Data is still my favorite four-letter word
Gaining signals from noise and understanding the trajectory of service delivery
When I started speaking on the U.S. national circuit a decade ago, I delivered a standard presentation called “Data my favorite four-letter word.” The aim of the lecture then was to convince listeners and agencies that they really did have enough data and information to collect, collate, process and trend into actionable intelligence to support solid decision making.
In my own organization, I banned anecdotal evidence and retired the phrase, “well we always did it this way,” and replaced it with, “If we do what we always did, we will get what we always got.” I also forbade the use of the word “multiple” when describing a quantity of whatever it happened to be with the good-natured rebuttal, “multiple is a word, not a number – how many of x were there?” That was then. I’m delighted to see that we are now data savvy and are using data to inform decisions and actions in EMS.
Data-driven decision making
My equal affection for all things public health has been driven by the fact that if we can present the picture of the looming emergency through data, then we can prepare and present steps to, if not stop it, at least prepare for it. One key data mining success at the Richmond Ambulance Authority (RAA) included becoming a local expert in the Central Virginia alfresco opioid retail industry by plotting all overdoses and tracking naloxone administration by dosage to provide a gross indicator of spread and severity of locally distributed mixture. With the assistance of our syndromic surveillance vendor, we created triggers to alert us to:
- Controlled drug use
- Frequent or repeat users
- Geo-cluster reporting
We also looked at those patients who had been administered naloxone more than once, and with the assistance of the medical examiner, compared opioid deaths against our own cohort of patients to identify trends and learning.
In fact, we had so much data, that we created a public health/MPH student internship for undergraduates to research our issues each season. One of the hypotheses explored identified that our city’s Latino community was reluctant to call 911 in an emergency, as 911, in their book equated to ICE. This research led to superb levels of liaison with the local Latino community, greater understanding on both sides of the community, and creation of and participation in Spanish language police and EMS citizen academies. This is something I recommend to all agencies as this is live training, and the possibility of peer reviewed publications or poster presentations for the student, and fantastic results for the organization.
NEMSIS EMS by the Numbers
One of my favorite, and publicly available and free data products now, is the National EMS Information System – Technical Assistance Center (NEMSIS TAC) “EMS by the Numbers” weekly charts. EMS by the Numbers offers a weekly look at specific categories of EMS activations occurring during the COVID-19 pandemic. The charts, updated weekly, provide information regarding temporal variations in the type and characteristics of EMS activations occurring across the nation. The data and trends contained in the charts certainly help us understand the effects of COVID-19 as seen through the eyes of the EMS responder. To provide context, many of the charts identify key dates and activities in the progress of the pandemic including:
- Week 9-10 (red vertical line). Feb. 26: CDC reports community spread; Vice President Pence to lead task force
- Week 12-19 (blue shaded area). President Trump declares national public health emergency. Many States initiate stay-at-home orders with orders beginning to phase-out in Week 19
- Week 22 (orange vertical line). May 25: Memorial Day
- Week 36 (teal vertical line). Start of Labor Day weekend
The most recent question (Figure 1) looks at the Rate of influenza-like illness (ILI) after the Labor Day holiday. Concerns were raised that the unsocially distanced gatherings and relaxed regulations of the last holiday would cause a re-ignition of COVID-19 on a national scale. While we are waiting for a few more weeks’ worth of data to declare a true trend, activity to the right of the teal-colored vertical line (Labor Day) has certainly moved away from its previous downward trajectory!
Figure 1: NEMSIS EMS by the Numbers influenza-like illness reporting
In addition to influenza-like illness (ILI), EMS by the Numbers also includes trends in EMS response to cardiac arrest, scene death, injury, vehicle crashes and opioid-related activations using the national EMS data set of over 40 million records collected and displayed over a 1-year chart. They answer some of the key questions we have asked this year, such as, “did our EMS volume drop off,” “are we seeing less cardiac arrest calls and more DOAs,” “what about opioids and naloxone administration?”
Hopefully, this article also addresses the question – what happens when I upload my EPCR? Your data joins a huge pot that can begin to answer questions on a national scale. I have found this data set useful for briefings and discussions, and I recommend them to anyone that needs to educate anyone, from new hires to elected officials.
The data intelligence cycle
Data or raw information is just the beginning, an assembly of numbers or facts in an act of feeding the beast is not the endgame. We must always take what we have, collate it, asses it and act on it. This is what others call the intelligence cycle or the science of generating signals from noise. We must make sure that we take action to either correct, learn from or develop new treatments and plans to improve our levels of service and patient outcomes. So yes, data is my favorite four-letter word, but as with many things, it’s not how much of it you have, but what you do with it that counts!
Data is still my favorite four-letter word: EMS One-Stop With Rob Lawrence
For an audio version of this article and more, listen below, as Rob is joined by Catherine R. Counts, PHD, MHA, health services researcher with Seattle Medic One in the Division of Emergency Medicine at the University of Washington School of Medicine; and Mike Taigman, improvement guide for FirstWatch.