Disagreeing with Myself

I had previously written about FMEA event severity. I won’t try to reproduce that entry here. The issue is how things are ranked in a Pareto.  For example …

Lab error Lab error Prob. Effect Effect Prob.
Patient sample mix up
(glucose assay)
0.01% Patient harm 0.0001%
Patient sample mix up
(newborn screening assay)
0.07% Patient harm 0.0000001%

The column Effect Prob. is the combination of the probability of the lab error with the probability that the two patients that were mixed up have such different values that patient harm is likely and that the clinician gives the wrong treatment based on the incorrect result. The issue is that I had previously argued that in ranking two items, when the probability of lab error is higher, even if the probability of patient harm is lower (true for newborn screening), this error should be ranked higher. (Assume that the processes for newborn screening and glucose assays are different so that there are two mechanisms for patient sample mix up).

Having read another blog, I was influenced by Bill Wilson and would keep the ranking as shown in the table. Also, this entry is a good explanation of the difference between an error and its potential effects.

The change in ranking is minor since for either case, one would try to ensure zero patient sample mix ups. But eventually, the money available runs out – hence the need for a Pareto.


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