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P C Austin

Publications and source records attributed to P C Austin.

20 records · Page 2Linked to original sources
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Measuring population health: correlates of the Health Utilities Index among English and French Canadians.

This study used cross-sectional data from the 1994/95 National Population Health Survey (NPHS) in Canada. The objective of the study was to examine the relationship between several established correlates of health status in the general population and the Health Utilities Index (HUI), a multi-dimensional, preference-based measure of health status. Analyses were carried out separately for the English-speaking (n = 9,853) and French-speaking (n = 1,519) respondents. The index correlated strongly with self-ratings of health status and functional disability and varied as expected according to age, sex, and income. Subjects classified to different categories of chronic conditions reported different levels of health, as predicted. The HUI was also associated with the use of drugs and recent history of hospitalization. No major differences in the findings were observed between the two cultural groups. The results should be treated with caution due to the cross-sectional design and other methodological limitations of the study.

Activities of Daily Living↗
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An introduction to multilevel regression models.

Data in health research are frequently structured hierarchically. For example, data may consist of patients nested within physicians, who in turn may be nested in hospitals or geographic regions. Fitting regression models that ignore the hierarchical structure of the data can lead to false inferences being drawn from the data. Implementing a statistical analysis that takes into account the hierarchical structure of the data requires special methodologies. In this paper, we introduce the concept of hierarchically structured data, and present an introduction to hierarchical regression models. We then compare the performance of a traditional regression model with that of a hierarchical regression model on a dataset relating test utilization at the annual health exam with patient and physician characteristics. In comparing the resultant models, we see that false inferences can be drawn by ignoring the structure of the data.

Bias↗