2020 to 31 May 2020).

          Setting:

          Integrated health care delivery system in Northern California.

          Participants:

          Adult health plan members.

          Measurements:

          Age, sex, neighborhood deprivation index, comorbid conditions, acute physiology indices, and race/ethnicity; SARS-CoV-2 testing and incidence of positive test results; and hospitalization, illness severity, and mortality.

          Results:

          Among 3 481 716 eligible members, 42.0% were White, 6.4% African American, 19.9% Hispanic, and 18.6% Asian; 13.0% were of other or unknown race. Of eligible members, 91 212 (2.6%) were tested for SARS-CoV-2 infection and 3686 had positive results (overall incidence, 105.9 per 100 000 persons; by racial group, White, 55.1; African American, 123.1; Hispanic, 219.6; Asian, 111.7; other/unknown, 79.3). African American persons had the highest unadjusted testing and mortality rates, White persons had the lowest testing rates, and those with other or unknown race had the lowest mortality rates. Compared with White persons, adjusted testing rates among non-White persons were marginally higher, but infection rates were significantly higher; adjusted odds ratios [aORs] for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 2.01 (95% CI, 1.75 to 2.31), 3.93 (CI, 3.59 to 4.30), 2.19 (CI, 1.98 to 2.42), and 1.57 (CI, 1.38 to 1.78), respectively. Geographic analyses showed that infections clustered in areas with higher proportions of non-White persons. Compared with White persons, adjusted hospitalization rates for African American persons, Hispanic persons, Asian persons, and persons of other/unknown race were 1.47 (CI, 1.03 to 2.09), 1.42 (CI, 1.11 to 1.82), 1.47 (CI, 1.13 to 1.92), and 1.03 (CI, 0.72 to 1.46), respectively. Adjusted analyses showed no racial differences in inpatient mortality or total mortality during the study period. For testing, comorbid conditions made the greatest relative contribution to model explanatory power (77.9%); race only accounted for 8.1%. Likelihood of infection was largely due to race (80.3%). For other outcomes, age was most important; race only contributed 4.5% for hospitalization, 12.8% for admission illness severity, 2.3% for in-hospital death, and 0.4% for any death.

          Limitation:

          The study involved an insured population in a highly integrated health system.

          Conclusion:

          Race was the most important predictor of SARS-CoV-2 infection. After infection, race was associated with increased hospitalization risk but not mortality.

          Primary Funding Source:

          The Permanente Medical Group, Inc.

          Related collections

          Most cited references29

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          Is Open Access

          OpenSAFELY: factors associated with COVID-19 death in 17 million patients

          COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.
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            Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study

            Abstract Objective To describe outcomes of people admitted to hospital with coronavirus disease 2019 (covid-19) in the United States, and the clinical and laboratory characteristics associated with severity of illness. Design Prospective cohort study. Setting Single academic medical center in New York City and Long Island. Participants 5279 patients with laboratory confirmed severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection between 1 March 2020 and 8 April 2020. The final date of follow up was 5 May 2020. Main outcome measures Outcomes were admission to hospital, critical illness (intensive care, mechanical ventilation, discharge to hospice care, or death), and discharge to hospice care or death. Predictors included patient characteristics, medical history, vital signs, and laboratory results. Multivariable logistic regression was conducted to identify risk factors for adverse outcomes, and competing risk survival analysis for mortality. Results Of 11 544 people tested for SARS-Cov-2, 5566 (48.2%) were positive. After exclusions, 5279 were included. 2741 of these 5279 (51.9%) were admitted to hospital, of whom 1904 (69.5%) were discharged alive without hospice care and 665 (24.3%) were discharged to hospice care or died. Of 647 (23.6%) patients requiring mechanical ventilation, 391 (60.4%) died and 170 (26.2%) were extubated or discharged. The strongest risk for hospital admission was associated with age, with an odds ratio of >2 for all age groups older than 44 years and 37.9 (95% confidence interval 26.1 to 56.0) for ages 75 years and older. Other risks were heart failure (4.4, 2.6 to 8.0), male sex (2.8, 2.4 to 3.2), chronic kidney disease (2.6, 1.9 to 3.6), and any increase in body mass index (BMI) (eg, for BMI >40: 2.5, 1.8 to 3.4). The strongest risks for critical illness besides age were associated with heart failure (1.9, 1.4 to 2.5), BMI >40 (1.5, 1.0 to 2.2), and male sex (1.5, 1.3 to 1.8). Admission oxygen saturation of 1 (4.8, 2.1 to 10.9), C reactive protein level >200 (5.1, 2.8 to 9.2), and D-dimer level >2500 (3.9, 2.6 to 6.0) were, however, more strongly associated with critical illness than age or comorbidities. Risk of critical illness decreased significantly over the study period. Similar associations were found for mortality alone. Conclusions Age and comorbidities were found to be strong predictors of hospital admission and to a lesser extent of critical illness and mortality in people with covid-19; however, impairment of oxygen on admission and markers of inflammation were most strongly associated with critical illness and mortality. Outcomes seem to be improving over time, potentially suggesting improvements in care.
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              Structural racism and health inequities in the USA: evidence and interventions

