title: Medical causation analysis heuristics.
abstract: Medical causation analysis determines whether or not a specific patient's illness is the result of a work site or an environmental exposure. In the past, this has been conducted implicitly with little analysis of the process per se. Our review suggests that there are several distinct heuristics that may be utilized; these include probability-based models, application of group-based data (epidemiology) to individuals, Bayesian analysis, a priori assumptions about which conclusions are better, and others. Some methods consider only work causes, whereas others explicitly consider alternative explanations. There are considerable differences among the methods in process, outcome, and fundamental assumptions. Formal assessment of the medical causation analysis process can provide insight and may ultimately lead to its standardization and improvement.
authors.affiliation: Department of Medicine, University of California, Los Angeles 90095-7027, USA.
authors.forename: P
authors.initials: P
authors.lastname: Harber
authors.forename: D
authors.initials: D
authors.lastname: Shusterman
mesh_terms: D015984:Causality; D003662:Decision Theory; D004812:Epidemiologic Methods; D006801:Humans; D016273:Occupational Exposure / Q000706:statistics & numerical data*; D011336:Probability; D012044:Regression Analysis; D012945:Social Values; D014942:Workers' Compensation / Q000592:standards / Q000706:statistics & numerical data*