Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia.
BACKGROUND
Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference.


METHODS
Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart.


RESULTS
Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples.


CONCLUSIONS
The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit.
Knox
Stephanie A
SA
AIHW General Practice Statistics and Classification Unit, The University of Sydney, Sydney, Australia. sknox@med.usyd.edu.au
Chondros
Patty
P
D001315:Australia / Q000453:epidemiology; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D003710:Demography; D005194:Family Practice / Q000706:statistics & numerical data*; D005260:Female; D019538:Health Care Surveys / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D009017:Morbidity; D015588:Observer Variation; D010045:Outpatients / Q000145:classification / Q000706:statistics & numerical data