Background: Emergency departments (EDs) are the major source of hospital admissions, and admissions are a major driver of healthcare costs. Understanding factors that drive admissions is critical to containing cost and optimizing hospital operations. We hypothesized that, due to multiple factors, emergency physicians would be more likely to admit a patient seen later in their shift.
Methods: We conducted an observational cohort study using de-identified data from the operations database at a large academic medical center. We examined all patient visits from July 2010 to July 2016 (n = 294,031 unique ED visits); only patients with missing data were excluded (n=191). The primary exposure of interest was the time during the shift at which a patient was first evaluated by the clinician. We modeled the primary exposure as (1) the last hour of shift, (2) last quarter of shift, and (3) shift hour as a continuous integer. We used a generalized estimating equation with Poisson error, a log link and exchangeable correlation structure. We utilized physician as the clustering level, and adjusted for patient age, gender, emergency severity index (ESI), and 24-hour clock time.
Results: There was a significant association between being evaluated in the last hour (relative risk 1.03, 95% confidence interval 1.01-1.06) and last quarter (RR1.02, 1.01-1.03) and the likelihood of admission. Additionally, there was a trend towards increased likelihood of admission later in shift; the relative risk of admission rises to 1.04 in hour 6, (1.02-1.05), 1.03 in hour 7 (1.01-1.05), 1.04 in hour 8 (1.01-1.06), and 1.06 in hour 9 (1.013-1.101). Based on our estimate of the total attributable risk, we estimate that 78 excess hospitalizations occurred due to being seen in the last hour of a clinician’s shift between 2010 and 2016.
Conclusion: There is a small but significant association between a patient being evaluated later in an emergency physician’s shift and their likelihood of being admitted to the hospital. This is mitigated by the smaller number of new patients seen in the last quarter of a shift. This association also suggests that the effects of shift timing on clinical operations should be studied further, and if replicated, has implications for staffing patterns and cost.