The association between day of arrival, time of arrival, daily volume and the rate of patients that "left without being seen"

Am J Emerg Med. 2023 May:67:24-28. doi: 10.1016/j.ajem.2023.02.006. Epub 2023 Feb 8.

Abstract

Introduction: Patients' left without being seen (LWBS) rate is used as an emergency department (ED) quality indicator. Prior research has investigated characteristics of these patients, but there are minimal studies assessing the impact of departmental variables. We evaluate the LWBS rate at a granular level, looking at its relationship to day of week, hour of arrival and total patient volume.

Methods: Retrospective cohort analysis of 109,983 cases from a single academic center. We captured patient disposition, day of week and hour of day of arrival, and total daily volume. Chi-squared test was performed to determine the difference in LWBS rates based on arrival variables. We ran a polynomial regression for LWBS rates by decile of daily patient volume.

Results: The overall LWBS rate was 1.82% over 2 years. This varied significantly by day of week and hour of day (p < 0.001). Day of week rates ranged from 0.73% on Sunday to 2.45% on Wednesday. Hour of day rates ranged from 0.26% between 8 AM-9 AM, to 3.71% between 10 PM-11 PM. As total daily patient volume increased, LWBS rates gradually increased until the 70th percentile, followed by significant exponential growth afterwards.

Discussion: LWBS rates are not static measurements, and vary greatly depending on ED circumstances. Weekdays and evenings have significantly higher rates. Additionally, LWBS rates climb above 2% as daily registrations reach the 70th percentile, increasing exponentially at each subsequent decile. Understanding these effects will allow for more effective, targeted interventions to minimize this rate and improve throughput.

Keywords: Efficiency; Emergency Service, Hospital; Operations; Throughput; Workflow.

MeSH terms

  • Chi-Square Distribution
  • Emergency Service, Hospital*
  • Humans
  • Patients*
  • Retrospective Studies
  • Time Factors
  • Triage