Analysis of time-to-disposition intervals during early and late parts of an emergency department shift

Am J Emerg Med. 2021 Dec:50:477-480. doi: 10.1016/j.ajem.2021.09.002. Epub 2021 Sep 4.


Introduction: Time-to-disposition is an important metric for emergency department throughput. We hypothesized that providers view the shift end as a key timepoint and attempt to leave as few dispositions as possible to the oncoming team, thereby making quicker decisions later in the shift. This study evaluates disposition distribution relative to when patients are assigned a provider during the course of a shift.

Methods: 50,802 cases were analyzed over the one-year study interval. 31,869 patients were seen in the early half of a shift (hours 1-4) and 18,933 were seen in the later half (hours 5+). We ran a linear mixed model that adjusted for age, gender, emergency severity index score, time of day, weekend arrivals, quarter of arrival and shift type.

Results: Median time-to-disposition for the early group was 3.25 h (IQR 1.90-5.04), and 2.62 h (IQR 1.51-4.31) for the late group. From our mixed model, we conclude that in the later parts of the shift, providers take on average 15.1% less time to make a disposition decision than in the earlier parts of the shift.

Conclusion: Patients seen during the latter half of a shift were more likely to have a shorter time-to-disposition than similar patients seen in the first half of a shift. This may be influenced by many factors, such as providers spending the early hours of a shift seeing new patients which generate new tasks and delay dispositions, and viewing the end of shift as a landmark with a goal to maximize dispositions prior to sign-out.

Keywords: Disposition; Efficiency; Operations; Throughput; Workflow.

MeSH terms

  • Adult
  • Aged
  • Efficiency, Organizational*
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Humans
  • Length of Stay / statistics & numerical data*
  • Male
  • Middle Aged
  • Practice Patterns, Physicians' / statistics & numerical data*
  • Time Factors