Abstract
Health researchers commonly use logistic regression when profiling health providers.
Data from the patients treated by the providers are used to construct models predicting
the expected number of outcomes for providers and the ratio of observed to expected
outcomes (O/E ratio) used as a risk-adjusted measure of provider performance. Typically,
when calculating the standard deviation (SD) of O/E ratios, only O is treated as a
random variable. We used the propagation of errors (Pe) to derive a SD estimate that
accounted for variability in O and the estimate of E. Using data previously used to
profile Canadian cardiac surgery providers, we compared Pe-SD estimates with typical
SD (SDT) estimates. The SDT estimates and confidence intervals were always larger than the Pe estimates, most
notably when one or more providers treated a large proportion of the patients. This
was confirmed using computer simulations. SDT estimates should be abandoned in favor of more sophisticated estimates.
Keywords
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Article info
Publication history
Accepted:
January 10,
2003
Received:
September 17,
2002
Identification
Copyright
© 2003 Elsevier Inc. Published by Elsevier Inc. All rights reserved.