George Rebane

[This introduction to modern medical decision making is intended as the first of a series of such essays on RR.  Subsequent pieces will cover simplifying nomograms (to avoid the arithmetic), personal utility (always subjective), and planning sequential diagnostics and treatments.  The aim here is to prepare the intelligent healthcare customer to communicate effectively with the healthcare industry and make prudent decisions for his own benefit.  A related background tutorial by the author for this piece is 'Hello Bayes Theorem!']

The healthcare industry woefully lags in many areas, but helping patients make correct decisions about their individual healthcare is where healthcare providers, led by attending physicians, are pathetically behind the times.  Let me explain.

Almost all of us have been in a clinic or doctor’s office and encountered a quandary on how to decide on what diagnostic or treatment procedure to choose next, or how to meaningfully interpret the results of a test that just came back.  The usual response of the layman in this situation is to give up trying to understand the gobbledygook from the healthcare professional, and just put everything into their hands.  Arguably for most people this is the wrong choice.  The medical profession has a terrible record of mistakes that result in tens of thousands of deaths annually (mortality rate), and even a much higher rate of morbidity (making things worse).

However, it doesn’t have to be that way if the patient has an elementary understanding of how uncertainties are measured and can be dealt with when they inevitably encounter their next critical decision in their own or a loved one’s healthcare.  Numeracy on the part of the patient is the only real requirement.

The Meaning of a Diagnostic Test

To firm up our understanding of this topic, let’s consider a couple of scenarios.  A patient could have a dreaded disease, say DD4, and has undergone a diagnostic test for that disease.  The attending physician reports that the results came back ‘positive’.  What to do now?  The first question should be ‘then what are the chances that I really do have DD4?’  Unfortunately, that question is seldom asked, and when asked, the answer at best is an ambiguous prevarication such ‘well, the chances are pretty good that you’re suffering from DD4.’  Now what are you supposed to do with ‘pretty good’.

On another occasion a patient’s blood test comes back during a routine physical, and the physician notices an anomaly that may harbinger DD9.  He points this out to the patient, says not to worry, ‘it’s probably nothing, just a normal aberration’, and tells the patient that they’ll repeat the test six months from now just to make sure.  We all know what the patient does with that kind of a report – he goes away and worries for six months, making all kinds of plans for the contingency that he really does have DD9.

In both scenarios a more complete report would have served the patient better in deciding what to do next or how to respond.

To begin, the patient can do his part with a little homework on the reliability of tests in general.  No test is 100% reliable in the sense that if it comes back ‘positive’ or ‘negative’, one is then assured that they do or don’t have some dreaded disease.  This means that the chances, or probability, of suffering from DD is somewhere between zero and one (or 100%).  One reason for this is that most tests come back with a number – e.g. your PSA test for prostate cancer returns 5.7 – instead of just ‘positive’ or ‘negative’.  It is where the physician or the clinical literature puts the threshold on such a number that determines their pronouncement ‘positive’ (if the PSA is at or above, say, 4.0) or ‘negative’ (if it is below 4.0).

But let’s not forget that just getting a positive/negative report on a test result doesn’t answer the burning question on the patient’s mind – ‘given the test result, what’s the chance that I have the DD?’  To answer that we have to encounter some more realworld details about test results.  The easiest way is to look at the following graphic from Wikipedia (Figure 1) that summarizes the clinical data for a specific test given to diagnose a specific DD.

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