Objectives Studies of the early months of the COVID-19 pandemic indicate that patient outcomes may be adversely affected by surges. But the impact on in-hospital mortality during the largest surge to date, September 2020-March 2021, has not been studied. This study aimed to determine if in-hospital mortality was impacted by the community surge of COVID-19. Methods A retrospective cohort study of 416,962 adult COVID-19 patients admitted immediately before or during the surge at 229 U.S. academic and 432 community hospitals in the Vizient Clinical Database. The odds ratios of death among hospitalized patients during each phase of the surge was compared with the corresponding odds prior to the surge and adjusted for demographic, comorbidity, hospital characteristic, length of stay and complication variables. Results The unadjusted proportion of deaths among discharged patients was 9% in both the pre-surge and rising surge stages but rose to 12% during both the peak and declining surge intervals. With the pre-surge phase defined as the referent, the risk-adjusted odds ratios (aORs) for the surge periods were rising, 1.14 (1.10-1.19), peak 1.37 (1.32-1.43), and declining, 1.30 (1.25-1.35). The surge rise in-hospital mortality was present in seven of nine geographic divisions and greater for community hospitals than for academic centers. Conclusions These data support public policies aimed at containing pandemic surges and supporting health care delivery during surges.

BACKGROUND Since the initial COVID-19 cases were identified in the United States in February 2020, the United States has experienced a high incidence of the disease. Understanding the risk factors for severe outcomes identifies the most vulnerable populations and helps in decision-making. OBJECTIVE This study aims to assess the factors associated with COVID-19–related deaths from a large, national, individual-level data set. METHODS A cohort study was conducted using data from the Optum de-identified COVID-19 electronic health record (EHR) data set; 1,271,033 adult participants were observed from February 1, 2020, to August 31, 2020, until their deaths due to COVID-19, deaths due to other reasons, or the end of the study. Cox proportional hazards models were constructed to evaluate the risks for each patient characteristic. RESULTS A total of 1,271,033 participants (age: mean 52.6, SD 17.9 years; male: 507,574/1,271,033, 39.93%) were included in the study, and 3315 (0.26%) deaths were attributed to COVID-19. Factors associated with COVID-19–related death included older age (80 vs 50-59 years old: hazard ratio [HR] 13.28, 95% CI 11.46-15.39), male sex (HR 1.68, 95% CI 1.57-1.80), obesity (BMI 40 vs <30 kg/m₂: HR 1.71, 95% CI 1.50-1.96), race (Hispanic White, African American, Asian vs non-Hispanic White: HR 2.46, 95% CI 2.01-3.02; HR 2.27, 95% CI 2.06-2.50; HR 2.06, 95% CI 1.65-2.57), region (South, Northeast, Midwest vs West: HR 1.62, 95% CI 1.33-1.98; HR 2.50, 95% CI 2.06-3.03; HR 1.35, 95% CI 1.11-1.64), chronic respiratory disease (HR 1.21, 95% CI 1.12-1.32), cardiac disease (HR 1.10, 95% CI 1.01-1.19), diabetes (HR 1.92, 95% CI 1.75-2.10), recent diagnosis of lung cancer (HR 1.70, 95% CI 1.14-2.55), severely reduced kidney function (HR 1.92, 95% CI 1.69-2.19), stroke or dementia (HR 1.25, 95% CI 1.15-1.36), other neurological diseases (HR 1.77, 95% CI 1.59-1.98), organ transplant (HR 1.35, 95% CI 1.09-1.67), and other immunosuppressive conditions (HR 1.21, 95% CI 1.01-1.46). CONCLUSIONS This is one of the largest national cohort studies in the United States; we identified several patient characteristics associated with COVID-19–related deaths, and the results can serve as the basis for policy making. The study also offered directions for future studies, including the effect of other socioeconomic factors on the increased risk for minority groups.

Objective To create and validate a methodology to assign a severity level to an episode of COVID-19 for retrospective analysis in claims data. Data Source Secondary data obtained by license agreement from Optum provided claims records nationally for 19,761,754 persons, of which, 692,094 persons had COVID-19 in 2020. Study Design The World Health Organization (WHO) COVID-19 Progression Scale was used as a model to identify endpoints as measures of episode severity within claims data. Endpoints used included symptoms, respiratory status, progression to levels of treatment and mortality. Data Collection/Extraction methods The strategy for identification of cases relied upon the February 2020 guidance from the Centers for Disease Control and Prevention (CDC). Principal Findings A total of 709,846 persons (3.6%) met the criteria for one of the nine severity levels based on diagnosis codes with 692,094 having confirmatory diagnoses. The rates for each level varied considerably by age groups, with the older age groups reaching higher severity levels at a higher rate. Mean and median costs increased as severity level increased. Statistical validation of the severity scales revealed that the rates for each level varied considerably by age group, with the older ages reaching higher severity levels (p < 0.001). Other demographic factors such as race and ethnicity, geographic region, and comorbidity count had statistically significant associations with severity level of COVID-19. Conclusion A standardized severity scale for use with claims data will allow researchers to evaluate episodes so that analyses can be conducted on the processes of intervention, effectiveness, efficiencies, costs and outcomes related to COVID-19.