Category Archives: Firefighting Operations

Dynamic Risk for Intelligent Fire Move-Ups

Planning for the placement and staffing of fire apparatus, either in a fixed location or for a temporary move-up position, involves the comparative evaluation of community risk for each alternative. Unfortunately, our typical understanding of risk is skewed and outdated. Basing operational decisions on inadequate data leads to choices that can be inefficient, ineffective and legally indefensible.

Of course, there are many factors that combine to influence the danger of a fire response. There must be some estimate of fuel load along with the exposures and barriers to a potential fire spread. For the most part, existing studies get this right – even if only rudimentarily. But it is the most significant single impact on fire frequency that is modeled the poorest. Kasischke and Turetsky stated in 2006 that “(people) are the dominant source of ignitions except in sparsely populated regions.” Our troubled standard for measuring population is the decennial US census. Prior to the twenty-first century, these federal statistics were clearly the most consistent available figures that were widely accessible.

Census population data, which is often the basis of many comprehensive fire plans, have several logical failures for their use in local community risk evaluation. The first problem is the age of the data. The census is taken only every ten years and the values of intervening years are estimated through algorithms. At this present point in time, the 2010 population estimates have been statistically massaged for the past 7 years. Add to that, the fact that the census only counts “night-time” populations by estimating where individuals “live” (or spend the majority of their sleeping time) rather than accounting for their patterns of movement outside of the home. The time away from their census-defined abode can often be the better part of each 24 hour period, yet the nineteenth century agrarian idea of home is the value most studies use to consider the number of humans at risk in an area. Still another major problem is the aggregation level of these population estimates. The census ‘block group‘ is the smallest numerical unit that the US Census Bureau reports to the public. By definition, the block group typically consists of a neighborhood of between 600 and 3,000 individuals where estimates of its values are extrapolated through reports from a representative fraction of the area. Finally, in a 2015 study on population density modelling in support of disaster risk assessment, the authors conclude that “block groups are not fine enough to be suitable for specific hazard analysis.” While many planners attempt to break down these manipulated night-time population estimates by factoring a simple percentage of an area, there is no statistical support for such assumptions. In fact, the foundation of the referenced work by Tenerelli, et. al. describes specific ‘downscaling techniques’ using intensive proxy attributes to give clues for any justifiable disaggregation of coarse population statistics. Most of these techniques are far more involved than percentages and have value only when no other population measure is present.

Today, the near real-time visualization of population surges that quantify the urban influxes at the start of the work day and their subsequent retreat into suburbia for the evening are becoming a reality. Dynamic population movement can now be mapped using anonymized mobile phone data. According to a 2017 Pew Research Center Fact Sheet, it is estimated that “95% of Americans own a cell phone of some kind” (and well over 75% have devices that are classified as “smartphones”.) Since every one of these devices must regularly ‘ping’ a tower in the cellular network, these signals open bold new opportunities for tracking, visualizing and even analyzing population movement forming an important layer in the dynamic risk of any community with a fidelity far greater than the census block group.

Generic population measures are a great start, but not all people are similar when factoring risk. Some populations are more vulnerable than others. Families that live in flood zones, for instance, have a greater exposure for both life and property loss during heavy rain events. Those who live in large housing complexes with limited egress may also be unfairly disadvantaged during a significant event that requires evacuation. Socioeconomic factors can also limit access to current information or an individual’s ability to react to it. Beyond raw numbers of bodies, we must be able to classify groupings of individuals and label their vulnerability.

