Annals of Emergency Medicine
Volume 49, Issue 6 , Pages 747-755, June 2007

Measuring and Forecasting Emergency Department Crowding in Real Time

  • Nathan R. Hoot, MS

      Affiliations

    • Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
    • Corresponding Author InformationAddress for correspondence: Nathan R. Hoot, MS, 400 Eskind Biomedical Library, 2209 Garland Avenue, Nashville, TN 37232; 615-936-3720, fax 615-936-1427.
  • ,
  • Chuan Zhou, PhD

      Affiliations

    • Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
  • ,
  • Ian Jones, MD

      Affiliations

    • Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
    • Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN.
  • ,
  • Dominik Aronsky, MD, PhD

      Affiliations

    • Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
    • Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN.

Received 30 August 2006; received in revised form 7 November 2006 and 18 December 2006; accepted 4 January 2007. published online 28 March 2007.

Study objective

We quantified the potential for monitoring current and near-future emergency department (ED) crowding by using 4 measures: the Emergency Department Work Index (EDWIN), the National Emergency Department Overcrowding Scale (NEDOCS), the Demand Value of the Real-time Emergency Analysis of Demand Indicators (READI), and the Work Score.

Methods

We calculated the 4 measures at 10-minute intervals during an 8-week study period (June 21, 2006, to August 16, 2006). Ambulance diversion status was the outcome variable for crowding, and occupancy level was the performance baseline measure. We evaluated discriminatory power for current crowding by the area under the receiver operating characteristic curve (AUC). To assess forecasting power, we applied activity monitoring operating characteristic curves, which measure the timeliness of early warnings at various false alarm rates.

Results

We recorded 7,948 observations during the study period. The ED was on ambulance diversion during 30% of the observations. The AUC was 0.81 for the EDWIN, 0.88 for the NEDOCS, 0.65 for the READI Demand Value, 0.90 for the Work Score, and 0.90 for occupancy level. In the activity monitoring operating characteristic analysis, only the occupancy level provided more than an hour of advance warning (median 1 hour 7 minutes) before crowding, with 1 false alarm per week.

Conclusion

The EDWIN, the NEDOCS, and the Work Score monitor current ED crowding with high discriminatory power, although none of them exceeded the performance of occupancy level across the range of operating points. None of the measures provided substantial advance warning before crowding at low rates of false alarms.

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 Supervising editors: Michael J. Schull, MD, MSc; Michael L. Callaham, MDAuthor contributions: NRH and DA conceived the study. All authors contributed substantially to the study design. DA and IJ obtained research funding. NRH implemented the software and collected the data. NRH and CZ performed the statistical analysis. NRH drafted the article, and all authors contributed substantially to its revision. NRH takes responsibility for the paper as a whole.Funding and support: Mr. Hoot was supported by the National Library of Medicine grant LM07450-02 and National Institute of General Medical Studies grant T32 GM07347. The research was also supported by the National Library of Medicine grant R21 LM009002-01.Publication dates: Available online March 27, 2007.Reprints not available from the authors.

PII: S0196-0644(07)00077-7

doi:10.1016/j.annemergmed.2007.01.017

Refers to erratum:

  • Correction

    Annals of Emergency Medicine November 2007 (Vol. 50, Issue 5, Page 534)

Annals of Emergency Medicine
Volume 49, Issue 6 , Pages 747-755, June 2007