Journal of the American College of Emergency Physicians Open (Oct 2024)

What explains differences in average wait time in the emergency department among different racial and ethnic populations: A linear decomposition approach

  • Hao Wang,
  • Nethra Sambamoorthi,
  • Richard D. Robinson,
  • Heidi Knowles,
  • Jessica J. Kirby,
  • Amy F. Ho,
  • Trevor Takami,
  • Usha Sambamoorthi

DOI
https://doi.org/10.1002/emp2.13293
Journal volume & issue
Vol. 5, no. 5
pp. n/a – n/a

Abstract

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Abstract Objective Non‐Hispanic Black (NHB) and Hispanic/Latino (Hispanic) patients wait longer in the emergency department (ED) to see practitioners when compared with non‐Hispanic White (NHW) patients. We investigate factors contributing to longer wait times for NHB and Hispanic patients using a linear decomposition approach. Methods This retrospective observational study included patients presenting to one tertiary hospital ED from 2019 to 2021. Median wait times among NHW, NHB, and Hispanic were calculated with multivariable linear regressions. The extent to which demographic, clinical, and hospital factors explained the differences in average wait time among the three groups were analyzed with Blinder‒Oaxaca post‐linear decomposition model. Results There were 310,253 total patients including 34.7% of NHW, 34.7% of NHB, and 30.6% of Hispanic patients. The median wait time in NHW was 9 min (interquartile range [IQR] 4‒47 min), in NHB was 13 min (IQR 4‒59 min), and in Hispanic was 19 min (IQR 5‒78 min, p < 0.001). The top two contributors of average wait time difference were mode of arrival and triage acuity level. Post‐linear decomposition analysis showed that 72.96% of the NHB‒NHW and 87.77% of the Hispanic‒NHW average wait time difference were explained by variables analyzed. Conclusion Compared to NHW patients, NHB and Hispanic patients typically experience longer ED wait times, primarily influenced by their mode of arrival and triaged acuity levels. Despite these recognized factors, there remains 12%‒27% unexplained factors at work, such as social determinants of health (including implicit bias and systemic racism) and many other unmeasured confounders, yet to be discovered.

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