EMS Myth #7: System Status Management lowers response times and enhances patient care

I was actively involved in prehospital care from 1974 until 1983 in various capacities. During the summer after my freshman year of medical school, I worked full time as a paramedic, but, for the next six years, I was overwhelmed with medical school and residency responsibilities. When I finally finished my residency in 1990, I found EMS had changed drastically while I was away. For one thing, the practice of system status management (SSM) had been instituted in many EMS systems. It was a strange concept. Ambulance crews really didn't have fixed stations; they were continuously moved around the city, presumably to decrease response times. Likewise, crew shifts were varied. Some crews came in at peak hours as others left. Somewhere behind it all must be some science, I thought. But is there? Or is SSM built on a foundation of sand?

History
      The concept of SSM was introduced to EMS by consultant Jack Stout. It is a computer-based system where historical call data are used to deploy the ambulance fleet for optimal response times and to predict where the next cluster of calls is likely to occur. In most systems, call response data for the previous 20 weeks are entered into a computer and, based on that historical data, systems believe they can predict when and where calls will occur—or at least establish trends. This is usually broken down into two categories: chronological demand and geographical demand history. Chronological demand is defined as the volume of calls to expect at any given hour or day of the week—basically to try and predict when calls are likely to occur. Again, this is determined from the previous 20 weeks' call activities, although some systems use historical data from the past year. Geographical demand history uses the same methodology to try and predict where calls will occur.
      SSM is most commonly used by so-called "high-performance systems." In reality, it is pretty much limited to public utility model (PUM) operations and a few private ambulance services (SSM and PUMs were both invented by Jack Stout). In the larger systems, a specially designated system status controller monitors the system and directs fleet movement in response to perceived future call locations and volume. The SSM feature is built into several of the more popular computer-aided dispatch (CAD) software packages.

The Scientific Evidence
      When I began my literature search into the science of SSM, I was surprised that there was no scientific evidence to support the practice. All of the writings pertaining to SSM were in EMS trade magazines or were written as though the process was based on science.¹ Most were written by people who had a proprietary interest in implementing the practice.^2–5 The only numbers published relative to SSM were from the city of Tulsa, OK. Following implementation of SSM, response time dropped from 6 minutes, 46 seconds to 6 minutes, 9 seconds—a saving of 37 seconds. However, this savings is clinically insignificant, and furthermore, ambulance maintenance costs were increased by 46% after implementation of SSM because the ambulance fleet was constantly on the road.⁶
      In reality, it is impossible to predict where and when calls will occur with any degree of certainty. Historical data from a 20-week interval, or even a one-year interval, are statistically insufficient to make any reasonable prediction of call location or timing.
      In preparing for this article, I discussed this concept with two university-based statisticians. One figured that it would take 20–40 years of historical data to make a reasonably accurate probability prediction as to call location and timing. The other stated that it would probably take 100 or more years of data before any predictions would approach significance in terms of probability. He likened it to predicting the weather. Even with over 100 years of weather data, temperature predictions are still relatively inaccurate. The meteorologists get close, but they are rarely correct. And, predicting temperatures is a lot less complicated than predicting EMS calls. The statistical calculation necessary to determine the probability of where and when a particular EMS call will occur is massive and would require a super computer to solve.
      There are some meaningful data, but these are often not integrated into SSM models. Demand for EMS is higher for certain subsets of the population. For example, persons of low income are more likely to access EMS than those of higher income. Likewise, elderly patients are more likely to summon EMS than their younger counterparts. Thus, the demand will be greater in areas where there is more poverty and more elderly. We can state that the probability of an ambulance responding to a nursing home, assisted-care facility or neighborhood with a high percentage of elderly residents is greater than in other areas. Likewise, the probability of an ambulance responding to an impoverished neighborhood, public housing project or homeless shelter is greater than you would see in an affluent neighborhood.⁷ But, over the last two decades, there has been a federal and state mandate to relocate economically disadvantaged folks throughout the community rather than concentrating them in rows of public housing or "projects." This throws a wrench into predicting where the poor folks are. Finally, and this will be a great revelation for many, most traffic accidents occur on busy roadways. Thus, we can reasonably predict that the probability of an accident occurring on a major highway during morning rush will be greater than at midnight on a lonely neighborhood street. Do we really need a computer to tell us that we will have more EMS calls at nursing homes, in impoverished neighborhoods or on major thoroughfares during rush hour?
      In an interesting study, researchers in Ontario, Canada, evaluated the impact of SSM on EMS personnel following its implementation. They found that SSM resulted in employees being forced to sit in idling or moving ambulances for extended periods of time. In fact, during a 12-hour shift, EMS personnel spent 56% of their time roaming or on standby (exclusive of responding to calls). After implementation of SSM, a survey found that 71% of EMTs and paramedics reported an increase in back pain, while 93% reported back pain or discomfort from simply sitting in the ambulance.⁸
      SSM is purported to: Optimize response times, maximize use of personnel and equipment (a cost-saving measure), increase skills retention by exposing personnel to a variety of calls, decrease potential for the EMS system to become "swamped," limit exposure to high-stress areas and provide a shorter travel distance to the scene. Whether these are true is open to conjecture. But I think I can safely say, as have others, that SSM does result in unruly and overly tight staffing schedules due to projected system demands and status.⁹ It does not provide any significant leeway in the event of a MCI or disaster. In these cases, mutual aid must be obtained from neighboring agencies or personnel called in from home. Furthermore, with SSM, there is less chance that field personnel will have a "light shift" where they can relax, catch up on paperwork, stock the ambulance or review cases. It is important to remember that there is a lot more to EMS than simply running calls. One of the big problems is that you never have any real place to call home—a station where you can relax, grab a bite to eat, lie down, read, watch television, exercise or take care of basic human needs (shower, toilet, sink). This was evident to me one day when I stopped into a Texaco station in south Fort Worth where ambulance crews frequently "post." After fueling my car, I went into the bathroom. There, beside the toilet, was a copy of Emergency Medical Services Magazine.
      It seems reasonable to assume that SSM increases work stress due to constantly changing assignments that make it harder for EMS providers to learn the geography of their response areas or become familiar with the neighborhoods they are entering. Furthermore, anticipating the call that never comes can also be stressful. I have known paramedics working in an SSM system who spent nine hours of an 11-hour shift in the ambulance, on the road, and were only dispatched to three calls. The rest of the time they were "posting" or being relocated for coverage. Also, SSM causes an increase in vehicle maintenance and miles traveled. This is a real cost that must be considered by any EMS operation considering implementing SSM. Finally, and this may be among the most important factors, SSM discriminates against low-volume areas (read affluent, sparsely populated, away from major roadways) due to long response times. If the SSM system is operating as it should, ambulances should be constantly directed to perceived high-volume areas and away from low-volume areas. I'll bet that the taxpayers would not like to hear this! Is this practice really fair for EMS providers and consumers?

