I am interested in the philosophical answer to the question: can any complex process with a measurable outcome of success or failure truly have a zero error rate (ie 100% success and 0% failure). I accept that that one can measure outcomes of processes and usually observe a non zero error rate, though if you do observe a non zero error rate can you say with certainty that this is a sampling error.
As an example:
A health insurance company in Australia is proposing that it will not pay hospitals when certain adverse events happen (post operative infection or blood clots and about 100 other events) on the basis that these are considered 'highly preventable' and the observance of such events should be considered a 'mistake'.
It is true that applying certain preventative measures (prophylactic antibiotics or blood thinning agents) will reduce the risk of these relatively uncommon events though the relative risk reduction is moderate. Each of the listed events have an observed non zero rate of occurrence when all known prophylactic treatments are applied. The health insurers proposal is not to withhold payment if prophylactic measures are withheld but to withhold payment if the adverse event occurs - regardless of anything else. I understand that it should be sufficient to argue that non zero error rates are observed in optimal circumstances in all of the situations proposed, though I want to know if it can be argued in general that insistence on a a non zero error rate is asking for the impossible.