There are many other sensors in a community that can also be leveraged in modelling the dynamic nature of risk. The risk for flooding is dependent on a source of water input. Rain gauges within your watershed can define the amount of water added over a measure of time. Stream gauges measure the depth of water in a channel and can inform you of the likelihood of imminent flooding. Increasingly, these sensors are becoming part of the Internet of Things (IoT) that allow remote access of real-time data. Even layers of data that are often considered to be static can have variability capable of being modeled. A school, for instance, is usually categorized as a ‘high risk’ asset, but is it always at the same risk level? The actual risk experienced is far lower during summer months or on weekend evenings. Conversely, its risk status may go even higher than normal on certain Friday evenings when the home team is playing a championship game and entire families gather in addition to the normal student population. Similar to pre-plan floor layouts or construction analysis, the use patterns of a building can be noted and input to a dynamic risk model. The increased effort of data collection should be more than repaid by the acute knowledge gained for steering protection decisions.

The reason we do not make more effort to realistically model the threat to our communities is not because it is difficult, but because we simply have never done it that way before. The technology to visualize changing demand and automate recommendations for responding to it has long been proven in the EMS world. The rebuttal is often that the fire service is different. However, simple modifications of existing software provide mobile access to risk as a spatial surface of probability on a user-selected basemap of imagery, topography, or cadastre for incident management or support in apparatus move-up decisions. Modification of the dispatch software to recommend not just the closest ambulance but the most appropriate response package of apparatus based on incident reporting is also being made. The Mobile Area Routing and Vehicle Location Information System™ (MARVLIS) by BCS is leading the movement to change the management of fire apparatus, not just as another point solution, but a significant new platform for visualizing your community and better protecting it.

“Risk” is defined in the Business Dictionary as “the probability or threat of damage, injury, liability, loss, or other negative occurrence.” The threats that face any neighborhood (or fire planning zone) are never constant. We must re-evaluate these time dependent risk factors and re-imagine the information flow used in making decisions that respond to knowing the time-dependent threat. If you only report call history as daily averages, you are ignoring the role that reality plays in your responses. Action as simple as viewing call demand by the 168 hours of each week will provide a clearer image of the routine daily patterns that exist. And these patterns are likely to be different during each season of the year or, at the very least, in comparing the months when school is in session against the months it is not. I recognize commuting changes in my own neighborhood the very day school opens and again on the day after it closes each year. If you can see that too, why are you not making efforts to adjust response potential to these realities?

While public safety is not a traditional ‘business’, it can learn a great deal from business leaders like Warren Buffet who said, “part of making good decisions in business is recognizing the poor decisions you’ve made and why they were poor.” We can do better and that is exactly why we should.

Leave a comment

Filed under Administration & Leadership, Command & Leadership, Dispatch & Communications, Fire Dispatch, Firefighting Operations, Funding & Staffing, Technology & Communications, Training & Development, Vehicle Operations & Apparatus

Analyzing Routes and Response Times

This is a second preview chapter of a new book in the Primer series from Bradshaw Consulting Services to be titled “Closest Vehicle Dispatch: A Primer for Fireâ€? to be released in time for the FDIC 2017 at the end of April.

Whether you are held to the standards of NFPA 1710, which addresses predominately career fire department responses in the US, or NFPA 1720, which deals specifically with volunteer departments, the challenge of meeting these response time standards is increasingly difficult for many reasons. Higher demands on limited resources and increasing performance expectations from the public are just a couple of those forces opposing response efficiency. Another elementary factor that critically impacts our response times is the route we choose in order to arrive at an incident. In most cases, there is not always a single route that is consistently the best choice at all times of the day or week. These differences can also include seasonal variations or be complicated by special events which may be planned or unplanned (Demiryurek, 2010). The subjectivity of route selection is further complicated by dynamic characteristics such as traffic or weather in addition to the extent of the mental map we develop of a service area or what that map may be lacking in adjoining or mutual aid areas (Spencer, 2011).

Most of the considerations that we process as we consider a potential path of travel in an emergency vehicle are often made subconsciously through personal experience and knowledge. While there is no legitimate argument against knowing your service territory well, the question becomes do we have sufficient awareness to consistently make the best route choices?

