Optimizing Demand Forecasts

Improvement of your deployment operations requires that you understand where your services will be needed and how to get the available units into the most suitable positions. Then, once you are prepared to respond, it is also critical that only the most appropriate assignments are made for each request to preserve your ability to respond to the next call as well. Traditionally call assignment was a simple “closest unit” consideration with all your resources being equal. That task has now become increasingly complex with a recognition of a growing diversity in call acuity and the increasingly common tiered capabilities of your immediately available resources. This second step of appropriate dispatching toward operational efficiency will be the subject of a future blog post to focus this article solely on demand forecasting.

A common practice for emergency services that have grown beyond a single central depot has been a simple distribution of their resources geographically in the hopes of being able to serve anyone at any time. Without an abundance of crews, this is not typically a successful strategy since neither population nor risk are ever uniform. To make matters even worse, most agencies are experiencing an increase in their volume of demand while also facing some of the most serious challenges in decades to simply maintain staffing levels. Emergency medical services across the country are reporting employee turn-over rates of around a quarter of their staff annually. This trend suggests that there are not only fewer providers per call but less experience on each transport as well. Dispatch centers across the nation also face challenges with an average of 20% of their staff positions routinely left unfilled during the past few years. These difficulties underscore the importance of making good decisions quickly.

Figure 1

Disproportionate access to services is difficult to resolve with fixed stations and often results in increased service available outside of the intended district. To adequately populate this geographic coverage model requires an excessive workforce.

So, are you accurately forecasting demand to help improve your operations?

Is your current demand forecasting process recognizing trends throughout the day and week to allow for effective decision making in response to any predicted demand patterns? Without some certainty in your predictive capabilities, it is impossible to effectively trust the recommendations of any decision automation. A potential lack of credible information makes the choices of unit movement more difficult at the same time they are becoming even more critical to the agency. And a lack of credibility also encourages the freelancing of decisions outside of the control of your administration.

Seasonal variation

When reviewing your own annual call history, you should notice the seasonal variation that distinguishes not only the volume of calls within or between school calendars, but the very nature of the calls themselves tend to follow a pattern. During the summer months, personal schedules tend to be increasingly variable with more adventurous outside activities repeatedly lead to more traumatic events. Once school is in session, most families have less-flexible schedules and the shorter, cooler days often make individuals more vulnerable to acute medical conditions.

Even shorter temporal variation

On a shorter scale of time, differences are also recognizable by day of the week or even hour of the day. Higher call volumes typically occur toward the start and end of the traditional work week. The early morning hours of these business days also exhibit patterns found with early waking habits and the increased vehicle traffic and population movement. The pattern repeats itself later in the afternoon, but the locations of people are quite different than in the morning. The unique business hours and personal behaviors on the weekend also make these days unique from the rest of the week. An unequal distribution of people throughout space and time leaves discernable patterns in the location of requests as well.

Figure 2

Sample data demonstrating ALS (green) and BLS (blue) call volume comparisons by hour-of-the-day and day-of-the-week. Notice the similarity in daily patterns although total volume (represented by 90th percentile) is unique.

To create a useful model that honors all these variations, the operational period to be described in a forecast must generally be shortened while simultaneously extending the pool of similar examples to achieve the required statistical precision. The more similar the forecast of demand is to the current moment in time, the more useful it will be in guiding effective decisions. If the intention is to describe demand during the next hour or two, the historic records queried should reflect a comparable timeframe.

Fortunately, your call history is proven to contain many useful clues about the future. It is not merely a matter of extrapolating a progression of time or an assumption that the same request will come from the same caller again. The real-world is complex, yet we all tend to live, work, and associate with individuals that are more like us than the overall population. As a result, each previous request is an indicator of the types of requests likely from our unique population cohorts. The successful technique is in the allocation of the right populations within the right timeframes to sufficiently forecast the future demand. This is accomplished through the way incident records are selected in a dynamic query to represent a time-based forecast and even more importantly, how those results will be spatially aggregated.

Through Demand Monitor, MARVLIS users can not only update forecast parameters based on their local knowledge, but they can monitor both the accuracy and precision of each dynamic forecast. Using a default configuration, most services should find that approximately 80% of the actual calls received are in an identified hotspot recognized by a current demand forecast. With some effort, that average can often be raised to over 90% of future requests are correctly forecast by the hotspot zones. Simply raising accuracy, however, could be easily accomplished if precision is not considered. By including the whole jurisdiction within a hotspot, an accuracy of 100% would be the result. While technically valid, this type of forecast would provide absolutely no assistance in pre-positioning responders to improve outcomes. The forecast area must be maintained as small as possible while increasing the predictive capabilities of a demand query. Currently, this is recognized by comparing incoming requests over time to the effective forecast when each call was received.

