Predicting patient visits to an urgent care clinic using calendar variables

  • Batal H
  • Tench J
  • McMillan S
 et al. 
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OBJECTIVE: To develop a prediction equation for the number of patients seeking urgent care. METHODS: In the first phase, daily patient volume from February 1998 to January 1999 was matched with calendar and weather variables, and stepwise linear regression analysis was performed. This model was used to match staffing to patient volume. The effects were measured through patient complaint and "left without being seen" rates. The second phase was undertaken to develop a model to account for the continual yearly increase in patient volume. For this phase daily patient volume from February 1998 to April 2000 was used; the patient volume from May 2000 to July 2000 was used as a validation set. RESULTS: First-phase prediction equation was: daily patient volume = 66.2 + 11.1 January + 4.56 winter + 47.2 Monday + 37.3 Tuesday + 35.6 Wednesday + 28.2 Thursday + 24.2 Friday + 7.96 Saturday + 10.1 day after a holiday. This equation accounted for 75.2% of daily patient volume (p

Author-supplied keywords

  • Forecasting
  • Regression analysis
  • Utilization
  • Walk-in clinics

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  • H. Batal

  • J. Tench

  • S. McMillan

  • J. Adams

  • P. S. Mehler

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