The call came in as an unresponsive man, 75, who suffered a fall. At the patient’s home first responders find the man is actually in sudden cardiac arrest. He fell, his wife tells them, maybe 15 minutes ago or longer, but he seemed to be breathing at first, and she wasn’t sure if she should call 9-1-1. She didn’t do CPR. The crew pretty well knows what the outcome will be but pulls out all the stops anyway, just as they’ve been trained. An hour later the patient is pronounced dead in the ED. The paramedic who impatiently fills out the report has never had a successful save.
If you’ve been in EMS long enough, you’ve probably been in a system that rarely sees a sudden cardiac arrest survivor, or for that matter even knows what its survival rate is. Historically there hasn’t been evidence that all that effort makes a difference, especially for such a small percentage of calls.
In the past several years, however, we’ve seen a change in attitudes as more and more communities report improved survival rates and system leaders realize SCA is a treatable condition, not a death sentence. The foundation for this improvement has been a commitment to the collection and analysis of basic data.
Over the past decade there has been a virtual data explosion across society. With the digital revolution came the ability to collect huge amounts of data, search it for answers and visualize it in ways that just weren’t possible before. Data has always been with us; we just never had the ability to readily access and analyze it until computing power came of age.
Data has also taken on particular importance in healthcare. With the passage of the Affordable Care Act, data will be used now more than ever to define quality of care and what is reimbursable. With the broad adoption of electronic patient care reports, EMS is poised to collect and use this data in innovative ways.
EMS is unusual in the way it delivers healthcare, which in many ways makes it ideal for data-based research. Healthcare provided by EMS is largely dictated by geography and is usually a sanctioned monopoly delivered by a combination of public and private providers supported either directly by taxpayers or indirectly through mechanisms like Medicare, Medicaid and the private insurance market.
All EMS practitioners are typically trained to a specific standard and follow protocols for the care of given patient conditions. The care they deliver is documented on a standard platform based on nationally accepted data elements and definitions (the National EMS Information System, or NEMSIS). In most instances, information about 9-1-1 calls is first entered in a CAD or some other sophisticated software system, creating another valuable source of data. Because of these reasons EMS could be a case study on how to look at data for healthcare operations, quality of care and risk reduction.
So what is data? What can it do for EMS? And why should you care?
What Is Data?
Merriam-Webster defines data as “the factual information (as measurements or statistics) used as a basis for reasoning, discussion or calculation.” Data can be virtually anything that gives us factual information, such as 9-1-1 chief complaints, response times, vital signs, patients’ addresses, ages, genders, medication histories, hospital drop times, even paramedics’ impressions of patients’ conditions. You soon come to realize we have been doing “data collection” for quite some time.
However, in order to use the immense power data holds, just collecting it isn’t good enough; you have to collect “good” data. Many researchers and operations chiefs have spent too much time focused on the outcomes of data analysis without investing in the input on the front end.
What’s It Good For?
Collecting and analyzing data gives us enormous potential to look for trends, discover new therapies and find ways to improve care and operations. Without data you fly blind, with no ability to see what you’ve done or should be doing. You’re somewhat like Alice in Wonderland, working hard to find an answer to the wrong question.
In thinking back to our cardiac arrest patient, what data would be useful in predicting whether he (or any given patient) has a decent chance at survival? While there are many points of data in a sudden cardiac arrest event, the Utstein criteria are the most accepted. Was the arrest witnessed? Was CPR started by a bystander? Did the 9-1-1 caller receive CPR instructions over the phone? What was the patient’s down time? What was the EMS response time? What was the patient’s initial rhythm? All of these data points paint a picture that helps to predict whether this patient is likely to survive a cardiac arrest, and all are captured, or should be, somewhere in the system. Being able to say confidently which patients we should look at to determine how well the system is doing and how can we make it better absolutely depends on data provided from the field.
Research and Innovation
Data is the lifeblood of research and innovation. Because of data we now know that MAST pants are not so good for trauma and the airway in CPR isn’t the most important thing to improve survival from cardiac arrest. It wasn’t until we embraced the scientific process that medicine moved from the likes of traveling salesmen and barbershop owners into the evidence-based profession it is today.
Since its beginning EMS has battled to become a respected profession within both public safety and the medical world, with many successes. However, if EMS is ever to become the presumed experts in care of the ill and injured outside the traditional healthcare setting, it will need to prove its worth. To do this takes research, which requires data.
Go back to our cardiac arrest patient and think about the impact of bystander CPR. Research has consistently shown that bystander CPR is one of the most effective ways to improve survival. The data on this, collected by EMS, has been instrumental in how bystander CPR is promoted and taught.
Data also allows you to think innovatively because you are more confident of your situation and the results. This allows you to see what others may not and try things others may not understand. For instance, it was noted by one EMS agency that having dispatchers go through a long list of instructions for callers in order to start CPR defeated the purpose of dispatcher-assisted CPR. There were often times when callers were still on the phone with dispatchers when medics arrived to find patients pulseless and not breathing—with no CPR having been performed.
In this case the question identified was: How long does it take a dispatcher to start prearrival instructions? The research around this topic led to a simplification of the process and allowed callers to begin chest compressions much more quickly. The result was improved survival from sudden cardiac arrest—and without having or looking at data, this innovation would not have been possible.
