Twitter Can Help Predict Emergency Hospital Visits
Ram and colleagues created a model that was able to successfully predict approximately how many asthma sufferers would visit the emergency room at a large hospital in Dallas on a given day, based on an analysis of data gleaned from electronic medical records, air quality sensors and Twitter.
"We realized that asthma is one of the biggest traffic generators in the emergency department," Ram said.
"Often what happens is that there are not the right people in the ED to treat these patients, or not the right equipment, and that causes a lot of unforeseen problems," she added.
The researchers found that as certain air quality measures worsened, asthma visits to the emergency room went up. Asthma visits also increased as the number of asthma-related tweets went up.
The findings are scheduled to be published in the Journal of Biomedical and Health Informatics.
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