According to U.S. Fire Administration statistics for 2005, responding to alarms accounted for 17 percent of firefighter on-duty fatalities (Response, 2007). Deaths in road vehicle crashes are often the second most frequent cause of on-duty firefighter fatalities. In 2014, this percentage dropped to only 10 percent with a total of just 7 fatalities. Although the change is positive, it is too early to consider this to be a trend since it is only the second lowest number of crash deaths over the past 30 years (Fahy, 2015). While these accidents are not all due to their route choice, it can be argued that there are times where crews were clearly in the wrong place at the wrong time. Furthermore, the shortest path is not always the quickest route, and the fastest one may not have the simplest directions either (Duckham, 2003). Given the technology and data available today, there is little doubt that we can make strong decisions provided that we understand how we make these choices and what information may improve them.

In selecting a route for any particular apparatus, we may consider the physical or geographic characteristics of the roadway that determine the maximum speed of travel based on the maneuverability and size of our apparatus. Similarly, we must consider the likelihood of traffic congestion and also the safety of our crews as well as the public. As we increasingly rely on algorithms for making driving decisions, it is important to appreciate the mechanics of how the technology components function together. The Global Positioning System (GPS) is often credited with providing guidance to vehicle operators, but this is not exactly true. The satellite constellation that makes up the American-operated GPS (and similarly the European GLONASS) simply sends accurate time signals by radio waves to our portable receivers who detect the length of time each signal has traveled through space and then triangulates a position based on the calculated distance from those man-made stars (Hurn, 1989). The accuracy of the position that your GPS unit determines is based on the quality of those signals received and the precision of the local clock used to compare the time encoded in the signals. These satellites have no concept of transportation networks or traffic congestion on earth. It is Geographic Information Systems (GIS) that model the street networks and also track the vehicles using them. Unlike the limited number of GPS-like constellations in space that help us derive our position, there are a multitude of GIS-based computer services that offer routing recommendations. Some of these services, like the consumer-based routing applications available on your smartphone, are located on “cloud serversâ€? (although they are quite terrestrial) while others may be hosted privately on local government networks and available only to “trusted clientâ€? applications on your Mobile Data Terminal (MDT).MARVLISiOSinFD

Each of these GIS services has unique embedded algorithms for recommending directions or to estimate arrival times (Keenan, 1998). As users of these systems, we become subject to the specific assumptions inherent within their design leaving them far from being equivalent to one another (Psaraftis, 1995). For instance, network models must account for the elevation differences of overpasses in relation to the roadway below in order to prevent suggesting that a vehicle take a turn off of the side of a bridge. The cost of that ill-fated maneuver would be insurmountable, but other legitimate turns have minor costs associated with them because the apparatus must slow down to navigate the curve safely. A traffic light, or oncoming vehicles, can add further to that turn delay. Accounting for these delays requires logic in the GIS routing algorithm as well as valid time estimates coded into the street network data at each intersection.

The most basic feature of any transportation network model, however, is the cost of movement along a road segment in either direction which is known as its “impedance.â€? Many systems will assume the speed limit over the distance (impedance_time=speed/distance) between intersections to derive a similar “drive time” in both directions. Real world conditions (including traffic, terrain, and weather) will prove that speed limit-based assumption to be overly simplified and can lead to poor routing decisions because of unrealistic impedance values in the model (Elalouf, 2012). Crews will quickly recognize these failures and the lack of trust that these errors engender can compromise the entire routing program. Realistic impedances should be variable based on the time of day or day of the week in addition to the direction of travel.

