TY - JOUR
T1 - Predicting trauma admissions
T2 - the effect of weather, weekday, and other variables.
AU - Friede, Kevin A.
AU - Osborne, Marc C.
AU - Erickson, Darin J.
AU - Roesler, Jon S.
AU - Azam, Arsalan
AU - Croston, J. Kevin
AU - McGonigal, Michael D.
AU - Ney, Arthur L.
PY - 2009/11
Y1 - 2009/11
N2 - One of the challenges all hospitals, especially designated trauma centers, face is how to make sure they have adequate staffing on various days of the week and at various times of the year. A number of studies have explored whether factors such as weather, temporal variation, holidays, and events that draw mass gatherings may be useful for predicting patient volume. This article looks at the effects of weather, mass gatherings, and calendar variables on daily trauma admissions at the three Level I trauma hospitals in the Minneapolis-St. Paul metropolitan area. Using ARIMA statistical modeling, we found that weekends, summer, lack of rain, and snowfall were all predictive of daily trauma admissions; holidays and mass gatherings such as sporting events were not. The forecasting model was successful in reflecting the pattern of trauma admissions; however, it's usefulness was limited in that the predicted range of daily trauma admissions was much narrower than the observed number of admissions. Nonetheless, the observed pattern of increased admission in the summer months and year-round on Saturdays should be helpful in resource planning.
AB - One of the challenges all hospitals, especially designated trauma centers, face is how to make sure they have adequate staffing on various days of the week and at various times of the year. A number of studies have explored whether factors such as weather, temporal variation, holidays, and events that draw mass gatherings may be useful for predicting patient volume. This article looks at the effects of weather, mass gatherings, and calendar variables on daily trauma admissions at the three Level I trauma hospitals in the Minneapolis-St. Paul metropolitan area. Using ARIMA statistical modeling, we found that weekends, summer, lack of rain, and snowfall were all predictive of daily trauma admissions; holidays and mass gatherings such as sporting events were not. The forecasting model was successful in reflecting the pattern of trauma admissions; however, it's usefulness was limited in that the predicted range of daily trauma admissions was much narrower than the observed number of admissions. Nonetheless, the observed pattern of increased admission in the summer months and year-round on Saturdays should be helpful in resource planning.
UR - https://www.scopus.com/pages/publications/77449118039
UR - https://www.scopus.com/pages/publications/77449118039#tab=citedBy
M3 - Article
C2 - 20069999
AN - SCOPUS:77449118039
SN - 0026-556X
VL - 92
SP - 47
EP - 49
JO - Minnesota medicine
JF - Minnesota medicine
IS - 11
ER -