Improving the accuracy of severity indexes: exceptions to the rules

This study explores the difference between additive and non-additive indexes in measuring the severity of myocardial infarction. It shows, as an example, the fallacy of adding severity scores in a straightforward manner. An additive severity index was constructed from the judgments of seven experts. The experts also identified several exceptions to the additive index. The study used the exceptions to modify the additive index and produce a non-additive severity index. The non-additive severity index explained 36% more of the variance in the severity judgments made by five physicians and two nurses on 50 hypothetical cases than the additive index did. In addition, the non-additive index was 3% more accurate in predicting in-hospital mortality of 7,500 patients with myocardial infarction. When the study reduced the noise in the data by ignoring 1,200 rare cases in which stable estimates of mortality rate were unavailable, the prediction of the non-additive index was 13% more accurate than that of the additive index. Statistical tests showed that the differences between the additive and the non-additive indexes were significant at an alpha level below 1%. The practical implications of non-additive severity indexes are discussed. Researchers and physicians who assess the severity of myocardial infarction should systematically explore exceptions that may improve the accuracy of prediction of an additive index.