More complex online routing services now offer near real-time traffic updates. While this traffic feedback can be invaluable to most drivers, its practicality to emergency vehicles appears limited in general. If our task was to deliver pizzas, we would be constrained by normal traffic regulations. Knowing where traffic congestion is at any given moment would allow us an opportunity to seek an alternative to bypass a congested intersection. This is a common type of need for drivers and therefore many consumer routing apps seek to address that specific function (Ruilin, 2016). But when our duty is to respond to the accident at that same intersection that is causing the delay for others, these typical consumer routing applications may fail our unique requirement. This objection is especially valid where emergency vehicles are not strictly constrained by the driving patterns of other vehicles on the roadway. In certain situations, it may be allowable for an apparatus to use the road shoulder for travel or even cross a median to use an on-coming traffic lane or to traverse a one-way street in the wrong direction (Harmes, 2007). The only reasonable exceptions to this generality are those dense urban areas where congestion is excessive and these “open” lanes or roadway shoulders simply do not exist to allow apparatus to circumvent that traffic. In a recent trip to New York City, I visited a fire station in downtown Manhattan. They received a call and exited the station with red lights and sirens blaring, but even the air horn was unable to move traffic. The engine sat at the traffic light behind the rest of the cars until the intersection cleared enough to allow drivers to create a path up to the next intersection.

In general, when we look to leverage technology for our unique demands in public safety, a system would ideally be able to learn our peculiar patterns of travel and record typical impedances based on how our own fleet resources travel. Additionally, these impedances will likely be different during certain hours of the day or on specific days of the week and vary even further seasonally based on whether school is in or out of session. These cyclical patterns will have a huge impact on actual drive times and any route recommendations must account for them accordingly. Current consumer routing applications are continually improving their ability to recognize and address the needs of passenger cars or ordinary delivery trucks, but this still does not necessarily translate to better routing of emergent public safety vehicles in most cases.

Finally, the last critical piece of route selection is a review after the call. Comparing the actual route traveled with the recommended path is an important feedback mechanism to both ensure that the system is operating as intended and to build confidence within your crews that encourage them to trust the system. This is not to suggest a blind obedience to technology, but constructing a learning process for everyone in developing tools that function to improve overall performance. No technology is perfect in the real world, just as no person has ultimate knowledge at all times. But cooperatively, we can learn to make improvements in either the computer or human systems as needed to enhance awareness in the other. The most successful implementations of routing assistance create cooperative relationships between responders and the GIS staff responsible for maintaining the data. Failures discovered in any system should not be used to condemn an otherwise useful technology, but seen as opportunities for improvements in either the algorithms behind it or the data that fuels it.

One of the critical outcomes of route selection, aside from arriving safely, is the total time of travel. No matter when the clock starts for measuring your response time, it is the minutes and seconds that the wheels are rolling that often consume the majority of it. The longer that time or distance, the higher the cost. A cost that can be measured both in actual vehicle operating expenses as well as the risks associated with its operation; not to mention the losses adding up on scene prior to your arrival. In general, the shorter the time (and distance) between dispatch and your safe arrival on scene, the better it is for everybody.

 

References:

Demiryurek, U., Banaei-Kashani, F., Shahabi, C. “A case for time-dependent shortest path computation in spatial networks.” GIS ’10 Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, November, 2010; 474-477.

Duckworth, M., Kulik, L. “’Simplest’ Paths: Automated Route Selection for Navigation in Spatial Information Theory.” Foundations of Geographic Information Science. (2003) 169-185. Berlin: Springer-Verlag.

Elalouf, Amir. “Efficient Routing of Emergency Vehicles under Uncertain Urban Traffic Conditions.” Journal of Service Science and Management, (2012) 5, 241-248

Fahy, R. F., LeBlanc, P., Molis, J. Firefighter Fatalities in the United States-2014. NFPA No. FFD10, 2015. National Fire Protection Association, Quincy, MA.

Harmes, J. Guide to IAFC Model Policies and procedures for Emergency Vehicle Safety. 2007. IAFC: Fairfax, VA.

Hurn, Jeff. GPS: A Guide to the Next Utility. (1989) Sunnyvale: Trimble Navigation.

Keenan, Peter B. “Spatial Decision Support Systems for Vehicle Routingâ€?. Decision Support Systems. (1998);22(1):65-71. Elsevier, Salt Lake City.