              The Lancet, 389(10077), 1453-1463
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                Author and article information

                Journal
                Ann Intern Med
                Ann Intern Med
                aim
                Annals of Internal Medicine
                American College of Physicians
                0003-4819
                1539-3704
                9 February 2021
                : M20-6979
                Affiliations
                [1 ]Kaiser Permanente, Oakland, California (G.J.E., L.S., G.T.R., C.L.)
                [2 ]Stanford Cancer Institute, Stanford, California (A.S.A.)
                [3 ]Kaiser Permanente, Oakland, and Kaiser Permanente Medical Center, Santa Clara, California (V.X.L.)
                [4 ]The Permanente Medical Group, Inc., Oakland, California (Y.I.C., S.M.P.)
                [5 ]Kaiser Permanente, Oakland, and Kaiser Permanente Medical Center, Walnut Creek, California (L.C.M.)
                [6 ]Kaiser Permanente Medical Center, San Jose, California (C.M.R.)
                [7 ]Kaiser Permanente Medical Center, Martinez, California (R.D.)
                Author notes
                Acknowledgment: The authors thank the Kaiser Permanente Division of Research Strategic Programming Group for formatting the data set; Brian L. Lawson, PhD, Colleen Plimier, MPH, and John D. Greene, MA, for assistance with programming; Dr. Tracy Lieu, Director of the Division of Research, for reviewing the manuscript; and Kathleen Daly for formatting the manuscript for submission.
                Financial Support: By The Permanente Medical Group, Inc., and Kaiser Foundation Hospitals, Inc. Dr. Vincent Liu was supported by National Institutes of Health grant R35GM128672.
                Reproducible Research Statement: Study protocol and statistical code: Available from Dr. Escobar ( gabriel.escobar@ 123456kp.org ). Data set: Data are the property of Kaiser Foundation Health Plan, Inc. and are not available outside a formal collaboration approved by the Kaiser Permanente Northern California Institutional Review Board.
                Corresponding Author: Gabriel J. Escobar, MD, Kaiser Permanente Division of Research, 2000 Broadway Avenue, Oakland, CA 94612; e-mail, gabriel.escobar@ 123456kp.org .
                Current Author Addresses: Drs. Escobar, Liu, Myers, and Lee; Ms. Soltesz; and Mr. Ray: Kaiser Permanente Division of Research, 2000 Broadway Avenue, Oakland, CA 94612.
                Dr. Adams: Intensive Care Unit, Kaiser Permanente Medical Center, 700 Lawrence Expressway, Santa Clara, CA 95051.
                Drs. Chen and Parodi: The Permanente Medical Group, Inc., 1950 Franklin Street, Oakland, CA 94612.
                Dr. Ramaprasad: Adult Infectious Disease, Kaiser Permanente Medical Center, 270 International Circle, San Jose, CA 95124.
                Dr. Dlott: Division of Endocrinology, Kaiser Permanente Medical Center, 200 Muir Road, Martinez, CA 94553.
                Author Contributions: Conception and design: G.J. Escobar, A.S. Adams, V.X. Liu, Y.I. Chen, S.M. Parodi. L.C. Myers.
                Analysis and interpretation of the data: G.J. Escobar, A.S. Adams, V.X. Liu, L. Soltesz, Y.I. Chen, S.M. Parodi, G.T. Ray, L.C. Myers, C.M. Ramaprasad, R. Dlott, C. Lee.
                Drafting of the article: G.J. Escobar, V.X. Liu, Y.I. Chen, L. Soltesz, L.C. Myers, R. Dlott, C. Lee.
                Critical revision for important intellectual content: G.J. Escobar, A.S. Adams, V.X. Liu, Y.I. Chen, S.M. Parodi, G.T. Ray, L.C. Myers.
                Final approval of the article: G.J. Escobar, A.S. Adams, V.X. Liu, L. Soltesz, Y.I. Chen, S.M. Parodi, G.T. Ray, L.C. Myers, C.M. Ramaprasad, R. Dlott, C. Lee.
                Statistical expertise: C. Lee.
                Obtaining of funding: G.J. Escobar, Y.I. Chen, S.M. Parodi.
                Administrative, technical, or logistic support: G.J. Escobar, V.X. Liu, Y.I. Chen, L.C. Myers.
                Collection and assembly of data: G.J. Escobar.
                Author information
                https://orcid.org/0000-0002-0146-4996
                https://orcid.org/0000-0002-2872-3388
                https://orcid.org/0000-0002-5746-774X
                https://orcid.org/0000-0003-0008-9052
                Article
                aim-olf-M206979
                10.7326/M20-6979
                7893537
                33556278
                46339470-f3e9-49d9-b027-4f8c590304ad
                Copyright @ 2021

                This article is made available via the PMC Open Access Subset for unrestricted re-use for research, analyses, and text and data mining through PubMed Central. Acknowledgement of the original source shall include a notice similar to the following: "© 2020 American College of Physicians. Some rights reserved. This work permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited." These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

                History
                Categories
                Original Research
                early, Currently Online First
                coronavirus, Coronavirus Disease 2019 (COVID-19)
                hospital, Hospital Medicine
                poc-eligible, POC Eligible

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