Forecasting Emergency Department Visits Using Internet Data - 07/04/15
Abstract |
Study objective |
Using Internet data to forecast emergency department (ED) visits might enable a model that reflects behavioral trends and thereby be a valid tool for health care providers with which to allocate resources and prevent crowding. The aim of this study is to investigate whether Web site visits to a regional medical Web site, the Stockholm Health Care Guide, a proxy for the general public’s concern of their health, could be used to predict the ED attendance for the coming day.
Methods |
In a retrospective, observational, cross-sectional study, a model for forecasting the daily number of ED visits was derived and validated. The model was derived through regression analysis, using visits to the Stockholm Health Care Guide Web site between 6 pm and midnight and day of the week as independent variables. Web site visits were measured with Google Analytics. The number of visits to the ED within the region was retrieved from the Stockholm County Council administrative database. All types of ED visits (including adult, pediatric, and gynecologic) were included. The period of August 13, 2011, to August 12, 2012, was used as a training set for the model. The hourly variation of visits was analyzed for both Web site and the ED visits to determine the interval of hours to be used for the prediction. The model was validated with mean absolute percentage error for August 13, 2012, to October 31, 2012.
Results |
The correlation between the number of Web site visits between 6 pm and midnight and ED visits the coming day was significant (r=0.77; P<.001). The best forecasting results for ED visits were achieved for the entire county, with a mean absolute percentage error of 4.8%. The result for the individual hospitals ranged between mean absolute percentage error 5.2% and 13.1%.
Conclusion |
Web site visits may be used in this fashion to predict attendance to the ED. The model works both for the entire region and for individual hospitals. The possibility of using Internet data to predict ED visits is promising.
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| Please see page 437 for the Editor’s Capsule Summary of this article. |
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| Supervising editors: Daniel A. Handel, MD, MPH; Judd E. Hollander, MD |
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| Author contributions: AE and MN conceived the study, undertook recruitment of participating centers, and managed the data. MC obtained research funding. AE drafted the article, and all authors contributed substantially to its revision. MN takes responsibility for the paper as a whole. |
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| Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org/). The authors have stated that no such relationships exist. |
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| A podcast for this article is available at www.annemergmed.com. |
Vol 65 - N° 4
P. 436 - avril 2015 Retour au numéro
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