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EMS in the Cloud

According to the Gartner Hype Cycle for 2010, “Cloud Computing” and “Cloud/Web Platforms” have reached the infamous “Peak of Inflated Expectations” and are already sliding down like a fog into the unavoidable “Trough of Disillusionment”.  But the story doesn’t end there as the cloud is expected to rise back upward and eventually reach the ultimate “Plateau of Productivity” within the next 2 to 5 years.  What does this mean for EMS?  Well, first, it means that there is probably still plenty of confusion about what the “cloud” actually refers to and its waning excitement at the moment means the enthusiasm of its promoters is more easily dismissed as the ramblings of zealots “with their heads simply stuck in the cloud.”   However, it is the critical review and appropriate response to technology offerings in just this state that separates the industry leaders from the rest of the pack.

Notice that I did not say the “full adoption” of a new technology, but rather the “appropriate response” to its availability.  As you will see in this post, my forecast of cloud computing is that tomorrow will only be “partly cloudy”.


According to Wikipedia,  ”cloud computing describes a new supplement, consumption, and delivery model for IT services based on Internet protocols” (IP).  This means that the cloud really becomes just another computing resource similar to existing enterprise servers except that these cloud-based resources are physically located (and maintained) somewhere else in the world and access is typically provided on a subscription basis that allows them to “scale” (increase or (more…)

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3 comments Posted by on November 7, 2011

GIS for EMS

Both acronyms (GIS and EMS) represent not just technologies, but fields of study and service that have very old roots even though each can trace their modern form to research starting in the 1960s.  Both have witnessed explosive growth and application far beyond their original vision.  But most importantly, these two names definitely belong together.

Those who have any knowledge of Geographic Information Systems (GIS) will often think first of maps at the mention of its name.  Maps, however, are simply the form GIS professionals use to express the actual work done with a GIS.  That work consists of maintaining a descriptive spatial database and using that database to perform analysis that answers real-world questions or solves domain specific problems.  There are many examples of how it can be applied, but here we will discuss just those in support of Emergency Medical Services (EMS).

At the very simplest end of the spectrum is printed mapbook production.  Because GIS “maps” are stored as data rather than graphics, they are easily edited and symbolized in different ways to meet different objectives.  For use in ambulances, maps should be quick references primarily showing roads (with street names and block addresses) and landmarks essential for navigation.  Street index creation is an automated function of the GIS that can make a printed book of maps more useful for crews attempting to find a specific street.  Better still is an interactive map – one that can locate your current position using GPS and can automatically search an address (a process called “geocoding” or “geovalidation“) and recommend an efficient route between these two points.  This function is manual in printed form but interactively can leverage historic “time-aware” (more…)

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3 comments Posted by on October 13, 2011

Dynamic System Status Management

System Status Management (SSM) is the fluid deployment of ambulances based on the hour-of-the-day and day-of-the-week in order to match supply, defined as Unit Hours of Utilization (UHU), with expected demand, expressed as calls for service, in the attempt to provide faster response by locating ambulances at “posts” nearer their next calls.  While the practice is still not unanimously embraced by all services, it has a sound foundation both in the research literature dating back to the 1980′s as well as in practice today.  Experience has shown that ambulance response times can be dramatically decreased using this type of dynamic deployment, but it is also recognized that it is possible to reduce performance when these techniques are not applied properly.  The direction of the results of a system implementation are typically influenced by the system design, competence of the managers creating the plan, and commitment of the workforce in implementing it.  Therefore the best practice is a simple and straightforward implementation that will show positive results quickly.  This methodology ensures a positive return on investment along with garnering the necessary buy-in from staff to make the project a success.

In his article, “System Status Management – The Fact is, It’s Everywhere“,  published in the Journal of EMS (JEMS) magazine back in 1989, Jack Stout explained the concept of SSM and tried to dispel certain myths.  Based on foreseen Geographic Information System (GIS) technology and even general computing capabilities of that time, it was quite logical to assume in his Myth #2 that “no matter how thoroughly the response zone concept is fine-tuned in practice, it cannot be made to cope effectively with the dynamic realties of the EMS environment.”  But systems implemented today around the US are capable of calculating dynamic response zones in a small fraction of a second while even being based on time-aware historic driving patterns making a truly dynamic system status management process a reality.  A practical and proven example of a dynamically functioning system status management application is the Mobile Area Vehicle Routing and Location Information System, or simply MARVLIS.

