A Quantitative Methodology for Determining the Need for Exposure-Prompted Medical Monitoring

Abstract

Some toxic exposures to drugs or other environmental chemicals may create an increased risk of future disease for which periodic preventive medical screening might be desirable. However, many of these risks, even if unacceptable as a matter of public health policy, might still not be significant enough for medical monitoring (periodic diagnostic screening for latent illnesses or medical conditions) to be an appropriate medical intervention. This somewhat unintuitive, but statistically certain conclusion can be demonstrated in relatively simple mathematical terms. Accordingly, we introduce Bayes's Rule and decision analysis, a quantitative methodology commonly employed by medical practitioners. A review of current medical practices indicates that physicians decide whether to recommend monitoring for a particular exposed population by knowing the natural history of the disease and by first calculating the predictive value of a positive test (PPV), which will be one to five percent or greater for an endorsable monitoring exercise, absent exceptional circumstances. Rather than simply relying on the opinions of retained medical experts, this accessible quantitative method permits judges, jurists, and policymakers to more confidently and objectively decide whether medical monitoring is appropriate and necessary as a result of a specific chemical exposure.