Demand Monitor allows analysts to define multiple query strategies for simultaneous execution and evaluation. If each of these queries is validated against reality, the distinct forecasts can be quantitatively compared and improved over time. The result is a continuous quality improvement that requires some regular review to maintain.

Best practices in Demand Monitor

A recommended best practice for modeling demand is reviewing and modifying the demand queries at least twice a year to coincide roughly with the school calendar. It is not necessary to be precise in modelling academic dates, it is the mindset of schedule regularity that is driving the demand pattern. Jack Stout, the father of the System Status Management concept, suggested using a floating 20-week period based on the size of the spreadsheets he used, but this often crosses the known seasonal variations discussed earlier. To minimize the impact of influence from outside the current season, the number of weeks can be shortened. Reviewing only 5 weeks before and after the current forecast date cuts that total number of weeks in half. It is possible to maintain the number of records of the longer period by including the same weeks from a previous year to mitigate the reduction of number of samples while maintaining seasonality. However, the addition of too many years may have a detrimental affect by increasing the influence of older neighborhoods since newer subdivisions would have less representation across the years. Experience suggests looking back no further than 2 previous years in most circumstances. For most agencies, that keeps the records reviewed within the post-pandemic experience as well.

Another successful strategy to control for the temporal pattern can be to query a fixed seasonal timeframe rather than a floating period. If you want to model the school year, setting fixed dates of mid to late August through mid-May will clearly eliminate the effect of any summer dates. A downside to this method would be the necessity of changing the query period once school begins or ends for the year. Automating the model of both strategies simultaneously can allow for each query option to be graded separately to discover the best alternative for your jurisdiction.

It is difficult to argue against modeling each day of the week individually, but when it comes to the finer segmentations of the day, there is legitimate debate. Again, Jack Stout recommended modeling each hour of each day for a total of 168 unique timeframes of the week. Part of his justification is the average busy time of a unit being about an hour and to simplify the calculation of a Unit Hour Utilization (UHU). Demand Monitor is typically automated to execute every 5 to 10 minutes to minimize the amount of change between each forecast while allowing the predictions to subtly adjust more frequently. It is also common for ambulances to be busy longer than an hour in our post-pandemic world.

Once a query definition is set, it can be tested in Demand Monitor to see how many records it will return. Ideally, the number of records for any sample query should be measured in the hundreds, but less than a thousand. If you need to adjust your parameters, altering the number of years will have the greatest impact followed by the number of weeks and finally the number of minutes which will have the smallest influence.

The experts at BCS have decades of experience bringing real-time analytics to the real-world. If you require any assistance in customizing your Demand Monitor queries, please contact your support representative.

Passing ‘Fast’ for ‘Appropriate’ Responses

During the height of the COVID pandemic, shortages led to many operational challenges that required creative solutions. One of the more challenging issues that has become as endemic as the disease itself is the recruitment and retention of EMS professionals. This shortage has disproportionally impacted paramedics, as evidenced in the NAEMT survey results published in May of 2022. The ripple effect of the workforce reductions that has changed the certification balance favoring basic credentials has led to some logistical changes in priorities. The most recent NAEMT survey results, published last month, show services are taking longer to respond to requests, considering alternatives to serve low acuity calls, and changing the provider mix that services patients.

As more agencies move from exclusive ALS capabilities to tiered responses, there must also be a growing concern with ensuring the most appropriate resources are responding to each call. The idea of thoughtful intentionality in the assignment of units helps to improve the chances that the right resource will be available to the next future request for service. I like to describe the logical shift in thinking as moving from “the right response times on every call” to “the right call for responses every time.” This may be a subtle but highly significant change in attitude regarding the best, or most “appropriate,” response assignments to each request rather than routinely sending the closest unit. Managing these resources well may additionally involve adjustments to the expectations of your community.

Depending on the priority of a call, it may be that the closest resource is logically passed over for a more appropriately matched capability responding to that call from a greater distance. While the 90th percentile response times may increase for certain lower acuity calls, this selective assignment process allows advanced capabilities to be preserved for potentially higher acuity needs. But it is seldom really as simple as it sounds. How much further can that preferred response be before its preference is overtaken by the need to simply respond promptly?

