Sequential test selection in the analysis of abdominal pain

Numerous decision-making tools exist to assist physicians in diagnosis management. However, the accuracy of available clinical information is often ambiguous or unknown and current analytical models do not explicitly incorporate judgmentally defined information. A model encompassing both physician judgment and probability analysis was developed to accommodate such data. A problem requiring sequential diagnostic testing was structured utilizing the analytic hierarchy process (AHP). The case presented involved a patient complaining of upper abdominal pain who, after initial evaluation, did not need immediate surgery. Physicians were faced with identifying the optimal sequence of diagnostic testing. The criteria used for test selection included minimizing risk, patient discomfort, and cost of testing and maximizing diagnostic capability. Although at the onset the ''best'' test choice was unknown, the clinical picture indicated four test alternatives: upper gastrointestinal series (GI), abdominal ultrasonography (US), abdominal computed tomography (CT), and upper gastrointestinal endoscopy (END). Based upon the relative preferences of the criteria utilized, the AHP analysis indicated that upper GI series was the optimal first test. Given a negative test, posterior probabilities were calculated using Bayes' theorem, resulting in a new estimate of diagnostic capability. The AHP analysis was reiterated, identifying abdominal ultrasonography as the optimal second test. This analysis may be repeated as many times as necessary. Sensitivity analysis demonstrated that changing criteria preferences may alter the choice of tests and/or their sequence.