Objectives/Goals: The relationship between factors that strain a healthcare system and delays in antimicrobial dosing for patients with sepsis is unclear – including redosing after first administration. The objective of this study is to define elements of capacity strain that impact timely second antimicrobial administration using electronic health record data. Methods/Study Population: In our planned retrospective cohort study, patients are eligible for inclusion if they present to one of 19 Atrium Health hospitals’ emergency department (ED) between 2022 and 2024, meet 2 or more Systemic Inflammatory Response Syndrome criteria within 6 hours, and are subsequently admitted to an intensive care unit (ICU). Capacity strain is defined using multiple measures including ED and ICU census, ED acuity, patient turnover, and ED wait times. The primary outcome is time between first and second doses of antimicrobials. Secondary outcomes are hospital length of stay (LOS), ICU LOS, days free of mechanical ventilation, and 90-day hospital re-admission. Association between variables will be assessed using univariate and multivariable regression models. Fit statistics will compare model performance. Results/Anticipated Results: Based on prior literature, we anticipate finding high rates of antimicrobial dosing delays (>10% incidence). We hypothesize that higher census, higher ED acuity, higher turnover, and wait times will each be associated with increased risk for delay in antimicrobial administration. This association will hold true when exposures are assessed in the ED, as well as in the ICU. We also expect that a model containing a combination of our proposed exposures will outperform each individual measure. Discussion/Significance of Impact: Gaps remain in understanding how system pressures interact with sepsis care delivery and outcomes. Health system strain may contribute to poor adherence to evidence-based practices. Identifying key strain measures can help direct the design and implementation of targeted interventions to improve care delivery and resource allocation.
Sheehan et al. (Wed,) studied this question.