An example of a study objective, for sample size estima-
tion purposes, is detecting the effect of a QI intervention
before and after the implementation of an intervention.
More specifically, the interest is in comparing pre-inter-
vention baseline performance to post-intervention per-
formance. Alternatively, interest may center on the im-
pact of the intervention by comparing the effect on a
group of patients that received a QI intervention (e.g.,
educational materials) vs. a group of patients that did not
receive the intervention being studied. Sometimes, pub-
lished information can be used to help estimate the size
of the sample required, but such information is often not
available, and we need to make educated guesses about
the value of key study parameters(a parameter is “a nu-
merical property of a population, such as its mean”) [3].
The most important aspect of the sample size estimation
process is clear specification of the study objective. A
sample size “power” calculation [6] requires some in-
formation about several parameters. The statistical power
approach is used when objectives are formulated as hy-
pothesis tests.