The reality of these critical decisions means the process becomes far more complex and dangerously slower. The more conditions that must be understood and compared extend the time for each dispatch without automated assistance. By planning and codifying dynamic selection criteria, the extra delay can be eliminated which means making far better decisions in no more time than traditional fastest responses. These guided decisions can also be made uniform across positions and shifts to achieve corporate objectives that prioritize clinical outcomes based on acuity in addition to broad operational objectives that consider the condition of crews.

A typical Charlie priority call, for instance, might prefer to have a paramedic respond timely. That ideal response might be within, say, 15 minutes. With expected delays beyond that time limit, it may be acceptable to dispatch a BLS unit to begin care while still allowing the ALS resource to join the response from a longer distance. However, the practicality of that rigid rule may send a basic unit on a 14-minute response when the nearest advanced unit is only 16 minutes away. That implementation of a simple preference for immediate care has practical limitations because it committed two units with little time for the first to even complete an assessment before requiring a hand-off of care. Is the additional drop in service level worth the brief time savings in this example?

Response rules should be focused on improving both the speed and quality of outcome without artificially taxing the system. In this case, the lower-level capability may only be desired if it will be more than at least 3 minutes faster than the closest ALS unit regardless of its distance to travel. Without more time for basic intervention on scene, the multiple assignments are only tying up more response units without actually improving care.

A Delta priority request may also need a speedy paramedic response and a basic unit alone for too long may not be an adequate alternative. However, matching a paramedic QRV, or another supervisor, with that nearest BLS resource provided that it can be completed in 5 minutes less time than the closest ALS ambulance could be an acceptable solution.

While the time-sensitive examples above show better potential for care, there are also system benefits with appropriate responses on the lower acuity side of the scale. A Bravo request could be most efficiently served in a BLS capacity with longer response times before it would be deemed late. Yet if the preferred units are just not available by the time a limit approaches, an ALS resource could be dispatched to keep your response statistics within acceptable limits.

The impact of posting schemes on response capabilities cannot be overstated. There simply is no substitute to having the right resources located closer to their next most likely call. But the post priority can also be useful in assigning appropriate responses at the low-end of the acuity scale. A hospital discharge, or typical interfacility transfer, will not benefit from sending a fastest unit. The posts nearer the hospitals tend, in general, to be busier locations. Using one of those units not only increases the chances of keeping a crew within the vortex of handling patients, but it also exposes a potential lapse in coverage until another unit can be moved from a less active post. If the assignment is given initially to the unit filling the least critical post, there is no immediate coverage loss and no additional post moves required. Assigning an appropriate unit for this call can actually reduce the effective activity, or UHU, of other resources.

Appropriate dispatch is becoming a necessity to balance workloads and provide the best care possible to our patients given current trends. It comes, however, at a cost to the complexity of decisions demanded of telecommunicators unless they are given tools to help manage the art and science of dispatching. But to be effective, we must use appropriate automation tools for the best results.

BCS Releases MARVLIS Version 4.5

Dale Loberger                                                FOR IMMEDIATE RELEASE: 9/13/22

BCS, Inc.

(803) 641-0960

dloberger@bcs-gis.com

BCS Releases MARVLIS Version 4.5

MARVLIS 4.5 Available Featuring Significant New Features and Updates

Aiken, SC: BCS today announced the release of MARVLIS version 4.5. This major release provides new and updated features focused on our rapidly changing world. Incident recommendation has been expanded in scope and complexity, adding tiered recommendations to get the right resources to the right place even when resource counts are running low. Incident recommendation now also supports response packages for those incidents where a single resource is insufficient. This release also contains tools to simplify MARVLIS database deployment and adds support for multiple MARVLIS systems running on a single database instance. Finally, this release contains improvements in the Dashboard report and help system, NETCall functionality, and the MARVLIS technology stack.

“The evolution of MARVLIS to version 4.5 is yet another example of our dedication to innovation in the Public Safety sector. This new release expands on MARVLIS’s position as the complete solution to control, route, and manage resources across the entire agency. Communication centers will save time and reduce manual steps with new features like tiered responses and response packages”, says Tony Bradshaw, President at BCS. “The latest version of MARVLIS NETCall is a game changer for the efficient management of non-emergency resources and provides technology to optimize trip assignments to maximize profitability.”

