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BMC Health Services Research
Published in: BMC Health Services Research 1/2009

Open Access 01-12-2009 | Research article

Is there much variation in variation? Revisiting statistics of small area variation in health services research

Authors: Berta Ibáñez, Julián Librero, Enrique Bernal-Delgado, Salvador Peiró, Beatriz González López-Valcarcel, Natalia Martínez, Felipe Aizpuru

Published in: BMC Health Services Research | Issue 1/2009

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Abstract

Background

The importance of Small Area Variation Analysis for policy-making contrasts with the scarcity of work on the validity of the statistics used in these studies. Our study aims at 1) determining whether variation in utilization rates between health areas is higher than would be expected by chance, 2) estimating the statistical power of the variation statistics; and 3) evaluating the ability of different statistics to compare the variability among different procedures regardless of their rates.

Methods

Parametric bootstrap techniques were used to derive the empirical distribution for each statistic under the hypothesis of homogeneity across areas. Non-parametric procedures were used to analyze the empirical distribution for the observed statistics and compare the results in six situations (low/medium/high utilization rates and low/high variability). A small scale simulation study was conducted to assess the capacity of each statistic to discriminate between different scenarios with different degrees of variation.

Results

Bootstrap techniques proved to be good at quantifying the difference between the null hypothesis and the variation observed in each situation, and to construct reliable tests and confidence intervals for each of the variation statistics analyzed. Although the good performance of Systematic Component of Variation (SCV), Empirical Bayes (EB) statistic shows better behaviour under the null hypothesis, it is able to detect variability if present, it is not influenced by the procedure rate and it is best able to discriminate between different degrees of heterogeneity.

Conclusion

The EB statistics seems to be a good alternative to more conventional statistics used in small-area variation analysis in health service research because of its robustness.
Appendix
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Metadata
Title
Is there much variation in variation? Revisiting statistics of small area variation in health services research
Authors
Berta Ibáñez
Julián Librero
Enrique Bernal-Delgado
Salvador Peiró
Beatriz González López-Valcarcel
Natalia Martínez
Felipe Aizpuru
Publication date
01-12-2009
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2009
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/1472-6963-9-60

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