Conclusion
      If you look through all of the SSM-related smoke and mirrors, you will see the true story. Fixed ambulance stations are costly. This is especially so if you make a commitment to respond to all service areas in a predetermined time, at least 90% of the time, or pay a monetary penalty. It costs nothing more than increased vehicle costs to "post" the ambulance at the Texaco station or the local 7-11 convenience store. Ambulances and personnel are much cheaper than fixed ambulance stations. Thus "high-performance" systems, most notably public utility models, use SSM, although others have adopted it or one of its variations. I can't document the following statement with science—just with experience and emotion. I believe that employee satisfaction, morale and pay are generally lower in systems that use SSM, while employee turnover, stress and physical ailments are higher. If SSM is such a great deal, why has not a single major fire department adopted the practice? Phoenix, Los Angeles, Seattle, New York, Chicago, Dallas, Houston and virtually all other large U.S. fire departments use fixed stations for their fire and EMS operations. This is not to say they don't move assets around in response to system demand. But, they always have a home base. That is what I grieve most about SSM. As I think back to my career in EMS, some of the best days of my life were spent in ambulance and fire stations with friends and coworkers. We were kindred spirits. SSM has killed that camaraderie and that, my friends, is a shame.

References
1. Stout JL, Pepe PE, Mosesso VN Jr. All-advanced life support vs. tiered-response ambulance systems. Prehosp Emerg Care 4(1):1–6, 2000.
2. Stout JL. System status management. The strategy of ambulance placement. JEMS 8(5):22–32, 1983.
3. Stout JL. Computer-aided what? JEMS 11(12):89–94, 1986.
4. Stout JL. Measuring response time performance. JEMS 12(9):106–111, 1987.
5. Stout JL. Peak-load staffing. What's fair for personnel and patients? JEMS 14(8):73–44, 76, 1989.
6. Hough TG. A view from the street: System status management. JEMS 11(12):48–50, 1986.
7. Cadigan RT, Bugarin CE. Predicting demand for emergency ambulance service. Ann Emerg Med 18:618–621, 1989.
8. Morneau PM, Stothart P. My aching back: The effects of system status management & ambulance design on EMS personnel. JEMS 24(8):36–50,78–81, 1999.
9. Hausweld M, Drake K. Innovations in emergency medical services systems. Emerg Med Clinics North America 8(1):135–144, 1990.

Bryan Bledsoe, DO, FACEP, EMT-P, is an emergency physician, author and former paramedic whose writings include: Paramedic Care: Principles and Practice and Paramedic Emergency Care.