Twitter can Help predict Emergency Hospital visits

Posted By: Gizbot Bureau

    Twitter can help several hospitals plan better in terms of tackling patient rush and availability of resources and staff, suggests a study.

    Twitter can Help predict Emergency Hospital visits

    The researchers said personal health-related tweets posted by some users could be helpful for hospitals.

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    "You can get a lot of interesting insights from social media that you can't from electronic health records," said lead author professor Sudha Ram from the University of Arizona.

    "You only go to the doctor once in a while, and you don't always tell your doctor how much you've been exercising or what you've been eating."

    "But people share that information all the time on social media. We think that prediction models like this can be very useful, if we can combine various types of data, to address chronic diseases," she explained.

    Twitter can Help predict Emergency Hospital visits

    The researchers looked specifically at the chronic condition of asthma and how asthma-related tweets, analysed alongside other data, can help predict asthma-related emergency room visits.

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    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 realised that asthma is one of the biggest traffic generators in the emergency department," Ram said.

    Twitter can Help predict Emergency Hospital visits

    "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.

    Source: IANS

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