There are many other uses for data outside the clinical world to improve the delivery of care. For example, doing robust demand analysis using call data to strategically place assets makes systems more efficient while contributing to survival by ensuring patients’ needs are satisfied in a timely fashion. Not having or using this data leads to understaffing and over-resourcing, the worst of both worlds for both patients and taxpayers.
Quality of Care
Quality has taken a front seat in the new healthcare argument. The government is moving away from paying for stuff and is now focusing on paying for results. Likewise, as budgets become more constrained, the fight over vanishing dollars will go to those who show the best bang for the buck. As a healthcare delivery mechanism subsidized in various amounts by taxpayers, EMS is vulnerable. It is critical that EMS show its worth. The best way to do that is through evidence-based performance, based on data.
Measuring quality of care delivered is making headway into EMS. For example, California has recently implemented “core quality measures” with the expressed intent to “highlight opportunities to improve the quality of patient care delivered with an EMS system.” Furthermore, “emergency medical services systems across the state will be measured and compared on their performance.” It is clear from these statements that unless EMS systems have robust data, they will not be able to be evaluated. Likewise, private EMS providers will find it more and more difficult to bid and win service contracts if they are unable to demonstrate a commitment to quality through attention to data.
So how does EMS show value to the community using data? We go back to our example of out-of-hospital cardiac arrest. It is widely accepted that what happens in the first few minutes of the arrest is critical to the outcome.
In 2005 USA Today ran a special report documenting the cardiac arrest survival rates of 50 of the largest U.S. cities (http://usatoday30.usatoday.com/graphics/life/gra/ems/flash.htm). Only 12 cities were rated as “Tier 1,” meaning they used scientifically valid methods to show how many of their citizens survived cardiac arrest. This standing would not have been possible without a commitment to collecting data. The development of the CARES registry and initiatives like the HeartRescue Project help facilitate and promote the collection of sudden cardiac arrest data.
Besides showing you how well you are doing, data also lets you know if you aren’t doing something particularly well before it hits the front page of your local paper. For instance, knowing in real time that you’re having problems meeting response-time criteria in a certain part of your city allows you to fix deployment of resources so that, at the end of the month, you’re not left explaining why the system failed. It is even more of a concern to not know what your response times are, then have an industrious local reporter figure them out after your EMS crew takes 20 minutes to get to a cardiac arrest victim.
Armed with data and a robust analysis and implementation program, your agency can be confident in demonstrating its value to the community. If you cannot, then your leaders likely don’t enjoy city council meetings, have a hard time justifying your budget and endure a constant barrage of negative press. Data gives you the ability to show quality and value, allows you to be innovative and helps you avoid problems. Without data, none of this is possible.
If the above reasons didn’t convince you of data’s importance, maybe these will:
Risk reduction—EMS practitioners often operate in high-risk environments. We go into dangerous situations, face unique challenges and sometimes do things that can either cure or kill our patients. Because we perform high-risk procedures, it is essential to document with data that we’ve done them correctly or, if we didn’t, that we recognized it and corrected the problem.
One well-used example of risk reduction is airway support. While anesthetists learned more valid and reliable ways to assure endotracheal tubes are in the right hole, EMS was slow to catch on. It was not until well-documented literature showed an alarming rate of undetected esophageal intubations that EMS began to get serious about getting it right. Intubation is a difficult psychomotor skill and can lead to catastrophic events if not performed correctly. Besides good training, your system must also be able to document that livesaving (or -taking) skills are done correctly and safely. This takes data.
There are many other operational issues where data is key. Have you ever thought a certain medic seemed to use more controlled substances than others? It’s possible for an agency to get providers’ data in real time and, applying statistical procedures automatically, see who is at the leading edge of the administration curve. Maybe there’s no problem, but without data you have no idea. If you are not tracking issues like these, you are left to interpretation of events, one of which could be from a plaintiff’s lawyer.
Advancing the profession—Data is also important because of what it conveys about maturity and professionalism. For EMS to become truly accepted as a profession, it will continually have to prove itself—and the only way to do this is through data. We all know that many of the electronic platforms currently on the market to collect patient information need better functionality and ease of use. But ultimately data still drives decision-making and is the only way to improve processes, prove value and provide protection.
Finally, let’s return once more to that cardiac arrest patient in the opening. The data the paramedic collected on this patient helped the medical director trend cardiac arrest survival rates, which was then used to go to the city council to argue effectively for more resources, including a public awareness campaign. It allowed a public health researcher to look for clues to improving survival and target segments of the community’s population for CPR training. It documented that the medic did an excellent job in caring for this patient, including that the endotracheal tube was in the right place. Finally it contributed to a research project that showed how dispatch-assisted CPR could be more quickly implemented by bystanders. In turn, this research helped support the evidence for new standards for every lay person—which, where implemented, led to more people surviving sudden cardiac arrest.
Behold the power of data.
Alex Garza, MD, MPH, is former chief medical officer for the U.S. Department of Homeland Security. Currently he serves as the medical director for FirstWatch, a technology company that helps public health and safety agencies use real-time data to improve situational awareness, operational readiness and clinical care. An emergency physician, Dr. Garza started his medical career in 1986 as an EMT and then paramedic in in Kansas City.