The Impact of Hospital and Patient Factors on the Emergency Department Decision to Admit

• Published in: The Journal of emergency medicine 2018-02, Vol.54 (2), p.249-257.e1
• Main Authors: Warner, Leah S. Honigman, Galarraga, Jessica E., Litvak, Ori, Davis, Samuel, Granovsky, Michael, Pines, Jesse M.
• Format: Article
• Language: English
• Subjects: admission variation; emergency department; hospital admission
• ISSN: 0736-4679; 2352-5029
• DOI: 10.1016/j.jemermed.2017.11.024

Substantial variation exists in rates of emergency department (ED) admission. We examine this variation after accounting for local and community characteristics. Elucidate the factors that contribute to admission variation that are amenable to intervention with the goal of reducing variation and health care costs. We conducted a retrospective cross-sectional study of 1,412,340 patient encounters across 18 sites from 2012–2013. We calculated the adjusted hospital-level admission rates using multivariate logistic regression. We adjusted for patient, provider, hospital, and community factors to compare admission rate variation and determine the influence of these characteristics on admission rates. The average adjusted admission rate was 22.9%, ranging from 16.1% (95% confidence interval [CI] 11.5–22%) to 32% (95% CI 26.0–38.8). There were higher odds of hospital admission with advancing age, male sex (odds ratio [OR] 1.20, 95% CI 1.91–1.21), and patients seen by a physician vs. mid-level provider (OR 2.26, 95% CI 2.23–2.30). There were increased odds of admission with rising ED volume, at academic institutions (OR 2.23, 95% CI 2.20–2.26) and at for-profit hospitals (OR 1.15, 95% CI 1.12–1.18). Admission rates were lower in communities with a higher per capita income, a higher rate of uninsured patients, and in more urban hospitals. In communities with the most primary providers, there were lower odds of admission (OR 0.60, 95% CI 0.57–0.68). Variation in hospital-level admission rates is associated with a number of local and community characteristics. However, the presence of persistent variation after adjustment suggests there are other unmeasured variables that also affect admission rates that deserve further study, particularly in an era of cost containment.