title: Use of calendar and weather data to predict walk-in attendance.
abstract: Hospital emergency rooms frequently provide routine health care to inner-city residents. Operating costs for such "walk-in" services might be reduced if staffing levels could be tailored to patient flow. To determine how calendar and meteorological factors affect attendance, we matched the daily visit records of a large ambulatory care center with concurrent calendar and weather data. Stepwise regression analysis resulted in a predictive equation that allows the projection of future attendance. In our facility, patient flow peaked on Monday and declined steadily during the remainder of the week. Fewer visits occurred during autumn and winter than during summer months. Higher temperatures were associated with more visits and daytime rainfall and glaze with fewer, once calendar variables were accounted for. The prediction equation has its greatest usefulness in projecting trends in walk-in attendance. Staffing levels can be adjusted to the predicted patient flow, allowing more cost-efficient operation.
mesh_terms: D003151:Community Health Centers / Q000706:statistics & numerical data*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005544:Forecasting; D006801:Humans; D012621:Seasons; D013997:Time Factors; D014887:Weather