Johns Hopkins launches emergency preparedness web apps

By Aditi Pai
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Surge JHJohns Hopkins National Center for the Study of Preparedness and Catastrophic Event Response (PACER) has launched two new web apps and updated a third to help hospital first responders and hospital planners prepare for emergency situations.

The two new apps are Flucast and Surge. Johns Hopkins made the third, EMCAPS, a downloadable program meant for first-responder training and hospital disaster planning, into a web app.

Flucast uses Google Flu Trends data in the hospital's location combined with the a history of flu trends data to forecast the current week's flu cases. If the hospital is too far away from a major metropolitan area, the application pulls from statewide Google flu trends data.

The process for collecting the providing this data came from a study published in Clinical Infectious Diseases. The study found that city-level Google flu trends had a strong correlation with influenza cases and inner-city emergency department visits, which validated its use as an emergency department surveillance tool. Google Flu Trends correlated with several pediatric emergency department crowding measures as well.

Surge helps show hospital administrators and public health officials what capacity in a hospital may look like if there is a disaster. The app offers users a simulation of the number of arrivals and discharges, predicts the number of beds that might be occupied and allows the user to simulate different strategies to see what these methods might do to change the number of patients in the hospital. Some strategies might include increasing the number of beds in the hospital or determining the priority of the patient's treatment based on the severity of their condition at beginning of the disaster.

PACER is developing the apps with the help of a $6.5 million grant from the Department of Homeland Security (DHS), that the department donated in 2010.

"We know that one of DHS' priorities is tools that people in the field can actually use to improve nation's preparedness," PACER Associate Director Lauren Sauer told MobiHealthNews. "So a lot of our work has been in the planning phases of these applications, but really what we wanted to ultimately do is make a tool that people in this arena can use to better plan, to better prepare, to make the disaster situation safer."

So far, EMCAPS 1.0 version has been used by Texas A&M, FEMA Region 1, various state health and emergency planning departments such as Washington State and Oregon. Because EMCAPS 1.0 had no registration procedure, PACER got very little feedback from users, although Sauer said hundreds of copies had been downloaded. The new web apps will all have a feedback form, which PACER will use to learn more about how well their products work in the hospitals and collect aggregate data about general trends.

While the apps are free, Sauer said Johns Hopkins and other hospitals would benefit when hospitals use the tool and learn how to be better prepared for a disaster. Sauer expects adoption to increase after a meeting they are having with DHS next week, which will be broadcast nationally among first responder and hospital response groups.

Because the suite of apps are meant to be used as planning tools, rather than in the field response tools, Sauer thought it was important that the first generation of apps should be on the web.

"It's easier to import data at a computer instead of a tablet or a smartphone, especially the flu and Surge apps," Sauer said. "We are looking at building tablet or phone apps in the second generation of the apps suite. It's definitely high on our priority list, but we felt like we wanted to put the most informational, user friendly version out there first to get people comfortable with the interface to build a relationship with our potential users and make sure that as many people have access to this as possible."

Another department within Johns Hopkins recently developed a tweet-screening method that delivers near real-time data on flu cases and filters out tweets unrelated to actual flu infections. Their method is based on analysis of 5,000 publicly available tweets per minute, which the Johns Hopkins researchers say track closely with government disease data that takes much longer to compile.