The first 20 months of the COVID-19 pandemic: Mortality, intubation and ICU rates among 104,590 patients hospitalized at 21 United States health systems.

MAIN OBJECTIVE: There is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic. STUDY DESIGN AND METHODS: University of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission. RESULTS AND SIGNIFICANCE: The 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months. CONCLUSIONS: Mortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528).

Assessment of Racial/Ethnic Disparities in Hospitalization and Mortality in Patients With COVID-19 in New York City.

Importance: Black and Hispanic populations have higher rates of coronavirus disease 2019 (COVID-19) hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored. Objective: To compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics. Design, Setting, and Participants: This retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status. Exposures: Race and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients). Main Outcomes and Measures: The likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death). Results: Among 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9). Conclusions and Relevance: In this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have critical illness or die after adjustment for comorbidity and neighborhood characteristics. This supports the assertion that existing structural determinants pervasive in Black and Hispanic communities may explain the disproportionately higher out-of-hospital deaths due to COVID-19 infections in these populations.

Optimize Your Electronic Medical Record to Increase Value: Reducing Laboratory Overutilization.

PURPOSE: The purpose of this study is to decrease overutilization of laboratory testing by eliminating a feature of the electronic ordering system that allowed providers to order laboratory tests to occur daily without review. METHODS: We collected rates of utilization of a group of commonly ordered laboratory tests (number of tests per patient per day) throughout the entire hospital from June 10, 2013 through June 10, 2015. Our intervention, which eliminated the ability to order daily recurring tests, was implemented on June 11, 2014. We compared pre- and postintervention rates in order to assess the impact and surveyed providers about their experience with the intervention. RESULTS: We examined 1,296,742 laboratory tests performed on 92,799 unique patients over 434,059 patient days. Before the intervention, the target tests were ordered using this daily recurring mechanism 33% of the time. After the intervention we observed an 8.5% (P <.001) to 20.9% (P <.001) reduction in tests per patient per day. The reduction in rate for some of the target tests persisted during the study period, but not for the 2 most commonly ordered tests. We estimated an approximate reduction in hospital costs of $300,000 due to the intervention. CONCLUSION: A simple modification to the order entry system significantly and immediately altered provider practices throughout a large tertiary care academic center. This strategy is replicable by the many hospitals that use the same electronic health record system, and possibly, by users of other systems. Future areas of study include evaluating the additive effects of education and real-time decision support.

Discharge before noon: Effect on throughput and sustainability.

BACKGROUND: Late afternoon hospital discharges are thought to contribute to admission bottlenecks. We previously described an intervention that resulted in a statistically significant increase in the discharge before noon (DBN) rate on 2 inpatient medicine units. OBJECTIVE: To evaluate (1) the effect of an increased DBN rate on the admission arrival time and the number of admissions per hour and (2) the sustainability of our DBN initiative. DESIGN: Pre-/postintervention retrospective analysis. SETTING: Two acute-care inpatient medicine units in a tertiary care, urban, academic medical center. PATIENTS: For the admission arrival time and admissions per hour analysis, all inpatients admitted to the medical units from June 1, 2011 to June 31, 2013. For the sustainability analysis, all patients discharged from July 1, 2013 to December 31, 2014. INTERVENTION: A multidisciplinary intervention to increase the DBN rate. MEASUREMENTS: Date and time of arrival to all inpatient sites, and discharge date and time of all patients from 2 inpatient medicine units. RESULTS: Concurrent with our increase in DBN rate, we found a statistically significant change in the median arrival time of emergency department (ED) admissions and transfers from 5 pm to 4 pm. High-frequency admission peaks were statistically significantly reduced for ED admissions. The statistically significant increase in DBN rate is sustained at 35%. CONCLUSIONS: Increasing the DBN rate correlates with admissions arriving earlier in the day and reductions in high-frequency peaks of ED admissions. Statistically significant improvements in DBN rates are sustainable.