Improving the power of genetic association tests with imperfect phenotype derived from electronic medical records.

ABSTRACT: To reduce costs and improve clinical relevance of genetic studies, there has been increasing interest in performing such studies in hospital-based cohorts by linking phenotypes extracted from electronic medical records (EMRs) to genotypes assessed in routinely collected medical samples. A fundamental difficulty in implementing such studies is extracting accurate information about disease outcomes and important clinical covariates from large numbers of EMRs. Recently, numerous algorithms have been developed to infer phenotypes by combining information from multiple structured and unstructured variables extracted from EMRs. Although these algorithms are quite accurate, they typically do not provide perfect classification due to the difficulty in inferring meaning from the text. Some algorith

SUBMITTER: Sinnott JA 

PROVIDER: S-EPMC4185241 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature