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Background: Hospitals are increasingly compared based on clinical outcomes adjusted for severity of illness. Multiple methods exist to adjust for differences between patients. The challenge for consumers of this information, both the public and healthcare providers, is interpreting differences in risk adjustment models particularly when models differ in their use of administrative and physiologic data. We set to examine how administrative and physiologic models compare to each when applied to critically ill patients. Methods: We prospectively abstracted variables for a physiologic and administrative model of mortality from two intensive care units in the United States. Predicted mortality was compared through the Pearsons Product coefficient and Bland- Altman analysis. A subgroup of patients admitted directly from the emergency department was analyzed to remove potential confounding changes in condition prior to ICU admission. Results: We included 556 patients from two academic medical centers in this analysis. The administrative model and physiologic models predicted mortalities for the combined cohort were 15.3% (95% CI 13.7%, 16.8%) and 24.6% (95% CI 22.7%, 26.5%) (t-test p-value<0.001). The r2 for these models was 0.297. The Bland-Atlman plot suggests that at low predicted mortality there was good agreement; however, as mortality increased the models diverged. Similar results were found when analyzing a subgroup of patients admitted directly from the emergency department. When comparing the two hospitals, there was a statistical difference when using the administrative model but not the physiologic model. Unexplained mortality, defined as those patients who died who had a predicted mortality less than 10%, was a rare event by either model. Conclusions: In conclusion, while it has been shown that administrative models provide estimates of mortality that are similar to physiologic models in non-critically ill patients with pneumonia, our results suggest this finding can not be applied globally to patients admitted to intensive care units. As patients and providers increasingly use publicly reported information in making health care decisions and referrals, it is critical that the provided information be understood. Our results suggest that severity of illness may influence the mortality index in administrative models. We suggest that when interpreting "report cards" or metrics, health care providers determine how the risk adjustment was made and compares to other risk adjustment models. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To investigate temporal trends and outcomes associated with early antibiotic prescribing in patients hospitalized with COVID-19. DESIGN: Retrospective propensity-matched cohort study using the National COVID Cohort Collaborative (N3C) database. SETTING: Sixty-six health systems throughout the United States that were contributing to the N3C database. Centers that had fewer than 500 admissions in their dataset were excluded. PATIENTS: Patients hospitalized with COVID-19 were included. Patients were defined to have early antibiotic use if they received at least 3 calendar days of intravenous antibiotics within the first 5 days of admission. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 322,867 qualifying first hospitalizations, 43,089 patients received early empiric antibiotics. Antibiotic use declined across all centers in the data collection period, from March 2020 (23%) to June 2022 (9.6%). Average rates of early empiric antibiotic use (EEAU) also varied significantly between centers (deviance explained 7.33% vs 20.0%, p < 0.001). Antibiotic use decreased slightly by day 2 of hospitalization and was significantly reduced by day 5. Mechanical ventilation before day 2 (odds ratio [OR] 3.57; 95% CI, 3.42-3.72), extracorporeal membrane oxygenation before day 2 (OR 2.14; 95% CI, 1.75-2.61), and early vasopressor use (OR 1.85; 95% CI, 1.78-1.93) but not region of residence was associated with EEAU. After propensity matching, EEAU was associated with an increased risk for in-hospital mortality (OR 1.27; 95% CI, 1.23-1.33), prolonged mechanical ventilation (OR 1.65; 95% CI, 1.50-1.82), late broad-spectrum antibiotic exposure (OR 3.24; 95% CI, 2.99-3.52), and late Clostridium difficile infection (OR 1.60; 95% CI, 1.37-1.87). CONCLUSIONS: Although treatment of COVID-19 patients with empiric antibiotics has declined during the pandemic, the frequency of use remains high. There is significant inter-center variation in antibiotic prescribing practices and evidence of potential harm. Our findings are hypothesis-generating and future work should prospectively compare outcomes and adverse events. [ABSTRACT FROM AUTHOR]