PNNL

Abstract

A number of methods have been proposed to detect an increasing shift in the incidence rate of a rare health event, such as a congenital malformation. Among these are the Sets method, two modifcations of the Sets method, and the CUSUM method based on the Poisson distribution. We consider the situation where data are observed as a sequence of Bernoulli trials and propose the Bernoulli CUSUM chart as a desirable method for the surveillance of rare health events. We compare the performance of the Sets method and its modifcations to the Bernoulli CUSUM chart under a wide variety of circumstances. Chart design parameters were chosen to satisfy a minimax criteria.We used the steady- state average run length to measure chart performance instead of the average run length which was used in nearly all previous comparisons involving the Sets method or its modifcations. Except in a very few instances, we found that the Bernoulli CUSUM chart has better steady-state average run length performance than the Sets method and its modifcations for the extensive number of cases considered.