Psaraftis, H.N. “Dynamic vehicle routing: Status and prospects.” Annals of Operations Research (1995) 61: 143.

“Response-Time Considerations.â€? Fire Chiefs Online. ISO Properties, 2007. Web. 20 May 2016.

Ruilin, L., Hongzhang, L., Daehan, K. “Balanced traffic routing: Design, implementation, and evaluation.” Ad Hoc Networks. (2016);37(1):14-28. Elsevier, Salt Lake City.

Spencer, Laura. “Why the Shortest Route Isn’t Always the Best One.â€? Freelance Folder, November 2011. Web. 7 December 2016.

2 Comments

Filed under Administration & Leadership, Conferences, Dispatch & Communications, EMS Dispatch, Fire Dispatch, Firefighter Safety & Health, Firefighting Operations, Technology & Communications, Training & Development, Vehicle Operations & Apparatus

The Fallacy of the "First Due" Area

The following is a preview of a book coming soon from Bradshaw Consulting Services to be titled "Closest Vehicle Dispatch: A Primer for Fire" which is a follow-up to "Dynamic Deployment: A Primer for EMS".
Watch for the new release in time for the FDIC 2017 conference at the end of April.

The modern legal definition of response zones can be found in the Code of Federal Regulations, which states that the “first-due response area is a geographical area in proximity to a fire or rescue facility and normally served by the personnel and apparatus from that facility in the event of a fire or other emergency.â€? (44 CFR 152.2) This banal definition glosses over some very interesting history in the development of modern professional fire departments. In the mid-nineteenth century, there were frequent, and often bitter, disagreements over territories that sometimes resulted in physical confrontations. In fact, the politically powerful New York City volunteer fire companies of that era were known to send out runners ahead of the engine in order to claim the right to fight a particular fire and thereby receive the insurance money that would be paid to the company who fought it. While the monetary incentives are not nearly so direct today, there is still a great deal of pride invested in being the “first responders” to an incident. It would not be a difficult argument to make that we haven’t changed as much as we would like to think in regards to response.
A retired fire chief recently relayed a story to me about an engine crew that raced through a residential neighborhood in order to beat another engine that had been dispatched for mutual aid since the “first dueâ€? engine was out of quarters returning from another call. The need was so great to be the first responding company in “their own areaâ€? that they willingly disregarded the safety of the public that they had sworn to serve simply to avoid the embarrassment of being second to a call that was “rightfully theirs.â€?
The concept of the “first due” area is a strategy to automate a century-old manual concept of pre-assigning the closest resources to specific structure addresses within a fixed response area. The thought that a central station will have the closest apparatus to any potential fire in their district is simple, but with the increasing complexity of urban transportation networks, it is also an increasingly simplistic idea. The reality is that traffic patterns, and increasing traffic congestion, can dramatically change response times, particularly in high density population areas.
Public safety vehicles, even those running emergency traffic, can sometimes struggle to reach the posted speed limits at certain times during a shift. Alternatively, a lack of traffic at other times will permit the discretion of rates above the normal traffic speed. These periods of diverse congestion levels exist not only for intermittent periods of time but can vary dramatically by the direction of travel as well. Additionally, these temporal and directional impacts are confounded by the fact that station locations are often inherited positions that were designated many years earlier when housing, demographic and development patterns were very different from today. In most areas, fire station placements have grown through ‘incrementalism’, often tainted with political influence. In some jurisdictions this inheritance may go back over a century or more. Not all current station locations are the result of some forward-thinking intelligent design. The result of fixing address assignments to these past growth patterns may, or may not, represent who will be able to arrive first on the scene with the right resources. Furthermore, the common overlap of nearly a third between each of multiple urban engine companies means that when they are each dispatched from quarters, the next few arriving fire units, under normal conditions, will likely have a similar response time to that of the “first dueâ€? apparatus.

