The Yale Algorithm Special Workshop—Clinical

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Abstract
The assessment of causality in drug-event associations depends on the setting and purpose of such an assessment. Epidemiologists are primarily interested in population-based inferences about whether a given drug can cause a certain adverse drug reaction (ADR), and if so, how often it does so. Pharmaceutical industries and regulatory agencies are also concerned with population-based risks, but in addition must worry about individual cases. Clinicians are primarily interested in the individual, ie, whether a given drug did cause a certain adverse event in a particular patient. The authors describe an algorithm that provides specific, detailed criteria for ranking the probability that an observed untoward clinical manifestation was caused by a given drug. The criteria are subdivided into six axes of decision strategy with a built-in scoring system that ordinally ranks the probability of an adverse drug reaction as definite, probable, possible, or unlikely. To illustrate the use of the algorithm, the authors assess a reference case of pancreatitis occurring after administration of methyldopa.

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