Racial and ethnic disparity in clinical outcomes among patients with confirmed COVID-19 infection in a large US electronic health record database

BACKGROUND

Racial and ethnic minority groups have been disproportionately affected by the US coronavirus disease 2019 (COVID-19) pandemic; however, nationwide data on COVID-19 outcomes stratified by race/ethnicity and adjusted for clinical characteristics are sparse. This study analyzed the impacts of race/ethnicity on outcomes among US patients with COVID-19.

METHODS

This was a retrospective observational study of patients with a confirmed COVID-19 diagnosis in the electronic health record from 01 February 2020 through 14 September 2020. Index encounter site, hospitalization, and mortality were assessed by race/ethnicity (Hispanic, non-Hispanic Black [Black], non-Hispanic White [White], non-Hispanic Asian [Asian], or Other/unknown). Associations between racial/ethnic categories and study outcomes adjusted for patient characteristics were evaluated using logistic regression.

FINDINGS

Among 202,908 patients with confirmed COVID-19, patients from racial/ethnic minority groups were more likely than White patients to be hospitalized on initial presentation (Hispanic: adjusted odds ratio 1·690, 95% CI 1·620-1·763; Black: 1·810, 1·743-1·880; Asian: 1·503, 1·381-1·636) and during follow-up (Hispanic: 1·700, 1·638-1·764; Black: 1·578, 1·526-1·633; Asian: 1·391, 1·288-1·501). Among hospitalized patients, adjusted mortality risk was lower for Black patients (0·881, 0·809-0·959) but higher for Asian patients (1·205, 1·000-1·452).

INTERPRETATION

Racial/ethnic minority patients with COVID-19 had more severe disease on initial presentation than White patients. Increased mortality risk was attenuated by hospitalization among Black patients but not Asian patients, indicating that outcome disparities may be mediated by distinct factors for different groups. In addition to enacting policies to facilitate equitable access to COVID-19-related care, further analyses of disaggregated population-level COVID-19 data are needed.

The role of non-oncology specialties in the real world longitudinal journey of prostate cancer patients

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Background: Electronic health records (EHRs) are increasingly being recognized by regulators and researchers as reliable sources of evidence. It is therefore critical that real world evidence databases accurately reflect all diagnostics and interventions that could affect patient outcomes. Some of the commercially available datasets source data solely from oncology clinics, which may not reflect patients’ full care journey. This analysis assessed the contribution of non-oncology specialties to prostate cancer care. Methods: Newly diagnosed prostate cancer patients with encounters between Jan 2014 to Dec 2017 were analyzed from the deidentified Optum Electronic Health Record Data Repository. Diagnostic procedures 6 months prior to the index date (first diagnosis date within the study period) and 1 year post index date were identified. Attending physician specialties were identified. All treatment related encounters up to 1 year post the index dates were mapped by specialty. Codes were verified by certified medical professional. Results: A total of 186,299 prostate cancer patients were identified between Jan 2014 to Dec 2017. In the 6 months prior to index date, biopsy was most commonly ordered by urologists (70%), followed by surgical specialists (14%). Biomarker tests were ordered mostly by general practitioners (40%) followed by urologists (18%). The trend was similar for 1 year post biopsy and other histology procedures. Interestingly, a large portion of treatment encounters was observed outside oncology: 48% of surgical management by urologists (48%), chemotherapy was prescribed by both oncologists (27%) and urologists (31%) in a similar ratio, while radiotherapy was performed predominantly by radiation oncologists (81%). Conclusions: In prostate cancer, a large proportion of care encounters occur outside oncology specialties, with urology conducting a significant proportion of diagnostic testing and early treatment. Restricting source data to oncology specialties may omit key factors affecting patients’ outcomes, therefore data for such studies should reflect the entire care continuum.

Assess how non-oncology care settings influence the longitudinal journey of cancer patients

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Background: Electronic health records (EHRs) are increasingly being accepted by regulators and as real world evidence (RWE). In a recent literature review (published elsewhere in this conference), we identified that many of the commercial databases source data solely from oncology clinics. This analysis aimed to understand the extent to which melanoma skin cancer patients receive cancer care specialties other than oncology. Methods: Newly diagnosed melanoma patients with one or more melanoma encounters (ICD10 CM) from January-Dec 2017 were included from the Optum Electronic Health Record Data Repository. Optum EHR data repository has more than 90 million de-identified patient lives mostly sourced from integrated healthcare delivery network EHRs within the US. Optum data includes the entire care continuum across primary case, across specialties, inpatient and outpatient encounters. Index date was defined as the first date of melanoma diagnosis within the study period. EHR history was assessed for 6 months prior to index and 1 year post index. All pathology, radiology and treatment encounters were identified, and all specialties who participated in the patient’s oncology diagnosis and care were counted. All ICD codes were verified by certified medical professional. Results: A total 7351 patients had one or more melanoma related encounters in 2017. During the 6 months prior to diagnosis, histological tests were ordered mostly by dermatologists (38%), followed by pathologists (19%), while oncologists and surgeons ordered 6% and 5%, respectively. Analysis of surgical excision on or after index indicated that dermatologists performed 47% of procedures followed by plastic surgeons (10%) and oncologists (9%). Oncologists comprised 44% of chemotherapy prescribing, while general medicine accounted for 14%. Conclusions: A large proportion of dermatological cancer care encounters occur outside the oncology setting. Therefore, to understand the factors that affect treatment outcomes, the EHR data used for outcomes research should include the entire care continuum.