 

The “effective service areaâ€? of any station will vary during different times of the day based on traffic congestion. On a typical morning, as most traffic is heading toward a downtown business district, an urban station located at the city center will be able to travel outward toward the suburbs with relative ease. At the end of a normal business day, that same station will find that it can no longer travel as far in the same direction in the same length of time. Any sort of break in the normal business routine will further alter that pattern. These exceptions can include weekends, holidays, or special events. Most areas will also experience seasonal changes to traffic as a result of adding school buses or tourists to the roadways. The result of traffic is the evolution a unique “first dueâ€? area for different hours of the day and days of the week during different months of the year. A “fixedâ€?, or “averageâ€?, first due area must either ignore, or at the very least, generalize the pressures of these growing realities.

 

Generalizations of Effective Service Areas as Impacted by Primary Traffic Patterns
Morning                                                                     Afternoon

Rzones1      Rzones2

During a typical morning “rush hourâ€? period, the heaviest traffic may be to the north and west as in the left example making response in that direction relatively more difficult than moving to the south and east. Consequently, the effective response zone represented in gray around two example stations will compress moving with the traffic and elongate against that traffic. In the afternoon, this pattern will reverse since the heaviest traffic would now be moving away from the downtown area making response to the south and east slower as compared to the morning pattern and therefore reforming the effective service area in the opposite direction.

The dispatch of a theoretical “persistently closest resourceâ€? is made even more difficult when we consider that an increase in call volume makes it increasingly common for an apparatus to be dispatched when it is already out of its assigned station, either on or returning from another alarm. With an increase in call volume, the chances of another call leading to a dispatch before a unit has returned to its station are only increasing. These moving vehicles will have a significantly different effective service area and a different proximity to an incoming alarm when compared to an apparatus that is currently parked in a given “first dueâ€? station. Additionally, the “chute timeâ€? in preparing the crew to respond is completely eliminated when the dispatched vehicle is already moving. In this case, the effective response area is larger when considering response time than an apparatus that is parked at its station. However, this dynamic nature of the responding vehicles can also work against the efficiency of a traditional “first dueâ€? response. Consider that an apparatus may be available after clearing an alarm at some extreme point within its district when a call is received from an opposite extreme location. The mere fact that the responding vehicle is moving may still not overcome the greater distance that places it significantly further from that next alarm than an apparatus that is parked elsewhere. In this case, the closest unit may well be one outside of the assigned primary response area.

Impact of Increasing Call Volume on Effective Service Areas

Rzones3

When an apparatus clears a call, it becomes available in a different location than the station and although it is capable of responding with a “zero chute time”, its distance from the station will impact its effective service area possibly putting it further away from the “next call” than a neighboring station “in quarters”. As call volume increases, the likelihood of being dispatched while returning from another call only increases.

These changing logistical dynamics significantly alter the performance realities for modern fire stations from simple planned service delivery to a complex system of matching dynamic resources to increasing demand. Meeting the expectations of your community requires more than the historical paradigm of “first dueâ€? scenarios assisted by mutual aid to that of a cooperative system approach designating primary and secondary response functions on-demand and independent of an arbitrary enforcement of outdated patterns of convenience. Fire departments must literally become dynamic fire services requiring an intelligent coordination of these mobile resources.

3 Comments

Filed under Administration & Leadership, Command & Leadership, Dispatch & Communications, Fire Dispatch, Firefighter Safety & Health, Firefighting Operations, Funding & Staffing, Technology & Communications, Training & Development, Vehicle Operations & Apparatus

We Need Some New Stories

We always hear that EMS is still a relatively new discipline. And in the scheme of medicine, or even public safety, that is certainly true. But we shouldn’t let the fact of its youth keep us from acknowledging that it has already been around long enough to accumulate some of its very own antiquated dogma. If you have any doubt, consider the reaction to changes in protocol – even those with good evidence to support some new practice. Working cardiac arrests on scene, for instance, was not met, at least in my experience, with enthusiasm at the prospect of improving patient outcomes. What I heard were excuses for why something different wouldn’t work. I thought about that exchange this week as I was listening to a recent Medicast podcast on an entirely different topic. Near the end of that recording, Rob Lawrence remarked that we really need to do away with the old stories that start out with “back in my day…”

