Clinical Decision Support (CDS) - It's the mythical creature that every healthcare administrator and informaticist is hunting, to help reduce costs and improve care. Loosely, it can be broken into a few different areas :
- Electronic decision support (e.g. CPOE Alerts to help prevent errors)
- Order / order set design (e.g. to help prevent errors / guide docs to evidence-based care)
- Workflow/documentation redesign (e.g. tools used to standardize high-risk decisions, e.g. procedure checklists)
- Workflow/protocol design (e.g. tools used to automate high-risk procedures)
One of the hardest to tackle is #1 - CPOE Alerts.
Are there too many, or too few? Everyone I know seems to be struggling with the same issue :
- Wanting to provide CPOE alerts to avoid errors, but
- Providing "too many alerts" could cause docs to ignore the "important alerts".
This phenomenon is loosely called alert fatigue, and has been fairly well-documented in literature as, paradoxically, a potential risk.
When you hear Informatics professionals discuss alert fatigue, the challenging part is actually knowing when alert fatigue exists. Docs sometimes complain about it, but the response docs get to this is often skepticism - After all, how can an alert be bad? Maybe the doc just complains too much? And who is going to turn off the alert? Is it safe to turn off the alert? What if this opens up other problems? When is it too much? When is it too little?
So when you ask docs to define alert fatigue, they typically use general, loose definitions, like :
- "It's when the system gives me too much information and I miss the important stuff."
- "It's when the system tells me about the Tylenol interacting with Colace, but I miss out on the Coumadin/Bactrim interaction."
- "It's when I can't read all of the alerts."
- "It's when I just keep clicking 'Bypass' without actually reading the alert."
- "It's when I just keep clicking 'Acknowledge' without actually reading the alert."
- "It's when I click 'bypass' within 3 seconds, so I know I didn't read the alert."
And recently, when I asked some informatics colleagues for their definition of alert fatigue, I again got a myriad of responses, followed by the same sort of response Supreme Court Justice
Potter Stewart gave in 1964, when defining "
obscenity" in the
Jacobellis v. Ohio case : "
I know it when I see it."
Unfortunately, this doesn't help much for those of us who are really working to combat alert fatigue.
The problem with all of these definitions is that they are fairly loose and subjective, and don't make a good litmus test to answer the question : Do you have alert fatigue?
So I'm going to use some reason and inference, to try to develop a better definition of alert fatigue that is quantifiable. (I used to be a mathematician/statistician, so please forgive the quasi-mathematical approach.)
Since it seems the "undesired scenario" nobody wants is made up of two steps :
- An EMR providing a confusing alert environment, and
- A doc displaying signs of poor response to that environment
So I'd like to submit two proofs, for two conditions which then go into a third proof. Here they are :
PROOF1 : "AlertOverload"
1. [AlertOverload] = [Bad] > [Good]
2. [AlertOverload] = [Noise] > [Signal]
3. [AlertOverload] = [Low-value alerts] > [High-value alerts]
4. [AlertOverload] = [Low-risk alerts] > [High-risk alerts]
5. [AlertOverload] = [# of low-risk alerts] > [# of high-risk alerts]
6. [AlertOverload] = [Number of low-risk alerts in a time period] > [Number of high-risk alerts in a time period]
7. [AlertOverload] = When the number of low-risk alerts exceeds the number of high-risk alerts for a given physician in a given time period
PROOF2 : "AlertLoss"
1. [AlertLoss] = [Bad] > [Good]
2. [AlertLoss] = [BypassedAlert] > [AcknowledgedAlert]
3. [AlertLoss] = [Number of bypassed alerts in a given time period] > [Number of acknowledged alerts in a given time period]
4. [AlertLoss] = When the number of bypassed alerts exceeds the number of acknowledged alerts in a given time period
If one were to accept proof #1 and #2 as true, then I would propose this final proof/definition of AlertFatigue :
PROOF3 : "AlertFatigue"
1. [Bad] = [Bad]
2. [AlertFatigue] = [Bad]
3. [AlertFatigue] = [AlertOverload] + [AlertLoss]
4. [AlertFatigue] = Exists when a given physician experiences [AlertOverload] and displays [AlertLoss] in a given time period
So
voila - My
proposed definitions :
- Alert Overload = When the number of low-risk alerts exceeds the number of high-risk alerts for a given physician in a given time period
- Alert Loss = When the number of bypassed alerts exceeds the number of acknowledged alerts in a given time period
- Alert Fatigue = "When a given physician experiences alert overload and displays evidence of alert loss in a given time period."
It's certainly not a universally-recognized definition, and I'm curious if other people are aware of any other professional, practical, policy-grade definitions that exist out there. Obviously, this definition now needs to be peer reviewed, tested, validated, and professionally accepted, so please don't use it in your own organization without consulting a legal professional, informatics professional, and your local regulatory agencies first.
Remember : As always, this discussion is for educational purposes only! Remember, your mileage may vary! Always enjoy thoughts, comments, and ideas!
