190 Being a Doctor After Being a Patient
‘‘got comfortable with risk,’’ feeling that the existence of dangers did not
necessarily mean that the untoward event in question would occur. He
played a mind game with himself that in the end proved detrimental.
Being a physician screwed me. I play the scientific mind game. I
know that each act of sex is not going to transmit HIV. . . . It takes
maybe eighty episodes of sex to get pregnant once. I played the
numbers game with myself. After an unsafe episode, I could always
say to myself that the risk of getting HIV isn’t 100 percent. I’ve
heard it’s as low as 1 in 300 episodes of unsafe sex. I didn’t think it
was going to happen. It had no chance of happening. I didn’t see the
risk as being as high as lay people do.
Hence, Jeff used his medical knowledge against his own efforts to main-
tain his health. Medical knowledge not only can be ignored, but also
employed in the service of maladaptive denial.
Jeff went on to cite a common adage of medical training used to temper
subjective biases that overvalue the possibility of negative outcomes:
‘‘Common things happen commonly. Uncommon things happen uncom-
monly. You see zebra diagnoses’’—medical conditions that are rare, but
nonetheless described in detail in medical textbooks—‘‘only once in a blue
moon.’’
As a result of their professional training, many also distinguished, and
felt comfortable dismissing, small or negligible risks as ‘‘theoretical,’’
ignorable in day-to-day practice.
Thus, ill doctors, in facing knowledge of their disease, may either over-
or under-diagnose themselves, worrying too much or too little in evalu-
ating the risks they face. As described earlier with regard to self-diagnosis,
the difficulty of maintaining objectivity can lead to either of two extremes:
‘‘medical student disease’’ or ‘‘post-residency disease.’’
Yet even these doctors reported that despite their training, they were
not always clear what ‘‘the numbers’’ on diagnostic tests meant in terms of
clinical implications or prognoses. How much should one worry about a
40 percent risk of an event? These doctors, too, sought subjective inter-
pretations of quantitative data (e.g., conclusions that a particular percent-
age of risk was ‘‘good,’’ ‘‘bad,’’ or ‘‘great,’’ or that tissue was ‘‘dead’’ or
‘‘injured,’’ a more definitive status). Albert, who had an MI on the high-
way, wondered how to interpret percentages, and was surprised that
doctors didn’t anticipate his routine inquiries about such interpreta-
tions. For example, did a 10 percent occlusion mean a high or low risk of