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Statistical Significance
We used a
widely-accepted statistical formula1 to calculate the
95% confidence level required to perform a one-proportion, two-tailed hypothesis
test to determine if our hospitals’ scores for each quality measure were
statistically the same or statistically different from the U.S.
average.
- A score that was significantly
higher than the U.S. average received a "Green" designation.
- A score that was significantly lower than the U.S. average
received a "Red" designation.
- A score that was not significantly different from the U.S.
average received a "Beige" designation.
We obtained the data used in our calculations from the Centers
for Medicare & Medicaid Services (CMS) Web site. We downloaded the scores
and the denominators for each CMS process of care measure for each BayCare
hospital. The denominator is the total number of patients who met the criteria
for inclusion in the measure calculation. From there, we calculated the
numerator (the number of patients who actually received the recommended care)
for each measure. Then, we entered the information into the statistical formula
to apply tests of statistical significance.
1. Breyfogle, F.W. (1999). Implementing Six Sigma -
Smarter Solutions Using Statistical Methods. New York, N.Y.: John Wiley &
Sons, Inc.
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