← Matt Didcoe

The post-cardiac arrest learning gap

The technology is already here. The culture isn't.

I recently joined Eoin Walker on the Pre-Hospital Care Podcast to talk about what happens to a cardiac arrest case after the resuscitation ends. This is the short version of that conversation.

The starting position is one I’d defend fairly hard. The outcome for the patient in front of you is mostly decided in the moment. Bystander CPR, time to first defibrillation and who delivered it, compression quality, the post-ROSC bundle you put together before handover. That’s the case. What gets decided after the case is the outcome for the next hundred patients, and the next thousand. That’s the whole argument for taking post-event review seriously.

The guidelines aren’t the problem

At a guideline level this is done. ILCOR, ERC, AHA and ANZCOR all recommend or suggest some form of structured debriefing, and the most recent ILCOR EIT review found it associated with either no effect or improvements in ROSC, survival to discharge and neurological outcome.

So why is adoption still so variable? The barriers aren’t scientific. They’re operational and cultural:

If I’m going to throw the fox into the hen house, it’s a leadership problem, top down. Most clinicians on road want to improve. The job of leadership is making sure they have the space to do it.

“Good data” is wider than the crew

When we talk about post-arrest data we tend to mean what the crew did on scene, but the 2024 Utstein update pushes us to look at the whole chain of survival, and a debrief should follow it. If nothing happened in the first ten minutes before we arrived, of course the outcome wasn’t great. Working forward from the call:

Why crew recall isn’t enough

I don’t mean any offence by this, but crew recall is consistently unreliable. That’s not because we’re a bunch of liars or psychopaths. It’s because these are high acuity, low occurrence events. Outside critical care and high acuity response roles, most crews work maybe one or two viable arrests a year. Then put that person under cognitive load, with adrenaline up, in a noisy room, with family screaming and crying and the dog running around, and their perception of time goes. Paramedics overestimate compression depth, get rate wrong in both directions, and therefore overestimate compression fraction. One simulation study found only around 10% of compressions satisfactory when crews self-reported high confidence, and that’s a simulation, not even a real scene.

Real-time feedback closes some of that gap during the arrest. The data afterwards closes the rest.

Data without context is its own hazard

This is the caution I’d want people to take away. It is very easy to sit in a well-lit office with your AirPods in and your favourite music on, look at a rhythm strip and some CPR feedback data, see the gaps, and conclude the crew didn’t do a very good job.

But that gap might be there because the patient’s brother, who’d just taken a frantic phone call, barrelled into the room asking what was happening, and the crew’s attention went to their own safety for thirty seconds. That’s not the crew’s fault. It also won’t appear in the case sheet, because when I’m writing a case sheet I’m documenting the care I gave the patient, not the family dynamics in the hallway.

Which is why an automated report landing in someone’s inbox at the start of their next shift, unreviewed and unqualified, can feel like an attack even when nobody meant it that way. Adding the context costs someone’s time, and I don’t think that time is optional.

Oceans of data, a puddle’s worth used

We’re collecting oceans worth of data and using a puddle’s worth of it. The control room audits for AMPDS compliance, but does that flow anywhere else? Does hospital outcome data come back to us? Everyone has their own silo, their own privacy constraint, their own system that won’t interface with the next one, so someone ends up pulling a spreadsheet. Integration is the challenge now, not collection.

Close behind it: who is actually responsible for getting the learning back to the crew? A dedicated resuscitation improvement team, or a clinical leader with five thousand other things on their list already?

Pushing data forward, not just backwards

The same argument runs in the other direction, towards the hospital. Most EMS monitors can transmit something in real time now, whether that’s vital signs, the ECG, or full audio and video alongside live vitals. (I quoted a smaller figure on the episode, which I think I’d picked up from an in-hospital study. The paper below is the better source.) A 2024 systematic review and meta-analysis in CJC Open pooled 17 observational studies covering 4,306 patients and found pre-hospital digital ECG transmission associated with door-to-device times around 33 minutes shorter, first medical contact-to-device around 25 minutes shorter, and mortality of 8.9% against 13.7%. It’s observational data with considerable heterogeneity on the time outcomes, so hold the causal claim loosely. But the direction is consistent across almost every study in it, the mortality finding had no meaningful heterogeneity at all, and the intervention is close to free.

The technology isn’t the blocker. The blocker is that the ambulance service and the receiving hospital often sit in different trusts, different parts of a health department, or in North America different private providers entirely, and everyone now has a cybersecurity position on what’s allowed on their network.

There’s a secondary use here I think is underrated. Live vital signs plus a senior clinician on the other end is genuinely useful remote decision support for a junior workforce. We lost a lot of senior clinicians around COVID, and with a paramedic career lifespan sitting around six or seven years, there are crews out there without anyone senior to lean on.

Technology or culture?

Eoin asked whether quality improvement here is a technology problem or a culture problem. It’s a bit of a false dichotomy, but if forced to pick, culture wins. The technology is largely already here. Monitors record event data, most services have an ePCR, interoperability standards exist, and machine learning is perfectly capable of drafting a report for a senior clinician to review and contextualise before it goes out. Implementation science and a genuine no-blame culture are the parts we’re still working on. Technology takes the friction out of the learning loop. Culture decides whether the loop actually runs.

The full episode is on the Pre-Hospital Care Podcast, part of the Medic’s Academy Network: Spotify or Apple Podcasts.

That’s the high-level version. A few things here deserve their own post: what a genuinely useful debrief report actually contains, the dispatch end of the chain, and the case for a structured resuscitation data set that’s comparable between services and eventually between countries. I’ll link them back here as they go up.