Hello, and thanks for any help ahead of time.
I am a Medical Informatics student at OHSU and right now I am in a research
methods class at my institution: Geisinger.
For My project I wanted to investigate Alert Fatigue, suffering, myself,
from the condition.
So far most of what I can document comes from high-risk industries like
nuclear power, aerospace and the military. There is very little data in the med
As I begin the topic though, I can find very little nomenclature defined
Is there taxonomy of alerts? And as I start, I really have not found a
definition of an alert either.
Is there an official medical informatics definition of ‘alert’? I propose
the definition below, would you please comment on it?
Alert: “unsolicited 1 signal 2 of [possible/potential/definite] 3 error
(1) a self posted reminder, like ‘3 days until tax day’ would not be an
alert for my purposes.
(2) Any kind of signal or communication, it could be a vibrating watch, and
it does not have to be interruptive or require an action to continue.
(3) Many alerts are before the fact, and in medinfo most are trivial or
I would appreciate any help in pointing me to medical informatics articles
on experiments in alert fatigue. There is a lot of data about alerts, and
about overrides, but not a lot about the human behavior and what makes an alert
productive and what makes an alert cause other alerts to fail. I have found
nothing about how many alerts the mind can take before it zones out. And even
the articles that mention how many alerts were fired in a system and
overriden, there is nothing I have found yet about how many alerts per encounter, and
how many alerts per doc per day.
I have found a few articles that look at the fatigue effect itself. A 2008
preprint on overrides vs. number of alerts and a 2000 article that talks about
a drag effect of one alert on overall compliance. These are two of the
articles that I found that talk about alert fatigue:
There are 3 things that I would like to do in my project:
1: define an alert, and come up with taxonomy of alerts, there are some
textbooks that mention this.
2: present a simple count of alerts by taxonomy and by per doctor per day.
So far all I have found is number of alerts in a system over a month or a
year, nothing from the doctor point of view or using the doctor in the
3: start to define the fatigue factor itself. This is based on a hypothesis
that the more alerts the more overrides and the less time an alert is on
A simple approach to the third step would be percent of overrides morning
vs. afternoon, Monday vs. Friday as in the sample attached graph called
overrides. By pairing Monday morning with Monday afternoon etcetera, we can show
more significance, and by controlling for rates within each doctor
morning/afternoon//Monday-Friday we can get even more significance.
Any advice on the next step and other articles would be very welcome.