ABSTRACT
Executive Summary Beyond descriptions of medical error events, identifying their causes or consequences requires two complementary strategies. The first is the a priori causal attribution model for detecting known or “obvious” causes like failures of tools or technologies. The other is the epidemiological model of causal proof requiring some kind of analytical observational or experimental methodology based on fundamental, field, and clinical epidemiology experience and expertise. Why is this the case? Medical error can be viewed as a “disease” with its own origins, causes, spread, and means to control or prevent it.
