Tag Archives: static v dynamic

Static v. Dynamic: A Continuum of Cost

In our recently published book, “Dynamic Deployment: A Primer for EMS“, John Brophy and I established a dichotomy between the standards of static deployment and dynamic deployment in the very first chapter.  Fortunately, that strong polar perspective has spurred some interesting discussions for me. While the check-out lane analogy was effective in distinguishing some of the differences of static and dynamic deployments, its simplicity only recognized the extreme ends of the spectrum and failed to acknowledge what I would describe as a “Continuum of Cost” between them.

Few systems (at least those with more than just a few ambulances) probably function exclusively at either extreme. The static model will necessitate some flexibility to provide “move-ups” to fill holes, just as dynamic systems will have reasons to keep specific posts filled as long as enough ambulances are available in the system. The reasons for moving, or even fixing locations, may have something to do with demand necessity or even the political expedience of meeting community perceptions.

While there are many differences between static and dynamic deployments that we could discuss, there are also some elementary misconceptions. For instance, dynamic deployment does not mean vehicles are constantly in motion. The term dynamic refers to the nature of their post assignments which can vary between, and even within, shifts. As alluded to in the book, proper post assignments also reduce, not increase, operational expenses. In at least one example we stated, the dynamic deployment strategy was shown to significantly reduce the number of unloaded miles actually driven, which in turn increases the percentage of overall miles that can be billed. This situation not only increases revenue while simultaneously reducing expenses, it also reduces fuel costs and wear on the vehicles (and crews) too which potentially extends their useful life. All this is still in addition to reducing response time and improving crew safety by positioning ambulances closer to their next call so that fewer miles need to be driven under lights and sirens.  The inherent efficiency of this management strategy allows a system to achieve response compliance at the 90th percentile with the smallest possible fleet.  To achieve the same compliance level with a static deployment of crews and posts, the fleet must grow significantly larger. Another recent sample calculation showed that both staff and fleet size would need to grow by well over double in order to reach the same goal. The resulting cost continuum, therefore, clearly shows that a static fleet has operational and capital expenses multiple times the costs of the dynamic deployment model without burning crews out with excessive and unhealthy UHU figures.

For the sake of validating my argument, it is unfortunate that these examples are from private ambulances companies who do not wish to openly share details of their calculations at this time for competitive reasons. It would be safe, however, to assume from these competitive reservations that these results are not automatic, but dependent on proper management and the use of good tools. There are certainly numerous examples of poorly managed systems or ineffective operational tools. To achieve similar positive results in your own system requires certain knowledge, an underlying reason for having written the book in the first place, and an assurance that the deployment tools are proven to be effective.  Just as managers should have references checked during the hiring process, vendors of operational deployment tools should be able to provide ample references for successful implementations of their technology in comparable systems to your own. It is also important that any solution be able to address a continuum that includes your specific objectives to find a balance between geographic coverage with anticipated demand coverage at an acceptable workload and schedule for your staff.

There is no “magic bullet” to achieving operational nirvana, but the combination of effective management with operationally proven tools has shown that cutting costs while improving performance is an achievable goal in most any size system. It is also fair to say that performance can be enhanced with less skill through the application of significant sums of money; but honestly, who can afford that sort of strategy in the competitive arena of modern mobile integrated healthcare.

It is our desire to produce yet another, even more extensive, volume on the topic of dynamic deployment to make the achievement of efficient and effective high performance EMS a reality for more systems. Stay tuned for future details!


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