All improvement requires change, but not
all change results in improvement.1 The
key to identifying beneficial change is
measurement. The major components of measurement
include: (1) determining and defining
key indicators; (2) collecting an appropriate
amount of data; and (3) analysing and interpreting
these data. This paper focuses on the
third component—the analysis and interpretation
of data—using statistical process control
(SPC). SPC charts can help both researchers and
practitioners of quality improvement to determine
whether changes in processes are making a
real difference in outcomes. We describe the
problem that variation poses in analysis, provide
an overview of statistical process control theory,
explain control charts (a major tool of SPC), and
provide examples of their application to common
issues in healthcare improvement