“We live in the era of Big Data,” said study co-author Sudha Ram, professor at The University of Arizona in the US, referring to increasingly immense sets of information that lends itself well to analysis revealing patterns of human behaviour.
“Our research is innovative and unique because it harnesses the power of Big Data from social media and other sources to address the problem of anticipating emergency department visits for a chronic condition, in this case asthma, in close to real-time conditions,” she noted.
For the study, the researchers collected tweets posted between October 2013 and June 2014 and narrowed them down to the 3,810 that mentioned asthma attacks and that originated in the Dallas-Fort Worth area.
During the same time period, incidences of asthma-related emergency department visits and hospitalisations across the region area were recorded.
When the number of asthma-related tweets increased in a given week, the researchers found, the number of asthma emergency department visits or hospitalisations increased proportionally during the following week.
“If the number of asthma-related tweets increased by 20 in a given week, for example, we would expect asthma-related emergency department visits or hospitalisations to increase by 12 in the following week,” lead researcher Yolande Mfondoum Pengetnze, medical director at Parkland Center for Clinical Innovation (PCCI), a non-profit research and development corporation in Dallas, US, said.
The findings are scheduled to be presented at the ongoing annual meeting of the Pediatric Academic Societies in Baltimore, US.
“This is an important finding that can change the way health departments and other healthcare stakeholders monitor asthma activity in a community,” she said.
“By using real-time Twitter activity, health departments could actually anticipate asthma ED visits or hospitalisations in the following days and possibly intervene before some of them occur,” she explained.