Estimated reading time: 1 minute and 45 seconds
By Dillon Twombly, Senior Vice President, Corporate Sales
In today’s world, mass shootings are reported weekly, and they are often more deadly than in the past. For healthcare facilities, preparation for such incidents has never been more crucial. Any mass casualty incident plan must include real-time information so hospitals can respond quickly and efficiently and provide patients with the highest standard of care.
When the unexpected occurs and there is an influx of patients, healthcare facilities’ emergency management teams must have the most up-to-date understanding of the size and scope of the incident to ready resources. They need the right staff in place, the right facilities prepped, and the space made for those injured. This is why they require access to real-time information, and social media, when coupled with artificial intelligence and machine-learning technology, is an essential dataset. Today people post on social media often before taking any other action, making this medium a singular and critical asset to healthcare emergency management professionals because it offers advance knowledge of an incident and context as it progresses.
Alerts delivered from social media can inform emergency management professionals of an unfolding event almost as it occurs, reducing their reliance on traditional and often slower information streams, something that was made clear during the 2017 Las Vegas mass shooting. On October 02, 2017, a gunman opened fire from his hotel room at a country music festival on the Las Vegas strip, killing 59 people and injuring more than 500 others. During such a chaotic incident, it isn’t surprising that the information coming in was wildly disparate.
The staff at the University Medical Center Southern Nevada initially had a hard time grasping the scale of the event. Deborah Kuhls, medical director for UMC’s trauma intensive care unit, told Healthcare Finance News that the extent of the tragedy was initially unclear, explaining that their first notification specified five to 10 patients in route to their trauma center, however a second source said there were 50 to 100 or more patients coming.
Clearly, in cases like this, alerts from social media can help provide a fast and comprehensive understanding. Dataminr detected the event 22 minutes ahead of major news reports. As the shooting progressed, Dataminr alerted on eyewitness accounts of this event, including countless photographs and videos, providing visibility into conditions on the ground. Such details supplied critical insight into the staggering array and volume of injuries, all of which could have enabled healthcare professionals to prepare their resources and manpower within their hospitals., a real-time information discovery company, uses proprietary algorithms and machine-learning technology to discover indications of breaking events in social media and publicly available data. During the mass shooting,
Beyond healthcare emergency management, real-time information also offers hospital security directors a view into events happening in and around their hospitals that may impact security. A nearby fire, a water main break, road closures, or even an active shooter inside the healthcare facility are things likely to be reported on social media. Just like emergency managers, security directors can prepare for impacts stemming from these issues faster with use of this dataset.
Real-time information helps healthcare professionals know more sooner allowing for a higher quality of care and a more streamlined, effective approach to treatment than if they were only relying on traditional communication methods. This demonstrates the benefits of utilizing social media alerts as a key dataset.
When it comes to treating those affected by mass casualty incidents, advantages are few and far between. Therefore, having a real-time understanding of these events is critical because the time to plan is often measured in minutes, and, as emergency management professionals know all too well, minutes can save lives.