This paper studies a decision theoretic method for timing medical examinations. The specific model is motivated by screening asymptomatic individuals for hidden disease or risk-increasing conditions. Ideas and strategies may be applied more broadly to problems in which a stochastic process is monitored over time with a costly and possibly faulty data collection procedure. The decision space is modelled as a space of functions, termed screening intensity functions. Results include explicit rules for deciding whether or not an individual of given age and risk factors should be screened for a disease, and for deciding when an individual examined today should be examined again. Breast cancer screening is used as an illustration.
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Giovanni Parmigiani (1997) studied this question.
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