The analysis of the frequency, distribution, and determinants of adverse drug reactions, medical errors, and other adverse events poses special challenges to the statistician. Although some errors or events might be frequent, those that injure patients are "rare". As the easily identified errors are eliminated using system redesign, the remaining risks will become even more rare, although much in need of identification and reduction. Generalizable studies, whether observational or controlled, usually require multicenter designs to obtain adequate samples. Clinicians often identify and/or classify events with error; their best judgments exhibit suboptimal reliability. Under these circumstances, simple statistical methods fail and results can mislead. Using both examples from the literature and simulations, we shall demonstrate the impact on variance estimates of clustering of patients across multiple centers, and the effect of misclassification of adverse events on design and analysis. The potential of confounding by center on the estimation of risk will be explained and explored. The implications of these statistical problems for the study, analysis, and reporting of risk and determinants of adverse events will be discussed.
Learning Objectives: The attendee will be able to identify the types of statistical problems inherent in epidemiologic analyses of the risks of adverse drug reactions and adverse medical events, and the implications for analysis, reporting, and critical appraisal of the literature.
Keywords: Biostatistics, Health Care Quality
Presenting author's disclosure statement:
Organization/institution whose products or services will be discussed: None
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.