Features and benefits of MARVLIS 4.5 include:

• Added Incident Recommendation module support for tiered recommendations and response packages
• New Query Sets to create vehicle and incident queries for incident recommendations
• Dashboard pages now include context-specific help links
• MARVLIS Database now supports multiple MARVLIS systems running on a single database instance
• Updates to Playback, Post Coverage, and Incident Recommendation Reviewer Dashboard Reports
• Added support for password complexity 
• Updated technology stack includes:
  • MARVLIS Client updated to support ArcGIS^® Runtime 100.13
  • MARVLIS Dashboard updated to support jQuery^® 3.6.0 from 3.3.1
  • MARVLIS Dashboard updated to support the ArcGIS^® API for JavaScript^TM 4.23
• Added support for routing with live traffic in Canada using the TomTom^® Real Traffic Feed
• NETCall updates to support revenue information in processing and numerous user interface enhancements

MARVLIS 4.5 is now available and is included as part of annual maintenance for existing MARVLIS customers. If you’d like more information or think that MARVLIS might be the right solution for your organization, please email sales@bcs-gis.com or visit https://www.bcs-gis.com/marvlis.html.

About BCS, Inc.: Founded in 1998 in Aiken, SC, BCS develops solutions to help organizations leverage technology and strategies to improve operational performance and delivery of time-critical resources, services, and management of non-emergency transportation. Visit us at bcs-gis.com

About Esri: Esri, the global market leader in geographic information system (GIS) software, location intelligence, and mapping, helps customers unlock the full potential of data to improve operational and business results. Founded in 1969 in Redlands, California, USA, Esri software is deployed in more than 350,000 organizations globally and in over 200,000 institutions in the Americas, Asia and the Pacific, Europe, Africa, and the Middle East, including Fortune 500 companies, government agencies, nonprofits, and universities. Esri has regional offices, international distributors, and partners providing local support in over 100 countries on six continents. With its pioneering commitment to geospatial information technology, Esri engineers the most innovative solutions for digital transformation, the Internet of Things (IoT), and advanced analytics. Visit us at esri.com.

About TomTom: At TomTom we’re mapmakers, providing geolocation technology for drivers, carmakers, enterprises and developers.

Our highly accurate maps, navigation software, real-time traffic information and APIs enable smart mobility on a global scale, making the roads safer, the drive easier and the air cleaner.

Headquartered in Amsterdam with offices worldwide, TomTom’s technologies are trusted by hundreds of millions of drivers, businesses and governments every day. Visit us at tomtom.com

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Advice From an FTO

As we begin to wind down on the pandemic-level of constant 911 calls and the endless hours waiting on a room in the ED, we find ourselves in a time to reflect a little before our next call. Like so many services, we have a new influx of eager young professionals. Recently, a new student asked me, “how do you guys keep doing this day after day?” Not an unusual thing to ask lately, and my reply was this:

“determination and our perseverance to make sure our patient gets the definitive care and treatment they need.”

COVID-19 has really stretched us thin, not just with staffing, but with supplies, training, willpower, and people who actually WANT to learn. Training new hires and students can be tedious and frustrating if you don’t have the opportunity to learn and adapt along with them in addition to teaching them what they need to know. You must become extremely patient and place yourself into their boots. If you don’t empathize, you risk placing yourself in the position of doing harm. Not only to your student, but to the patient, and most likely our profession as well. We need to be resilient and steadfast, showing them the ropes and thoughtfully placing them into the patient care position supported with good proctoring and mentorship.

Minority Report or Moneyball

I have often heard comparisons on the automation of System Status Management to the 2002 Spielberg movie starring Tom Cruise called “Minority Report” loosely based on the 1956 short story by Philip K. Dick. This science fiction action thriller is set in the year 2054 when police utilize a psychic technology to arrest and convict murderers before they commit their crime. The obvious comparison there is to the forecast of future call demand and the eerie accuracy of the reports that allow the right resources to get there in time to make a difference in the outcome. Sometimes in the movie, as in real life, there is a considerable cost to achieve that goal as well. It is easy to get wrapped up in the technology, particularly the virtual reality user interface that Detective Anderton (Cruise) uses to make sense of the premonitions and quickly locate the scene. I like to end the analogy there before we learn the darker side of the way the technology works and can even be manipulated to put a stop to the whole project. Perhaps some EMS providers think they see a similar inherent darkness and hope for an eventual collapse of the whole dynamic deployment paradigm as well. This may be where the art of a story and our reality diverge, especially considering the current economic dynamics even given the admittedly sporadic successes. This may also be why we need a different analogy.

