The eMERGE Consortium* , * The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.

BACKGROUND Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) may increase the risk of COVID-19 infection or affect disease severity. Prior studies have not examined the association of medication dose with risks. METHODS This retrospective cohort study included people aged ≥18 years enrolled in a US integrated healthcare system for at least 4 months as of 2/29/2020. Current ACEI and ARB use was identified from pharmacy data, and the estimated daily dose was calculated and standardized across medications. COVID-19 infections and hospitalizations were identified through 6/14/2020 from laboratory and hospitalization data. We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals, adjusting for race/ethnicity, obesity and other covariates. RESULTS Among 322,044 individuals, 826 developed COVID-19 infection. Among people using ACEI/ARBs, 204/56,105 developed COVID-19 (3.6 per 1000 individuals) compared with 622/265,939 without ACEI/ARB use (2.3 per 1000), yielding an adjusted OR of 0.91 (95% CI 0.74-1.12). For use of < 1 defined daily dose vs. nonuse, the adjusted OR for infection was 0.92 (95% CI 0.66-1.28); for 1 to < 2 defined daily doses, 0.89 (95% CI 0.66-1.19); and for ≥2 defined daily doses, 0.92 (95% CI 0.72-1.18). The OR was similar for ACEIs and ARBs and in subgroups by age and sex. 26% of people with COVID-19 infection were hospitalized; the adjusted OR for hospitalization in relation to ACEI/ARB use was 0.98 (95% CI 0.63-1.54), and there was no association with dose. CONCLUSIONS These findings support current recommendations that individuals on these medications continue their use.

Measuring problem prescription opioid use among patients receiving long-term opioid analgesic treatment: development and evaluation of an algorithm for use in EHR and claims data,

COVID-19 inequities have been well-documented. We evaluated whether higher rates of severe COVID-19 in racial and ethnic minority groups were driven by higher infection rates by evaluating if disparities remained when analyses were restricted to people with infection. We conducted a retrospective cohort study of adults insured through Kaiser Permanente (Colorado, Northwest, Washington), follow-up in March–September 2020. Laboratory results and hospitalization diagnosis codes identified individuals with COVID-19. Severe COVID-19 was defined as invasive mechanical ventilation or mortality. Self-reported race and ethnicity, demographics, and medical comorbidities were extracted from health records. Modified Poisson regression estimated adjusted relative risks (aRRs) of severe COVID-19 in full cohort and among individuals with infection. Our cohort included 1,052,774 individuals, representing diverse racial and ethnic minority groups (e.g., 68,887 Asian, 41,243 Black/African American, 93,580 Hispanic or Latino/a individuals). Among 7,399 infections, 442 individuals experienced severe COVID-19. In the full cohort, severe COVID-19 aRRs for Asian, Black/African American, and Hispanic individuals were 2.09 (95% CI: 1.36, 3.21), 2.02 (1.39, 2.93), and 2.09 (1.57, 2.78), respectively, compared to non-Hispanic Whites. In analyses restricted to individuals with COVID-19, all aRRs were near 1, except among Asian Americans (aRR 1.82 [1.23, 2.68]). These results indicate increased incidence of severe COVID-19 among Black/African American and Hispanic individuals is due to higher infection rates, not increased susceptibility to progression. COVID-19 disparities most likely result from social, not biological, factors. Future work should explore reasons for increased severe COVID-19 risk among Asian Americans. Our findings highlight the importance of equity in vaccine distribution. Supplementary Information The online version contains supplementary material available at 10.1007/s40615-021-01205-2.