Having a discussion with someone about the previous blog entry prompted me to make some additions to the entry. While this person argued for assigning a probability to event 3 and not event 1, it occurred to me that event 2 should also have a probability assigned to it.
For reference, the following sequence of events, which is a laboratory example of patient sample mix-up is reproduced from before.
Assigning a probability to event 2 is difficult using fault trees since this involves estimating not just the probability of event 1 but estimating probabilities from all other events that could lead to event 2. One then has to mathematically add the probabilities (done through software, since this is complicated). No one in a laboratory would do this. However, there is another way; namely to follow the total error approach on CLSI EP21. Here, a method comparison experiment is performed and all “bad” results are counted even though their cause is not known. It is important to define how bad a result must be before it causes harm. This is what CLSI EP27 will do, when it’s released.