Friede Kevin A, Osborne Marc C, Erickson Darin J, Roesler Jon S, Azam Arsalan, Croston J Kevin, McGonigal Michael D, Ney Arthur L
Duke University School of Medicine, Durham, North Carolina, USA.
Minn Med. 2009 Nov;92(11):47-9.
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.
所有医院，尤其是指定的创伤中心，面临的挑战之一是如何确保在一周中的不同日子以及一年中的不同时间有足够的人员配备。一些研究探讨了诸如天气、时间变化、节假日以及吸引大量人群聚集的活动等因素是否有助于预测患者数量。本文研究了天气、大规模人群聚集和日历变量对明尼阿波利斯 - 圣保罗大都市地区三家一级创伤医院每日创伤入院人数的影响。使用自回归积分滑动平均（ARIMA）统计模型，我们发现周末、夏季、少雨和降雪都可预测每日创伤入院人数；节假日和体育赛事等大规模人群聚集活动则不然。该预测模型成功反映了创伤入院模式；然而，其作用有限，因为每日创伤入院人数的预测范围比实际入院人数窄得多。尽管如此，夏季以及全年周六入院人数增加的观察模式在资源规划方面应会有所帮助。
