The Impact of Diagnostic Code Misclassification on Optimizing the Experimental Design of Genetic Association Studies
Author
Source
Journal of Healthcare Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-18
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
Diagnostic codes within electronic health record systems can vary widely in accuracy.
It has been noted that the number of instances of a particular diagnostic code monotonically increases with the accuracy of disease phenotype classification.
As a growing number of health system databases become linked with genomic data, it is critically important to understand the effect of this misclassification on the power of genetic association studies.
Here, I investigate the impact of this diagnostic code misclassification on the power of genetic association studies with the aim to better inform experimental designs using health informatics data.
The trade-off between (i) reduced misclassification rates from utilizing additional instances of a diagnostic code per individual and (ii) the resulting smaller sample size is explored, and general rules are presented to improve experimental designs.
American Psychological Association (APA)
Schrodi, Steven J.. 2017. The Impact of Diagnostic Code Misclassification on Optimizing the Experimental Design of Genetic Association Studies. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-5.
https://search.emarefa.net/detail/BIM-1181198
Modern Language Association (MLA)
Schrodi, Steven J.. The Impact of Diagnostic Code Misclassification on Optimizing the Experimental Design of Genetic Association Studies. Journal of Healthcare Engineering No. 2017 (2017), pp.1-5.
https://search.emarefa.net/detail/BIM-1181198
American Medical Association (AMA)
Schrodi, Steven J.. The Impact of Diagnostic Code Misclassification on Optimizing the Experimental Design of Genetic Association Studies. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-5.
https://search.emarefa.net/detail/BIM-1181198
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181198