Improving EMS Deployment Performance

I work regularly with agencies that are looking to improve aspects of their operations. Some casual readers may be surprised to know that the focus of those discussions is not always about cutting response times. While response is a simple and common measure, it clearly does not evaluate EMS well and certainly fails to encapsulate many of its complex needs and values. Still, I feel the necessity to address the time objective briefly before going on to other important aspects.  

Where Do We Go Next?

To know where our increasingly limited emergency resources will be needed next, we need to understand where future requests for service will originate. If we knew exactly where the next call would come from, we could proactively dispatch a resource there even before it is requested (watch the movie “Minority Report” for an idea of how that might work.) Unfortunately, the nature of emergency response is not nearly that easy, but that is not to say it is impossible to recognize useful patterns across both time and space. While the 2002 Spielberg movie was set 50 years into the future, it correctly predicted the use of several new technologies that have become reality in less than twenty years. And although we don’t use “precogs” in forecasting demand, the ability of data to show future patterns that effectively influence deployment is also now well established within some agencies.

No one can tell you who will be that very next person to dial 9-1-1; however, it is imperative for the effectiveness of deployment that we concede that people and events often follow certain predictable patterns. Let me explain how this works in just a few steps. First, consideration of the repeatable nature of the temporal distribution of calls has been used for years in making shift schedules. The following chart represents the daily call volume from a specific study, but without a scale along the vertical axis, it could easily be representative of almost any agency regarding their relative hourly volumes.

The daily behavioral routine of individuals perpetuates the collective pattern for the larger community. These daily patterns not only replicate over the years, but across various types of political jurisdictions according to a 2019 Scandinavian study on the �Use of pre-hospital emergency medical services in urban and rural municipalities over a 10?year period: an observational study based on routinely collected dispatch data.� The following graphs from that study represent the relative call volumes of rural, small and large towns, as well as medium and large cities over a decade showing the reproducibility of call volume forecasts by hour of the day.

If we segregate the total call data by weekday, we can capture variations by the hour-of-the-day within each day-of-the-week. The chart of call volumes by day over a twenty-week timeframe, shown below, displays the commonly repeated variation throughout each week. It is the reproducibility of these volumes that allows us to schedule adequate crews to cover these anticipated call volumes.

The next step is to adequately distribute those available resources spatially to address the variation over the geographic area by time which requires an even deeper understanding of the call patterns. The fact that we, as social creatures, often live or work in communities that share similar and predictable risk factors allows us to generalize assumptions of individual activities over larger community groups. Corporations have used targeted demographic profiles to understand local populations for many years. Community profiling has even been recognized by the World Health Organization as an essential skill for all health professionals to help understand the specific and detailed needs of focused populations. (See �Community Profiling. A Valuable Tool for Health Professionals� published in Australia during 2014.) Beyond predictable human variables that focus primarily on medical emergencies are the physical characteristics of our built environment that determine the repeatability of traumatic accidents. A 2009 publication by the Association for the Advancement of Automotive Medicine looked specifically at �Identifying Critical Road Geometry Parameters Affecting Crash Rate and Crash Type� to aide road safety engineers with the challenge of addressing safety issues related to the shape of motorways. The existence of identifiable causes explains the ability to properly forecast the vicinity of calls in addition to their timing.

The following animation demonstrates several spatial demand forecasts in quick succession that are normally separated in the real world by hours. Your existing historical CAD records contain the necessary information to build such dynamic views in real-time.

The demonstrated reliability of demand forecasts, both spatially and temporally, is well known to MARVLIS users and proven to provide the critical information necessary to make decisions in prepositioning resources to reduce the time of emergency responses and limit the distances travelled in emergency mode to enhance the protection of crews and citizens. Furthermore, the Demand Monitor has the capability of grading demand hotspot calculations specific to your service by comparing actual call locations � as they are being recorded � with the forecast probability surface to highlight both the accuracy and precision of our demand forecasts over time that is specific to your agency data and query parameters. The following screenshot shows comparisons of various forecast models.

The percentage of calls that correspond with each shaded area over the selected timeframe quantifies the query accuracy while the hotspot size denotes the relative precision. Accuracy could be increased easily by enlarging the hotspots, but this would be at the cost of precision. A well-balanced query should result in a relatively small-sized hotspot that properly captures a significant portion of actual calls.

