Website statistics can predict emergency room visit volumes
A new study from Karolinska Institutet and Södersjukhuset suggests that statistics on website visits may be used to predict the level of demand at emergency departments. The study, which is being published in the journal Annals of Emergency Medicine, shows a significant correlation between Internet searches on a regional medical website and next-day visits to regional emergency departments.
Using Google Analytics, researchers tallied and graphed Internet searches of the Stockholm Health Care Guide (SHCG), a regional medical website, over a one-year period and compared them to emergency department visits over the same period. Visits to the SHCG between the hours of 6:00 p.m. and midnight were significantly correlated to the number of emergency room visits the next day.
The most accurate forecasting for emergency department visits was achieved for the entire county, with an error rate of 4.8 percent. The error rate of forecasting individual hospitals’ emergency department visit rates based on Internet searches ranged from 5.2 percent to 13.1 percent. (An error rate below 10 percent was considered good performance, as this is on par with other methods already described for forecasting emergency room visit volumes.)
The research team behind the finding, conclude that website analytics may be used to predict emergency room visits for a geographic region, as well as for individual hospitals. Looking forward, researchers also suggest that it might be possible to create a model to predict emergency department visits that would enable better matching of personnel scheduling to emergency room volumes.
All co-authors are affiliated to Karolinska Institutet’s Department of Clinical Science and Education, Södersjukhuset (Stockholm South General Hospital). Annals of Emergency Medicine is the peer-reviewed scientific journal for the American College of Emergency Physicians.
Publikation
Forecasting Emergency Department Visits Using Internet Data
Andreas Ekström, Lisa Kurland, Nasim Farrokhnia, Maaret Castrén & Martin Nordberg
Annals of Emergency Medicine, published online as corrected proof on December 4th, 2014, doi: http://dx.doi.org/10.1016/j.annemergmed.2014.10.008