COVID-19 has disproportionately affected low-income communities and people of color. Previous studies demonstrated that race/ethnicity and socioeconomic status (SES) are not independently correlated with COVID-19 mortality. The purpose of our study is to determine the effect of race/ethnicity and SES on COVID-19 30-day mortality in a diverse, Philadelphian population. This is a retrospective cohort study in a single-center tertiary care hospital in Philadelphia, PA. The study includes adult patients hospitalized with polymerase-chain-reaction-confirmed COVID-19 between March 1, 2020 and June 6, 2020. The primary outcome was a composite of COVID-19 death or hospice discharge within 30 days of discharge. The secondary outcome was intensive care unit (ICU) admission. The study included 426 patients: 16.7% died, 3.3% were discharged to hospice, and 20.0% were admitted to the ICU. Using multivariable analysis, race/ethnicity was not associated with the primary nor secondary outcome. In Model 4, age greater than 75 (odds ratio [OR]: 11.01; 95% confidence interval [CI]: 1.96-61.97) and renal disease (OR: 2.78; 95% CI: 1.31-5.90) were associated with higher odds of the composite primary outcome.Living in a "very-low-income area" (OR: 0.29; 95% CI: 0.12-0.71) and body mass index (BMI) 30-35 (OR: 0.24; 95% CI: 0.08-0.69) were associated with lower odds of the primary outcome. When controlling for demographics, SES, and comorbidities, race/ethnicity was not independently associated with the composite primary outcome. Very-low SES, as extrapolated from census-tract-level income data, was associated with lower odds of the composite primary outcome.

International Statistical Classification of Disease and Related Health Problems, 10th Revision codes (ICD‐10) are used to characterize cohort comorbidities. Recent literature does not demonstrate standardized extraction methods. Objective: Compare COVID‐19 cohort manual‐chart‐review and ICD‐10‐based comorbidity data; characterize the accuracy of different methods of extracting ICD‐10‐code‐based comorbidity, including the temporal accuracy with respect to critical time points such as day of admission. Design: Retrospective cross‐sectional study. Measurements: ICD‐10‐based‐data performance characteristics relative to manual‐chart‐review. Results: Discharge billing diagnoses had a sensitivity of 0.82 (95% confidence interval [CI]: 0.79–0.85; comorbidity range: 0.35–0.96). The past medical history table had a sensitivity of 0.72 (95% CI: 0.69–0.76; range: 0.44–0.87). The active problem list had a sensitivity of 0.67 (95% CI: 0.63–0.71; range: 0.47–0.71). On day of admission, the active problem list had a sensitivity of 0.58 (95% CI: 0.54–0.63; range: 0.30–0.68)and past medical history table had a sensitivity of 0.48 (95% CI: 0.43–0.53; range: 0.30–0.56). Conclusions and Relevance: ICD‐10‐based comorbidity data performance varies depending on comorbidity, data source, and time of retrieval; there are notable opportunities for improvement. Future researchers should clearly outline comorbidity data source and validate against manual‐chart‐review.

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Quality Improvement and Patient Safety (QIPS) has become an increasingly important area of focus within undergraduate and graduate medical education. A variety of different QIPS curriculums have been developed, but standardization and effectiveness of these curriculums is largely unknown. The authors conducted a scoping review to explore the status of undergraduate and graduate nondegree QIPS curriculum in the United States. A scoping review was performed using The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model as a guide. Two databases were screened from January 2019 to March 2022 to identify relevant articles. Forty-seven articles met eligibility criteria, with most articles (n = 38) focused on graduate medical education. Of those 38, 86.8% (33/38) were developed as curriculum specific to a particular specialty. The article highlights similarities and differences in structure, evaluation metrics, and outcomes, and subsequently offers insight into curriculum components that should help guide standardization of successful curriculum development moving forward.