Still, knowing when and where to anticipate calls is not enough in itself to determine resource deployment. Some number of outlier calls will likely occur outside of the forecast hotspots, so it is critical to also develop a strategy for managing the risk of covering demand versus geography as weighted factors in any deployment decision. Where we need to be next is well beyond the simple strategies we typically employ now and must fully leverage the depth of our data for deeper understanding and action.

Examining the 2020 Vision of EMS

The NHTSA Office of EMS released a significant document last year called the EMS Agenda 2050 that was carefully crafted to set a bold vision for the next 30 years of paramedicine by clearly differentiating the focus of care from its original definition in the 1996 EMS Agenda for the Future. Now, after just a few months of a COVID-19 pandemic, we have seen these modern precepts being challenged. As with any such vision of the future, a bit more perspective then just the immediate quarter is required. Before stepping toward the future, it is important to know exactly where we are today. To provide that update, NASEMSO released a new National EMS Assessment this past April to provide a measure of emergency medical response personnel and their agencies in this pivotal year of 2020. Although the latest survey is only updating the original work of a decade ago, there have been such dramatic changes that direct comparisons, even over this relatively short time frame, are difficult. To help bridge that gap for comparison, the folks over at ZOLL did a quick blog to reflect on the evolution of the EMS industry since 2011. Still for many, a little more context on how we got this far may be helpful before we can truly understand the significance of these most recent discussions regarding the future of EMS.

It was only back in 1960, that President John F. Kennedy made the statement that “traffic accidents constitute one of the greatest, perhaps the greatest, of the nation�s public health problems.” The automobile was well entrenched in the new American dream by this point as ribbons of smooth highway were unrolling across the country that facilitated speeds of travel much greater than the safety aspects of the car would afford. Yet it wasn’t until 1966 that the National Academy of Sciences ‘white paper,’ officially titled “Accidental Death and Disability: The Neglected Disease of Modern Society,” that ambulances began to transform from a side business at funeral homes into our modern Emergency Medical Systems of today. This initial milestone report, delivered during the Vietnam War, stated that �if seriously wounded � chances of survival would be better in the zone of combat than on the average city street.� So, the signature of President Lyndon Johnson provided federal funding through the National Highway Safety Act of 1966 that not only provided for the establishment of EMS programs, but thoughtfully placed the system within the federal Department of Transportation. Although the Omnibus Budget Reconciliation Acts of the 1980’s under President Ronald Reagan transformed direct federal EMS funding into state preventive health and health services block grants, federal guidance remained within the National Highway Transportation Safety Administration.

The numbers 9-1-1 were added to the American experience by AT&T in 1968 and it grew slowly across the nation as more communities demanded Emergency Medical Services. The most effective recognition of out-of-hospital care throughout the 1970’s came as the result of a television show simply called “Emergency!” This drama highlighted the results of efforts by early cardiologists like Drs. Lown, Zoll and Pantridge in having developed portable devices capable of disrupting the lethal dysrhythmias of v-fib effectively parlaying paramedicine from a focus primarily on trauma to include chronic medical conditions within the home as well. Pediatric trauma would not be officially recognized until 1984 with an Emergency Medical Services for Children study leading to a report finally published in 1993. The patchwork quilt of EMS continued to grow with increasing interest and even more piecemeal funding. Economist Jack Stout led a revolution in economic modeling of EMS systems during the 80’s and 90’s in response to the imbalance of demand and financing that had already fractured EMS into a kaleidoscope of models from fire-based, public safety to “third-service” public utility models to for-profit integrated healthcare businesses. 

It is certainly no accident that our industry has ended up in the position we are today. As W.E. Deming has taught the world, “every system is perfectly designed to get the results it gets.” And we proudly embrace the philosophy that states “when you’ve seen one EMS, you’ve seen one EMS” because we still believe that each service knows the particular unique expectations of their individual community while allowing insurance companies to dictate reimbursement rates. As a result, there is little federal standardization beyond a minimum national level of competency and few local agencies that are funded as “essential services”  even though the NAEMT has advocated this position for years. 