The stories of some grizzled professionals include not just memories of MAST pants or nitrous oxide, but the idea that tourniquets take limbs, not save lives. More recently stories have been spun about the movement away from the long-held reliance on the long spine board as an immobilization splint during transport or even the value of therapeutic hypothermia for cardiac arrests.

While there is no denying, or even stopping, a rapid state of change in EMS, we must be sure that it is not just change simply for the sake of change or even resistance for the same reason. Change must be meaningful change that is guided by reasoned thought and scientific evidence, not personal anecdote. And new practices should be carefully modified to address current issues or new understandings of the problem.

Another sacred, yet unjustified, belief among too many providers is that the dynamic deployment of resources (commonly referred to as “SSM”, or System Status Management) is an unmitigated failure of cost-consciousness that actually leads to increased expenses and provider dissatisfaction. The evidence, however, from many of the services who now employ some facet of dynamic deployment has proven that while it can be tricky to implement well; the savings in time, money, and lives are definitely real. And those savings need not come at the cost of provider safety or comfort either. Whether you have had bad experiences in the past, or just heard about it from others, it is time to set aside the old stories and take a new look at the current technology and practice in every aspect of EMS that leads to improved performance.

To advance our profession, we must completely ban the expression,  “but that’s how we’ve always done it” and look toward “how we can do it now!”

 

6 Comments

Filed under Administration & Leadership, Command & Leadership, EMS Health & Safety, EMS Topics, Fire Rescue Topics, Firefighting Operations, Opinion, Technology & Communications, Training & Development

Is Our Success Killing Us?

Should we really be upset when people in the community listen to us? After all, EMS protocols and people are notorious for creating our own problems. We write the public a “blank checkâ€? saying that if they believe it is an emergency to call 9-1-1 immediately and as a result we have created an increase in calls for non-emergent complaints. We continue to treat every call we can by transporting to the hospital and create a class of consumers called “frequent flyers”. When we need funding, we tell the public that “seconds matterâ€? and we define a parameter that the public uses against us to measure our success. Perhaps they listen much closer than we typically give them credit.

So what happens once we figure out they have heard us – we change our story! And we feel that we must do it dramatically in order to make the point that “we don’t do it like that anymore.â€? At some point we began to use MAST or PASG as a primary treatment against shock but eventually removed them from every ambulance as they fell from favor by delaying definitive care for a short-term gain. At first it was critical to get cardiac arrest patients to the ED, but now we set policies to work them on scene for better survivability. We drill into each responder that every single fall must be suspected to have a spinal injury and now some have begun to campaign to remove long spine boards from vehicles. Evidence showed us that tourniquets should be used only as last resort measures before learning evidence now shows that proper application early can have the best effect. And then we learn that there is nothing magical that actually requires a doctor to remove them as well! It seems that the “evidence-basedâ€? trend in EMS requires that being “progressiveâ€? means we lay in wait for some “proofâ€? in order to jump on a previously long held belief so we can debunk it as some old “wive’s tale.â€? But why must we always go to an extreme new position? Our industry is designed to resist “fashionsâ€? by accepting change of practice slowly for safety reasons. While personal beliefs can be more fluid, it takes a while for the protocols to catch up. Perhaps we need to moderate both ends.

Change within a system is not expedited by extreme positioning, but reasoned and thoughtful conversation. The article on Things Your System Should Deliver is well written and certainly worth the read and consideration. You don’t have to become a zealot for change, a thoughtful advocate is powerful enough. Learn from the process we work within and work with it instead of against it if you want it to update more quickly. Engage in dialog with medical direction AND politicians AND the communities you serve. It is through these channels that change is truly affected and we will find the success we can live with.

