• Ann Emerg Med · Dec 1998

    VESAS: a solution to seasonal fluctuations in emergency department census.

    • K N Shaw and J M Lavelle.
    • Division of Emergency Medicine, Children's Hospital of Philadelphia and University of Pennsylvania School of Medicine, Philadelphia, USA. shaw@email.chop.edu
    • Ann Emerg Med. 1998 Dec 1;32(6):698-702.

    Study ObjectiveTo design and implement a plan for emergency department staffing and additional space to reduce waiting time and the rate of patients leaving without being seen during the viral epidemic season.MethodsThe study was conducted in the ED of a tertiary care children's hospital. We compared 24,657 children who presented for care between November 1996 and March 1997 (VESAS plan enacted) with 24,012 children who presented for care during the same period in the preceding year. VESAS (Viral Epidemic Supplemental Attending and Staff), an additional team of personnel, was on call for the viral epidemic season and was called to work if the hourly ED census that day was 25% or more of the past year's average hourly patient volume. Extra examination rooms were made available in space contiguous to the ED. Interval data, "left without being seen" rates, and ED census were monitored and compared with the previous year's data.ResultsThe VESAS team was used for 32% of the days during the 4-month intervention period. The left-without-being-seen rate was reduced by 37% (95% confidence interval, 33% to 41%). The average time from arrival to consultation with a physician was decreased by 15 minutes (95% confidence interval, -10 to -20) for all patients. Waiting times were most markedly reduced for less acutely ill or injured patients, although a modest decrease was also observed in patients with more severe illnesses or injuries (-10 minutes). The percentage of lesser-severity patients seen in an urgent care area was increased from 35% to 51%.ConclusionVESAS, a plan for providing space and personnel to handle an increased volume of patients that can be activated on the basis of hourly census data, was successful as judged by waiting times and percentage of patients who left without being seen.

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