I gave a presentation about error grids at the Quality in the Spotlight conference in Antwerp, Belgium. Someone asked a question about the meaning of error limits which I tried to answer but since then have thought of a better answer, which follows.
Assume there is a line of cars waiting in a tunnel and ahead of the cars there is a car spewing out carbon monoxide. A CO sensor goes off in the tunnel and emergency workers arrive. All engines are shut off and car occupants are examined.
Car 1 – the occupant has a high CO reading and is unresponsive. He is taken to a hospital and after a long treatment recovers.
Car 2 – the occupant has a much less CO than car 1, but it is still high. He has slight CO poisoning symptoms and is treated.
Car 3 – the occupant has a 5% CO less than car 2, and no symptoms.
Car 4 – the occupant has a detectable CO but much less than car 3 and no symptoms.
Car 5 – the occupant has zero CO and no symptoms.
If another CO meter had been reading zero CO for cars 1-5, one could postulate some error grid limits.
The error for the bad meter for car 1 would be at the “C” zone limit – meaning that this amount of error is life threatening.
By looking at the symptoms and CO levels for cars 2 and 3, one could set the “A” zone limit between the two error values for cars 2 and 3. That is, this error limit is just when harm starts to be observed.
However, it is important to think about what is happening in cars 3 and 4. In both cases there is harm but no clinical symptoms. Harm is occurring at a subclinical level – but it is still harm! So to set the limit where harm is detectable is somewhat arbitrary. The only case where there is no harm is where there is no error – for car 5. Thus, it always makes sense to have as little error as possible and hence state of the art limits are recommended. These arguments would translate to other diseases and tests.
NOTE: Okay, some COHb is normal in blood, but that’s my example.