ArticleAmerican journal of public health1990
A small area simulation approach to determining excess variation in dental procedure rates.
Article in American journal of public health, 1990. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Does access to care affect outcomes of appendicitis in children?--A population-based cohort study.BMC health services research · 2010Article
- Is there much variation in variation? Revisiting statistics of small area variation in health services research.BMC health services research · 2009Article
- Overestimating outcome rates: statistical estimation when reliability is suboptimal.Health services research · 2007Article
- Distribution of physicians in Ontario. Where are there too few or too many family physicians and general practitioners?Canadian family physician Medecin de famille canadien · 1997Article
- Analysis of variations in mortality rates with small numbers.Health services research · 1994Article
- Using census and mortality data to target small areas for breast, colorectal, and cervical cancer screening.American journal of public health · 1994Article
- The effect of prescription size on acquisition of maintenance medications.Journal of general internal medicine · 1993Article
- Testing the null hypothesis in small area analysis.Health services research · 1992Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
All small area analyses need to compare the observed variability in rates to that expected by chance alone, but the expected variability is usually not known. This paper uses patient-level data for five dental procedures to simulate the distributions of the summary statistics that are usually generated in such studies. These statistics are found to vary greatly even under the "null hypothesis" that all dentists are using procedures at the same rates. The simulated dentist rates are compared to observed rates obtained in a different study. These findings illustrate problems that can occur in small area analysis studies, and emphasize the importance of using statistical techniques that are appropriate for the data that are to be analyzed. Investigators should make every effort to obtain patient-level data, or at least to understand the underlying distribution of the number of procedures per patient, to avoid mistaking significant deviations from an incorrect model as evidence for significant variation among small areas.
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