Can Small-Area Analysis Detect Variation in Surgery Rates
The Power of Small-Area Variation Analysis
Bibliographic Data
| ID | 9100307 |
|---|---|
| Authors | Paula Diehr (University of Washington, corresponding author), Kevin C Cain (0000-0002-5665-6952, University of Washington, corresponding author), William Kreuter (University of Washington), Susan Rosenkranz, Susan E Rosenkranz (0009-0000-9686-5962, University of Washington, corresponding author) |
| Year | 1992 |
| Volume | 30 |
| Issue | 6 |
| Pages | 484-502 |
| Publication date | 1992-06-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/00005650-199206000-00003 |
| PMID | 1593915 |
| OpenAlex | W2013580744 |
| Language | EN |
| Citations received | 8 |
| References cited | 2 |
A variety of statistical methods can be used in small-area analysis to test whether there is more variation than would be expected by chance alone. However, the power of these methods to detect existing variation has never been studied. The authors used data regarding back surgery in Washington State to suggest several types of variation that might exist (alternative hypotheses), and then used computer simulation to determine the power, or the probability of detecting this variation. The chi-square test had the highest power of all methods considered against most alternative hypotheses. Power is higher if there are no multiple admissions, rates are higher, and counties have larger or similar population size. Problems of accounting for multiple admissions, adjustment for age and sex, choosing the optimum size of small areas, and detection of outliers also are discussed
Econometrics · Environmental health · Outlier · Population · Power (physics) · Statistical analysis · Statistical hypothesis testing · Statistical power · Statistics · Type I and type II errors · Variation (astronomy) · Computer Science · demographic modeling and climate adaptation · Demography · Healthcare Policy and Management · Mathematics · Medicine · Primary Care and Health Outcomes
Small Area Variation Analysis
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Physician Enthusiasm As an Explanation for Area Variation in the Utilization of Knee Replacement Surgery
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Hospitalizations for Ambulatory Care Sensitive Conditions and Quality of Primary Care
Diffusion of Information in Medical Care
| Unique citing works | 8 |
|---|---|
| Citations per year | 0,24 |
| Citation span | 1992 - 2011 (20) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 7 |