Although health care quality improvement has traditionally involved extensive work with
paper records, the adoption of health information technology has increased the use of electronic record and administra-
tive systems. Despite these advances, quality improvement practitioners now and for the foreseeable future need guid-
ance in defining populations of individuals for study and in selecting and analyzing sample data from such populations.
Statistical data analysis in health care research often involves using samples to make inferences about populations. The
investigator needs to consider the goals of the study, whether sampling is to be used, and the type of population being
studied. While there are numerous sampling strategies designed to conserve resources and yield accurate results, one of
these techniques—use of the finite population correction (FPC)—has received relatively little attention in health care
sampling contexts. It is important for health care quality practitioners to be aware of sampling options that may increase
accuracy and conserve resources. This article describes common sampling situations in which the issue of the finite
population correction decision often arises.