Statistical Issues Involved in Medical Device Postmarketing Surveillance *

Abstract

This paper describes several statistical methods for analyzing medical device reports received by the Food and Drug Administration. The nonparametric regressions (polynomial, loess, kernel smooth, and cubic spline smoothing) are used as exploratory tools to evaluate trends in adverse event reports. Several statistical models, including simple Poisson, mixed binomial/Poisson, zero-truncated Poisson, and the negative binomial (compound Poisson), are used to monitor and to determine the upper 95% threshold values for reported adverse events during the study period. The hip implant injury data and the intravenous tube total (sum of death, device malfunction, and injury) data are used to illustrate our model fitting procedures. In this paper, only the numerator data (medical device adverse events), not the denominator data (medical device usage), are available in our statistical analysis. The possible effects of marketing time and other factors, which may be available in adverse drug reactions, are not available and are not considered for medical device adverse events in this paper.