Today, it is heart disease that has overtaken the American consciousness as waistbands expand across the countryside demanding more from our organs than the body was designed to provide. In addition, we face new biological and socio-economic challenges for delivering healthcare in the field. We’ve needed a new road map like the EMS Agenda 2050, but we can’t just sit back and wait for it to happen. As professionals, we all need to educate ourselves on topics like Emergency Triage, Treatment, and Transport (ET3) and health information exchanges that are being piloted at select services. We must be the change we want to promote. 

 

How "New" Will "Normal" Actually Be?

Be careful what you wish for. Just a few months ago, before the words “COVID-19” and “social-distancing” became a regular part of our conversations, I was speaking with the Operations Chief of an EMS service about the difficulty in hiring and retaining paramedics. He said it would take “a downturn in the economy before we could hire enough medics” since candidates typically gravitate toward stable jobs in public service when the market is in a recession. Well, its technically not a recession, but the current pandemic is clearly stressing the world economy and even altering patterns of use for many EMS agencies. In some areas of the country, call volume is now out-stripping capacity while others find themselves in a very different place with far fewer calls than normal. So, as we even consider whether we still need the paramedics we had planned, the immediate questions become “what is ‘normal’,” and “what could be so ‘new’ about it?”

The past can often be a good guide. My primary job in consulting is helping agencies with the optimization of their resources. Doing this successfully requires that I can discover patterns from history to guide forecasts of the immediate future. This is a difficult position when the world is no longer behaving according to the regular fluctuations of the past. Yet, as an undeterred student of history, I continue to search for models that can illuminate the path before us as I did regarding demand in my previous post. There is no shortage of significant anecdotes from history to review, but each has its limitations when applied to today.

My first study was the so-called “Spanish Flu” of 1918-19. It was the deadliest pandemic in history that infected nearly a third of the human population and killed well over 20 million (or by some estimates more than 50 million) victims, including some 675,000 Americans. This historic pandemic had a similar effect to today by shutting down world economies and hiding its population behind face masks. The scariest consideration of a modern parallel to this period would be the idea of an even more devastating second (or even third) wave of infections yet to come. This historic flu, however, was still not able to destroy the world order as some feared. In fact, it preceded one of the greatest economic expansions of industry leading to a period that would be known as the “Roaring Twenties.” The score of our current pandemic is merely a shadow of its predecessor with less than 5 million worldwide infections known and slightly more than 300 thousand total deaths around the globe. So, could we also expect a similar economic boom following our current crisis? That is highly doubtful as the economic conditions preceding this shutdown were entirely different than a century ago. And I’m also not sure we would necessarily want that same exuberance that stemmed from a generation that developed an attitude of “nihilistic hedonism” born from a season of austerity and fear caused by the disease. The age group primarily affected at that time developed a laissez-faire attitude toward life fueled by a rapid rise in prosperity induced by sweeping changes in technology, society, and economy. It was literally the beginning of the modern age – and then came the worst economic depression ever.

Fortunately, the current death toll is still far too low to engender a similar sociological backlash even in a time of modern polarized politics echoing the protests of the last century. With a presidential election less than six months away, many states have entered some form of “Phase 1” of a controlled economic reopening of society. There are probably as many anecdotes as opinions with states like Texas going big on economics over epidemiology compared to the more cautious moves of hard-hit states like New York and New Jersey only ‘cracking open’ slowly. While scientific advances are promising, we still do not have a vaccine, effective treatment, or even reliable tests. Yet we seem reliant on the promise of “contact-tracing” in an environment of community-spread rather than recognized efforts elsewhere at “contact-isolation.” So we can likely plan on seeing more cases of COVID-19 in the coming months and political reactions will likely vary with an increased influence of politics.

What is likely to be lasting from our current experience are new “telemedicine practices” being implemented by physicians and widely accepted by a public that fears even going to the hospital at the moment. If EMS will ever be able to justify the continuation of Community Paramedicine practices or possibly even extending them through their own Mobile-Integrated Healthcare outreach (or as a home-provider within the telemedicine practice of doctors) it will be right now. If the opportunity of the current crisis passes without making political gains to extend the reach of EMS, it will only be more difficult to accomplish in the future. We have also seen traditional conferences gone virtual to eliminate travel and large physical gatherings. Although the experience lacks some of the traditional perks, it has huge cost and time savings. Similarly, professional-referred journals are quickly giving way to a faster social exchange of information and ideas online that bypasses traditional peer-review being replaced by a new social review creating “healthcare influencers” online. To continue this trend, we must figure out how to “qualify” these social icons in the long-term and socially circumscribe their power.