The following Slideshare presentation does an excellent job of telling the story of why and how the system works:

High Performance EMS is MARVLIS[slideshare id=8765718&w=425&h=355&sc=no]

View more presentations from hp_ems

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7 comments Posted by on August 8, 2011

Addressing Geovalidation

The most fundamental aspect of an E-911 emergency dispatch center is to be able to locate a call for service and communicate that location to the closest appropriate vehicle to be dispatched.  In nearly every case, that location description is eventually an address.  The back-end process starts when a call is placed to 9-1-1 from a traditional wired land-line and its Automatic Number Identification (ANI) is compared to phone company records to find the Automatic Location Identification (ALI) address which is then compared to the Master Street Address Guide (MSAG) database to determine which Public Safety Answering Point (PSAP) or “call center” will receive that call.  It is the dispatcher at the PSAP who will determine the required resources and ultimately dispatch the requested assistance.  For cellular phones, VOIP, or telematics, the process is a little more complex to return a current latitude/longitude coordinate rather than a pre-determined address.  In those cases, the PSAP will interpret the caller position to a nearest address using Geographic Information System (GIS) technology.  The process of turning an address into a latitude/longitude value is called “geocoding” by GIS people and “geovalidation” by EMS staff.  The inverse of that process, finding the address of a specified point, is preceded with the term “reverse” by either crowd.  So, regardless of how the location information is presented to the PSAP, the closest resources can be found by comparing points and, in return, an understandable location descriptor can be provided for any point – at least in theory.

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1 comment Posted by on June 21, 2011

Trading GPS Navigation for Wireless 4G Access

LightSquared, a hedge fund-backed start-up viewed as a major enabler of wireless competition in the US, was granted control over a portion of the US spectrum by the Federal Communications Commission (FCC) in order to build and wholesale 4G-LTE wireless broadband service through a nationwide network.  According to their own website, “LightSquared will unleash the boundless opportunity of wireless broadband connectivity for all.”   But unfortunately this presumed advantage comes at a serious known cost for popular navigation systems used by aviation and first responders.

During initial tests of the network conducted last month, there was significant interference with the Global Positioning System (GPS) receivers used by ambulances and state patrol.  These tests were conducted at Holloman Air Force Base in New Mexico where both sets of first responders experienced outages due to the LightSquared cell towers.  Bill Range, Director of the state E911 program, stated in a letter that the results of the April tests, “substantiate concerns that the LightSquared network will cause interference to GPS signals and jeopardize 911 and public safety nationwide.”

The problem is that the LightSquared system operates using bands between 1525-1559 MHz and 1626.5-1660.5 MHz while GPS signals (more…)

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11 comments Posted by on May 23, 2011

The Future of Prediction

I have read the positions stating that calls for emergency services are completely random (justifying the reason they are often called “accidents”) and therefore not able to be predicted.  But both academic literature and practical experience show that demand prediction can be an effective tool in helping to balance scarce resources (ambulances and their trained crews) with public demand (requests for emergency responses even without taking into account the abuses to the system as discussed in a previous posting on the problem of “frequent flyers”) while still improving response times and controlling costs.

For anyone who thinks all of this sounds too good to be true, there are examples of where expensive technology is not having the desired affect.  One such location is Lee County EMS in Florida where not only have response times not been improved, but ambulances are burning more fuel than ever and the critics include the very paramedics it is supposed to help.  While predicting where the next 911 call will come from may be similiar to ”picking the winning card at a casino” as the Florida investigative news reporter suggests, that isn’t really the objective.  We don’t need to know which phone will make the next call, it is enough just knowing the probability of a call coming from any given location within the service area.  This may be a subtle distinction, but one that makes a huge difference at MedStar in Fort Worth or Life EMS in Grand Rapids where response times were dramatically improved by taking the next step beyond simple demand prediction and placing ambulances at positions where they can be the most effective.

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1 comment Posted by on March 1, 2011