Decision analytic models are increasingly used to evaluate the costs and effects of medical technologies. To shed light on the fundamentals of decision analytic modeling, a set of three models for the evaluation of the effectiveness of cholesterol modification for the primary prevention of coronary heart disease is described in detail. The structure of the models is described and considerations are reviewed that affect this structure; potential pitfalls that may occur with the use of observational data to predict the effect of cholesterol modification on risk for coronary heart disease are discussed; the assessment of the validity of decision analysis models is discussed; and common sensitivity analyses performed for these models are reviewed. In conclusion, cholesterol modification has been one of the most intensively modeled preventive medical interventions. Incorporating more data from intervention studies, however, could substantially improve these models.
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