Annals of epidemiology · 2014
Estimation of biomarker distributions using laboratory data collected during routine delivery of medical care.
Сравнительное исследованиеСтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Brookhart Maurice Alan, Todd Jonathan V, Li Xiaojuan, Reams B Diane, Pate Virginia, Kshirsagar Abhijit V
Аннотация
PURPOSE: To examine the extent to which commonly ordered laboratory values obtained from large health care databases are representative of the distribution of laboratory values from the general population as reflected in the National Health and Nutrition Examination Survey.
METHODS: Means of test values from commercial insurance laboratory data and National Health and Nutrition Examination Survey data were compared. Inverse probability of selection weighting was used to account for possible selection bias and to create comparability between the two data sources.
RESULTS: The average values of most of the laboratory results from routine care were very close to their population means as estimated from NHANES. Tests that were more selectively ordered tended to differ. The inverse probability of selection weighting approach generally had a small effect on the estimated means but did improve estimation of some of the more selected tests.
CONCLUSIONS: Commonly ordered laboratory tests appear to be representative of values from the underlying population. This suggests that trends and other patterns in biomarker levels in the population may be reasonably studied using data collected during the routine delivery of medical care.
METHODS: Means of test values from commercial insurance laboratory data and National Health and Nutrition Examination Survey data were compared. Inverse probability of selection weighting was used to account for possible selection bias and to create comparability between the two data sources.
RESULTS: The average values of most of the laboratory results from routine care were very close to their population means as estimated from NHANES. Tests that were more selectively ordered tended to differ. The inverse probability of selection weighting approach generally had a small effect on the estimated means but did improve estimation of some of the more selected tests.
CONCLUSIONS: Commonly ordered laboratory tests appear to be representative of values from the underlying population. This suggests that trends and other patterns in biomarker levels in the population may be reasonably studied using data collected during the routine delivery of medical care.