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This question has a hidden nuance in how it is worded. It uses the terms “acceptable” and “expect.” While we should strive to avoid answering a question with a question, this may be one of those rare exceptions when we do so because it must be established as to whose job it is to determine what is acceptable and what the expectations are.
The simple answer may appear to place the burden of making the determination into the hands of elected officials. They are, after all, ultimately responsible for setting service expectations. However, they often lack intimate and contextual knowledge of the daily operations of a fire department. This can lead them to make uninformed, superficial and arbitrary decisions about productivity expectations. This problem can be exacerbated when elected officials are pressured by budget shortfalls.
Our recommendation for dealing with this question is avoid deferring the decision to elected officials in total. Rather, we think it best to engage them in meaningful discussion about how to define first responder productivity, be that for firefighters, EMS personnel or those who provide both services. (Note: It is often difficult for elected officials and appointed administrators to comprehend the schedule and workload of paid first responders, so we will exempt staffing-on-demand models from this discussion because their contribution to financial challenges is far less impacting.)
Engaging your decision makers in defining expected service levels is a key element in determining your response or deployment model. The response model – determining when, where and how personnel and apparatus are deployed – can then be directly linked to the productivity of your EMS crews. Be prepared to make connections between your response model and outcomes. For example, cities including Jersey City, NJ, Boston, MA, and Seattle, WA, have demonstrated that a focused team approach of basic life support (BLS) specialists along with advanced life support (ALS) paramedics positioned strategically throughout the region improved safe rates in cardiac arrest patients (i.e., patient returned to spontaneous circulation). The improvement was dramatic, increasing from 18% in 2005 to 46% in 2011.
The key to delivering quality care is driven by the productivity of crews; specifically, positioning crews properly during the times of highest call volumes. This type of resource staging and deployment is based on an analysis of your response system’s historical data – studying when, where and what type of EMS calls have occurred over a given period. This, combined with seasonal fluctuations and demographic changes, will reveal the best places to deploy your resources.
This defensible method to determine your deployment model accurately reflects “predictive modeling,” a term describing deployment decisions based on historical analysis of call patterns or trends. Analyzing crew assignments such as number and type of staff as well as varying work assignments to match expected call patterns can help you improve overall system performance. Employee productivity is improved with a redesign of work schedules that match supply to demand.
An early step in determining the level of productivity of EMS personnel is to track crew activity, but how long to track? While it may appear burdensome to track on-duty activities for extended periods, short-term tracking may project productivity levels that are not accurate. For example, if you decide to track activity for a week, an unusually slow or busy week could skew the results.
Tracking should be hour-by-hour and personnel should list activities they were involved in each hour. It’s important that work activities not be embellished. The truth always has a way of coming to the surface and exaggerating the activity of personnel will only serve to harm the credibility of the department and its management.