There are also examples we could study of pre-hospital responses to HIV/AIDS, MERS, and SARS. Even though each occurrence caused a significant public panic and subsequent EMS response, their lasting influence quickly waned and the lessons they taught for preparedness were not applied nationally to help us respond to a pandemic. Consequently, the real strategic question we must consider in planning for the future is fortunately not how society will react or estimate how many cases of COVID-19 we will experience, but what effective change will be wrought related to how EMS functions or is financed going forward. As we contemplate moving out from the Department of Transportation  where we are paid only for moving patients, we could consider the terrorist attacks of September 11, 2001, as another example of a precedent model. However, that initiating event concluded within hours and its perpetrators targeted an ideology rather than a lack of immunology. Both passions and fears were inflamed worldwide by these coordinated attacks, but the only lasting results have been legislation expanding government surveillance in the Patriot Act (reauthorized yet again nearly two decades after the event), the creation of a new government bureaucracy over the traveling public in the Transportation Security Administration (which remains focused largely on airline travel which was the target of the terrorists at that time), and the longest on-going war of American history.

Today, the enemy has no flag and the world (or even our industry) also has no unified leader to coalesce a response tactic. Even in the field, the providers of EMS services cannot agree on whether we represent public safety (which justifies an essential funding stream for the public good) or that we provide bona fide healthcare services as a part of an integrated service stream offering appropriate care anywhere from the home to a hospital (that is worth reimbursement independent of driving someone to the hospital.) What history teaches us are several lessons. First, government responds to situations that expand its own interests and that are simultaneously supported by the affections and desires of the public. Even during this EMS Week, it is doctors and nurses who are seen on the front lines of the pandemic war even though the tip of the spear is made up of Emergency Medical Services professionals who go into the homes of the sick and reach through the wrecked vehicles of the injured to risk themselves in the preservation of others. We will continue to be the ‘invisible third service’ as long as we struggle with our identity and lack the statement of a value proposition for a suitable underlying financial mechanism. Second, government consistently responds along an evolutionary path to the last threat rather than a forward-thinking approach. Until we can justify the payment for necessary treatment on scene in addition to any transport to definitive alternative destinations, we will not see revolutionary change. Even wars can be waged indefinitely as long as no one notices they continue. 

We may see some fluctuation in demand for a while, but in the long-run we will return to a familiar normal fare of heart attacks, strokes, and falls once again. It may not be the exact same place we left months ago, but it will not be an entirely new place either. The struggles we fought before will continue to be our struggles again. Hiring and retaining paramedics will again become a topic of discussion as we continue to fight for budgets to maintain our response metrics. That is unless we can learn from one other historical example that comes from back in 1843.  That is the year that Charles Dickens published his famous work known as, A Christmas Carol, where the the Ghost of Christmas Yet to Come prophesies, “If these shadows remain unaltered by the Future, the child will die.”

Improving Operations in Crisis

Our practice of EMS is facing significant challenges right now. Although many traditional aspects must still continue, we have a few more obstacles to overcome in a crisis. This “pilot podcast” highlights some practical modifications to consider for operational improvements, especially for MARVLIS users.

Notes:

Demand for EMS services is disproportionate across America and outside of normal patterns, but some changes to our practice are helpful across any service right now. If you haven’t begun seeing longer times yet, you can expect it to be coming as we face longer dispatch delays for extended EMD, longer on-scene times for re-triaging patients using a “1-in and 1-out” scouting method, longer decontamination times for ambulances possibly infected with COVID-19, and fewer professional human resources collectively making operational efficiency and crew management even more important than ever. At the same that time we are still dealing with our regular calls, mass quarantines and stay-at-home orders are likely to increase calls for domestic violence, drug abuse, acute mental illnesses, and even suicide as people socially distance.

1. Consider modifying queries in Demand Monitor to include longer general timeframes when forecasting dynamic demand:

• Extend the period of weeks, e.g. 56-60 days both Before and After the current date.
• Extend the period of minutes, e.g. 90-120 minutes both Before and After now.
• Enable hotspot accuracy reports to quantify the value of different queries.

2. Create new posting plans with Deployment Planner that balance the weight of geography and demand to limit post move recommendations.

3. Implement a Leapfrog in Deployment Monitor value to penalize moving stationary ambulances by preferring to move units already in transit.

4. Call BCS Support for any help you need to configuring MARVLIS to your operational challenges beyond simple mindless efficiency.