 

Leave a comment

Filed under Administration & Leadership, EMS Health & Safety, EMS Topics, Firefighting Operations, Funding & Staffing, Training, Training & Development

The Default Solution is Always More

My wife announced that there wasn’t enough money in the checking account again. The obvious solution to her was that I simply needed to add more money to it each month and that the problem would then go away. Any attempts on my part to question where the money is being spent is considered completely offensive simply on face value. There are so many details that I would just not understand. After all, I simply need to know that we are talking about meeting the needs of our family. How could I even consider not addressing those needs? Do I want a child to go without an education? Without shoes or food? It could happen she warns, if the funds are not provided. Oh, and I can’t reduce the family size either by letting any of the kids (or even my wife) go. Alright, maybe I took that analogy to an extreme there at the end, but replace my wife with the fire chief or union leaders, my kids with union firefighters, and make me a politician or simply the public and the story is replayed all over the country and even across the world. â€?If we don’t have more money, someone could die!â€?

I was thinking about this economic routine when I read the article City asked to boost fire resources in wake of slowing response times. I was prepared to blast it as another of the “how can you put a price on a lifeâ€? stories. But to my surprise, “city administratorsâ€? in this case started discussing “restructuringâ€? – they even got to specific issues by pointing out that it was “chute timeâ€? that was slowing down even though the actual travel times were improving. However, the familiar refrain still finally appeared, the Alderwoman in this particular story “plans to bring forward a notice of motion asking the city to look at what she calls a general lack of resources within the department.â€?

While I cannot diagnose why the response time compliance in this specific situation went steadily down from 64.7 percent in 2007 to just 54.7 percent last year, I also cannot concur automatically that it is by default a lack of money. Even the Deputy Fire Chief “expects a number of factors have played into the slowed turnout times since 2007,â€? before admitting “but he welcomes additional resources into the department, including more firefighters.â€?

Again, I admit that I don’t know all of the details surrounding the specific question in this next case asking Should City Merge Emergency Operations? But the first thing that struck me was that the city was looking to take over a nonprofit ambulance service in order to save money. I understand that the city is a major contributor to this service and that the fire department attends one third of their calls yet the city is the one complaining of the duplication of effort. The assumption is that the entire amount of support currently being given to the volunteers would be considered savings and could mean a new fully equipped ambulance after a merger. It seems to me that the money that was being used for operations would still be needed even after the fact.

A final article I read on the topic was New Toronto Fire Chief Says Merger with EMS Eyed. In this story, the City Fire Chief acknowledged that the existing fire model was broken saying “The status quo 
 is not an option. It just isn’t.â€? Part of his initial attack of the problem was reducing the number of firefighters to save money while an official service review is conducted. Once that review is completed,â€?every single truck in every single locationâ€? will be examined to determine the most “efficientâ€? route forward. It was exciting to hear an administrator keeping the options (outside of the status quo) open. But the next line in the story asked about the recommendation of an accounting firm to merge with the more profitable EMS agency. Then I began to hear that common refrain begin again when the chief responded, â€?I’m not opposed to anything that improves service for citizens.â€? However, he changed the melody a little by saying â€?You’ve got to build a model that fits this city. We need a ‘Made in Toronto’ solution.â€? there was no talk of “quantitative easingâ€? or government agencies “too big to fail.â€? It was, I hope, straight talk about finding real solutions in a bad economy. It may still be the money in the end, but let’s keep those options open until then. And I hope more agencies look at “locally grownâ€? solutions before defaulting to money or taking over EMS.

Oh, and just for the record, I would never really compare my wife to a union boss. It was just an analogy, Sweetheart.

1 Comment

Filed under Administration & Leadership, EMS Topics, Firefighting Operations, Funding & Staffing, News, Vehicle Operations & Apparatus