I have previously commented why in a ranking system, one should rank severity and probability and not include detection in ranking, e.g., use criticality = [severity] x [probability of occurrence], rather then RPN (Risk Priority Number) = [severity] x [probability of occurrence] x [likelihood of detection].
This essay describes the perils of trying to achieve for FMEA, a numerical reduction in criticality (or RPN) after instituting control measures (mitigations). Reduction in RPN is recommended by the IHI (Institute for Healthcare Improvement) website, http://www.ihi.org/ihi/workspace/tools/fmea/.
If one focuses on severity and probability, almost all dangerous events will (by definition) have the highest (worst) severity and the lowest (best) probability. As an example, for patient death caused by wrong site surgery, one would expect this event to be exceedingly rare (in the once in 5-30 year category) as opposed to more frequent. Less severe events could be expected to be more frequent. For example, a patient that waits for an appointment more than the prescribed time could be a frequent event.
Criticality – (severity times probability of occurrence) is a semi quantitative measure. The Veteran’s Administration HFMEA has rankings of 1-4 for both severity and probability. This results in criticality from 1 to 16 to cover all cases. As mentioned above, in a criticality grid, the cell that contains 16 is likely to be devoid of events.
Although there are a few exceptions, in most cases, control measures reduce probability of occurrence, not severity. This means that for the most dangerous events, one would institute a control measure on a criticality of 4 (severity = 4, probability = 1) and wind up with a criticality that is still 4 (severity = 4, probability = 1). On the other hand, it is possible to improve the numerical criticality of non severe events such as the excessive patient waiting times. For example one could improve criticality from 4 (severity = 1, probability = 4) to criticality of 1 (severity = 1, probability = 1).
It’s not hard to see where this is going. If one starts to add up all of the criticality numbers and seeks to have an improvement of criticality due to control measures, then the most likely way to do this is to focus on the least severe events! This is the reverse Pareto and not a good idea.
Pareto analysis is an important part of FMEA. One must focus on items at the top of the Pareto chart, and know that the criticality numbers are not likely to change for these items, in spite of the fact the risk has been reduced. If one had a true quantitative ranking of probability of occurrence, this would be a different story, but quantitative rankings are not in use in healthcare.