Tag Archives: geovalidation

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” travel impedances (the actual time it takes to travel a certain road segment in a specific direction given the current time of day based on your own past experience) and even access known road closures due to ongoing accidents or scheduled construction to provide realistic travel times and routes given current conditions.  The database can also be used to locate not just the closest vehicle, but make unit recommendations based on additional criteria such as special equipment or training.  When these interactive maps are used with ruggized touch-screen computers or new tablet devices, you have a powerful combination that can also support ePCR charting or other applications.

When a fleet of ambulances can provide positional and status information to the call center, the dispatchers have a better situational awareness of the functioning system in real time.  Then by using additional GIS functionality to map previous incidents, a “hotspot” map (a map showing the areas of highest likeliness for generating a call) can be created to forecast future demand using simple predictive analytics.  In the past, some organizations have poorly implemented a form of System Status Management (SSM) that failed to meet the objective of increasing efficiency and left many paramedics soured on the idea of post moves.  Effective implementations (some highlighted in past blogs here) have shown that Jack Stout’s idea can be properly done in almost any system using modern technology.  Moreover, by positioning ambulances closer to their next call, not only is response time reduced but the incentive to be hasty in that response is also reduced leading to less risk in travel.

Beyond these daily tactical applications of GIS, there are many potential strategic ones.  Preventing a call is better than an emergency response at any speed.  By looking beyond just the calls for service in the coming hour, we can begin to look further into the future and recognize specific risks of target lifestyle groups.  Preventive care or community wellness programs can be directed at the most vulnerable populations to maximize the investment of such a program.  Locating groups with increased potential for cardiac problems can aid in locating a blood pressure screening event as one example.  Some agencies have turned to GIS to help them find new recruits or volunteers.  I encourage you to communicate with your local GIS staff and let them know how they can help you.  After all, assisting you to become more efficient helps them show value as well.  You do not need to know the details behind the analytical tools, it is your existing knowledge of the community and its needs that will help your GIS staff address them.  If you lack those resources locally, or have specific questions, please make a comment below and I will follow up with you directly.

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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.

The ability of the GIS to translate addresses into coordinates in order to determine the closest responder (or the reverse process of turning an incident location into an address to communicate that location) is based on the quality of the geographic street database and its attributes.   Some US counties create their own data, but many others use street data from national level providers including the US Census Bureau who provides free TIGER/Line files and commercial sources such as TomTom (formerly TeleAtlas) or NAVTEQ as a foundation.

The accuracy of the street centerline shape for any segment of road allows a coordinate to be located precisely along the correct street and the address range attributes allow a position to be accurately described with an address.  So to make this all work, the centerline shape of your data must reflect the actual shape of the road on the ground and be segmented (typically broken at street intersections) to allow address ranges to be defined over limited distances.  These attributes typically include left-from-address, left-to-address, right-from-address, right-to-address (relative to the increasing direction of the numbers), prefix or direction, street name, street type, and suffix or direction for each segment of street at a minimum.  This all sounds very easy, but the real world always gets more complicated than our simple schemes.

According to David Hunt, GIS Analyst and 911 Coordinator for Wake County in North Carolina, “the whole country has been actively converting [rural] route and box numbers to addresses over the last 25 years,” but the process has not always been consistent.  The distance between addresses was not always uniform before the general availability of GIS for addressing.  Good centerlines make the address assignment process much easier for new subdivisions using GIS, but reflecting current addresses in an automated fashion is still not always straightforward.

Consider the following example from an older part of town where the house numbers are sequential based on structures rather than an increment distance as is more common in modern neighborhoods.  The house in the center is 502 and the structure next door to the east is 504 followed by 506 at the end of the street.  The structure on the west side of the middle house is 402 since there used to be an alley (but which is now closed) between those properties.  The next structure further west is on a corner and numbered 400.

So technically this street segment includes the 400 AND 500 blocks of this street.  The “right-from-address” would clearly be 400, but what is the “right-to-address”? Since the next block starts at 600, it could logically be either 506 or 598.  What is the difference?  Well, the greater ending value allows for more possible matches of any addresses searched but also provides approximation of non-existent addresses in a reverse-geocoding process. If a point query returned an address communicated as “410 S Washington St”?  Would it be located just 5% along the length of this street putting it at the actual structure numbered 400 or is there something between the structures at 402 and 502 that we need rescuers to find?   The smaller ending value limits some of the possible addresses and would not allow a possible match for a search on a non-existent house number like 510.  However, unless the segment is broken between 402 and 502, as it once was in reality, it would return an estimated coordinate for a query on a fictitious 404 instead of suggesting an entry error.

Another way around the problem is point-based addressing with GIS as managed in Sumter County, SC which limits queries to only actual house numbers in the geovalidation process.  Instead of applying the range attributes to the graphic representations of the centerlines, points are entered for each structure.  This also simplifies the problem with addressing mobile homes which need to change address as the actual dwelling is relocated.  “Making the digital address points more easily accessible helps create less issues,” says Emily Banar, GIS Analyst for Sumter County in charge of addressing.

Individual geocoding services provided through the GIS, named “locator services” by Esri, can be combined as “composite locator services”.  A composite geocoding search  is one that uses more than one single locator in order to attempt to match all possible addresses against more than one geographic dataset.  Combining search methods can provide more reliable geovalidation for your High Performance EMS by using a point range before a street range.

TheAddresser™ is an application built for both ArcGIS Desktop and ArcGIS Server by BCS as a complete address management system for both street ranging and single point addressing.  Business rules are built-in to the application logic to manage overlapping ranges, out-of-range addresses, as well as others to ensure that street centerline ranging and single point addresses stay in sync with each other and address accuracy is maintained.  This system also includes street name management and reporting of existing address errors.  Other tools of this system aid in the ease of editing street centerlines and address points to make sure that your GIS-based geovalidation process works as it should.

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