Data quality and the spatial analysis of disease rates: congenital malformations in New York State

Spatial analyses of disease rates are increasing as the hardware and software used in disease surveillance and cluster investigations become more accessible and easier to use. The results of these analyses should be interpreted with caution since inconsistencies in health outcome reporting and population estimates may lead to erroneous conclusions. In this report we provide an example, using data on congenital malformations in New York State, to show how under-reporting of malformations by some New York City hospitals can lead to apparent clusters of malformations in other areas of the state where reporting is more complete. We illustrate how spatial analysis techniques can be used to locate under-reporting problems and determine the extent to which the problem exists.