he NEMSIS project does a good job of standardizing WHAT data is collected, but does not particularly well establish a methodology for it's application. For example the percentage of chest pain patients given ASA can be collected and used to benchmark a system's compliance with the protocol, but how do you discern the numbers? I may only give 3 of 10 Cx pain's ASA, but three of them may be on coumadin, and another 4 are presenting with cough and fever. Have I given only 30% of the cx pain's ASA, or 100% of the CARDIAC related Cx pains? As far as the provider influencing the data collected, if the ALS first responders know that they are being looked at, and the necessity of ALS services in their area may be decreased or reduced, do you think that there may be an increase in ALS modalities perfomed on scene? In other systems, where there maybe a rife between the ALS first responders and the transport agency, perhaps the transporting agency might speed through the on scene process, so that they can have the patient in their truck faster, decreasing the first responders chance to have them on scene for an hour?

Citing NEMSIS again, to comply with a 100% number, would I give ASA to a highly probable pneumonia, so as to make the # look better? I feel that the opposition to data reporting, which we discussed only serves to highlight the fact that not many of the ALS services or treatments provided by EMS are strongly supported by positive outcome (as defined as time sensitive, not done by EMS = a lower survival rate, or increased cost to patient stay). Nobody (in management) be it public or private sector, wants to see anything that says less is better. Budgets need to justified, everybody’s little piece of the pie needs to be protected, and everyone wants another slice. Nobody wants to take a hard look at the services provided, and really have a truly data driven system. They might not like what we find out.

Data collection is important, but the interpretation and implementation of the results is also critical. How do we correlate outcomes with services provided? How do we interpret the data we get? Many of the studies published in the trade journals do not provide the data critical to correctly evaluate the data or conclusions made.

Take for example a recent study in Pennsylvania, which implied that paramedic intubation of head injuries correlated with an increase in mortality. Yes, it does. Patients intubated in the field have higher mortality rates, but it can be inferred that patients requiring field intubation are in worse condition than those not intubated prehospitally. Yet this study does not break down system configuration, number of paramedics in the system, number of intubations done per year per medic, or the scene time involved with the intubated vs. non intubated patients. It also does not state the time of injury to time of intubation, or show transport times. All of these factors are important in interpretation of the data, and in implementation of new protocols or policies, yet are not really addressed.

I was not trying to say that data collection and the concept of evidence based medicine are bad, in fact they are mission critical to the future of prehospital medicine, but that the politics of EMS nationwide are not currently set up to handle that type of change. The EMS system needs to put aside the politics of provision of services, and without the desire to have that type of change, a lot of time and money gets wasted.

I would suggest that we also look at the overall quality of the care provided in our systems. How often are our assesements accurate when compared to admitting or discharge Dx? Evaluating our cognitive abilities is equally important to a statistical breakdown of how many sticks it takes, or how often protocols are followed. Without it, we may as well go back to the "push half the blue box" days.

As a side note, I worked in NYC and the Albany, NY area, not Buffalo- that’s part of Canada I think. And you can add Palm Beach County to the list.

Chad Stephen Albert, EMT-Paramedic EVAC Ambulance,
Daytona Beach, FL
csa819@clearwire.net