Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48479
Title: Is there much variation in variation?: revisiting statistics of small area variation in health services research
Authors: Ibá̃ez, Berta
Librero, Julián
Bernal-Delgado, Enrique
Peiró, Salvador
Gonzalez Lopez-Valcarcel, Beatriz 
Martínez, Natalia
Aizpuru, Felipe
UNESCO Clasification: 531207 Sanidad
Keywords: Estadísticas sanitarias
Sistema sanitario español
Issue Date: 2009
Journal: BMC Health Services Research 
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.
URI: http://hdl.handle.net/10553/48479
ISSN: 1472-6963
DOI: 10.1186/1472-6963-9-60
Source: Bmc Health Services Research[ISSN 1472-6963],v. 9
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