Enabling Rapid Response

Geospatial intelligence proves a powerful tool for paramedics


In the Emergency Operations Center, a dispatcher takes a bystander’s cellphone call about a car crash on a poorly marked rural road. The report prompts the dispatcher to send regional air medics as well as the nearest local ground EMS crew. Next door, EMS managers analyze response statistics for a rapidly growing residential area.

Across town, an EMS crew teaches citizen CPR in a neighborhood with a high cardiac arrest rate. After training, a smartphone app will be integrated with EMS dispatch, so bystander CPR can be started in public spaces before EMS arrives. All of these activities, some long established and others cutting-edge, rely on geospatial intelligence (GEOINT) data and technology to save lives, yield better patient outcomes, and improve agency efficiency.

Early EMS operations used “static deployment,” with a set number of vehicles assigned to permanent stations. In the 1980s, increased call volumes without equal investment in EMS systems led to system status management, which was intended to optimize coverage based on temporal patterns of use.

The advent of computer-aided dispatch and automatic vehicle locator technology allowed dispatchers to determine the closest available ambulance for a call, but it took near real-time analysis and predictive analytics to make the deployment and use of resources truly effective. As economic stresses mandate that services accomplish more with fewer resources, dynamic deployment has become a mainstay in providing efficient and cost-effective coverage.

Dynamic Deployment

“In dynamic deployment, ambulances are directed toward the highest uncovered demand at that moment in time. Some call it ‘chasing the blob,’” said Dale Loberger, an active EMS member and a developer at Bradshaw Consulting Services, which developed the Mobile Area Routing & Vehicle Location Information System (MARVLIS). “Demand is constantly being re-evaluated in near real-time and resources are being matched to that demand as their level of availability changes.”

The MARVLIS system models the probability of future call locations based on historic data, near-real-time inputs such as dispatch and response times, and factors such as traffic conditions. The automated forecast is modeled through Esri’s ArcGIS platform and displayed as a mapping interface. Combined, MARVLIS GPS data, GIS modeling, and wireless communications allow EMS to “have the right units at the right places at the right times,” Loberger said.

The lower response times and decreased distances enabled by systems such as MARVLIS and Optima Predict from Intermedix help save lives in the subset of patients that must be reached in four minutes or less to survive. Jersey City Medical Center EMS doubled its return of spontaneous circulation rate in cardiac arrest victims after integrating MARVLIS into its operations in 2012.

A University of Pittsburgh team modeled fatal vehicle crash rates in Pennsylvania from 2013-2014 and distances from trauma resources using Fatality Analysis Reporting System data. They discovered a theoretical 12.3 percent decrease in mortality if two medevac units were to be reassigned to the higher-incidence areas.

“There was a big disparity for these patients, depending on where they live,” said Joshua Brown, a general surgical resident at the university medical center and lead investigator on the study. “It’s only recently that trauma systems analysts have begun to incorporate GIS tools into their work to achieve improved outcomes. That we could potentially reduce mortality by relocating only two helicopter units was a very powerful finding.”

Community Engagement

Focusing resources strategically to improve patient outcomes involves more than ambulance placement. According to the American Heart Association, more than 350,000 out-of-hospital cardiac arrests occur in the United States each year. Only 5.5 percent of these victims survive to hospital discharge. Improving survival rates from sudden cardiac arrest is a holy grail among the EMS profession, and providers are combining geo-location data, GIS modeling, and smartphone apps in this quest.

In Mississippi, American Medical Response analyzed new data for geospatial patterns, looking for hotspots associated with neighborhood type, rural versus urban patterns, and similar factors. In the Jackson metropolitan area, they discovered an association between citizen CPR/Automated External Defibrillator (AED) training and bystander CPR rates in certain neighborhoods. Since bystander CPR/AED use can double or triple the chances of surviving cardiac arrest, AMR increased outreach training to the areas with high arrest and low training rates. Improved bystander CPR and increased survival rates followed.

PulsePoint AED is a crowdsourcing app that allows users to report the location of AEDs in their community. (Image credit: PulsePoint)

“So much can happen during the critical minutes of an emergency,” explained Michael Arinder, M.D., director of clinical services for the south region with American Medical Response. “We recognized that we had the ability to see what happens in the moments before the arrival of trained personnel and we decided to use that to better serve the community. We knew that if it saved only one additional life, it was worth it.”

This focus on bystander CPR/AED inspired PulsePoint to create a smartphone app suite to bring citizen rescuers to the cardiac arrest victim. The PulsePoint Respond app sounds an alert when a cardiac arrest occurs in a public place. Users in the agency-defined notification area will see the victim’s location on a map. PulsePoint Respond incorporates data from PulsePoint AED, a crowdsourcing app that allows users to report the location of AEDs in their community. The AED location data is made available in PulsePoint Respond after being verified by local authorities. 

“PulsePoint is the marriage between technology and citizen engagement,” said PulsePoint spokesperson Shannon Smith.

To date, PulsePoint Respond has been activated more than 20,000 times and has more than 59,000 users.

911 for the Next Generation

Crowdsourced traffic information is another valuable geospatial tool that can benefit the EMS community. Genesis PULSE, a vehicular tracking system used for dynamic deployment, exchanges data on road closures and traffic conditions with navigation app Waze.

Data after the first year of information exchange revealed that in 62 percent of cases Waze obtained accident notification up to 4.5 minutes faster than 911 centers. Although the implications are unsettling, Waze data provides PULSE users an advantage in rapid deployment—if, as in all GEOINT use cases, the data is accurate.

All geospatial data requires accuracy to be useful, but in public safety, accuracy can make the difference between life and death. Leaders in the field consider this a primary public safety challenge.

“Geographic Information Systems, when coupled with first-responder missions, private industry, and public policy can improve operational understanding and help PSAPs (public safety answering points) create and maintain reliable, dispatchable address databases,” said Mike King, emergency call-taking and dispatch industry manager for Esri as well as a member of the National Emergency Number Association. “All three disciplines are necessary for true success.”

The Next Generation 911 (NG911) initiative, spearheaded by U.S. Department of Transportation, seeks to design an emergency communications architecture that will transcend current limitations. Wireless mobile devices, Voice over Internet Protocol telephoning, and other modern technologies have rendered the 911 call center system outmoded.

According to King, core GIS capabilities, wireless and broadband use, and 3D routing technology, particularly for indoors, will be incorporated into NG911, but the parameters and solutions are evolving with the initiative.

Startup RapidSOS hopes to end geo-location fuzziness with a database that seamlessly integrates with 911 call centers. A cellphone call to 911 will ping the RapidSOS database, and geolocation information will be supplied to the 911 center. In trials, RapidSOS provided more accurate geo-location information than the wireless carriers tested.

EMS relies increasingly on GEOINT to provide effective healthcare.

In the coming years, the technology will continue to evolve with the proliferation of predictive artificial intelligence and machine learning algorithms, according to Nikiah Nudell, chief data officer for The Paramedic Foundation and a board member of the National EMS Management Association.

“Geospatial intelligence has become a powerful worldwide tool for paramedic chiefs and the public health and safety officials they often work with,” Nudell said. “In an environment where limited resources are being used to respond to dynamic critical incidents, having full situational awareness from an historic and real-time perspective is powerful.”

Featured image: The MARVLIS system models the probability of future emergency call locations based on historic data, near-real-time inputs such as dispatch and response times, and factors such as traffic conditions. (Credit: Esri)


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