Earlier this month I read an article about researchers who combined tweets about asthma with data taken from air-quality sensors and electronic health records to predict, with 75% accuracy, the number of asthma-related visits that day.
In Pasadena, when the smog was thick and low up against the San Gabriel Mountains, we knew to expect an increase in upper respiratory symptoms, but we didn't have data to help with resource planning. However, air quality just isn't that obvious in some communities or during particular seasons. In this example, the application of technology will certainly help improve effectiveness.
There are other examples of the power of social media and usefulness for health surveillance and predicting outcomes. In June, I'll be presenting at the TeamSTEPPS Annual Conference and will share the story of another social surveillance application. This one is using social media to augment traditional surveillance methods to improve knowledge of complications among hypoglycemia in diabetics and impact behaviors.
This is only the beginning... stay tuned for much more!