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PLoS Comput Biol. 2011 Aug;7(8):e1002141. doi: 10.1371/journal.pcbi.1002141. Epub 2011 Aug 25.

Using electronic patient records to discover disease correlations and stratify patient cohorts.

Author information

1
Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.

Abstract

Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systematic and non-cohort dependent manner. By extracting phenotype information from the free-text in such records we demonstrate that we can extend the information contained in the structured record data, and use it for producing fine-grained patient stratification and disease co-occurrence statistics. The approach uses a dictionary based on the International Classification of Disease ontology and is therefore in principle language independent. As a use case we show how records from a Danish psychiatric hospital lead to the identification of disease correlations, which subsequently can be mapped to systems biology frameworks.

PMID:
21901084
PMCID:
PMC3161904
DOI:
10.1371/journal.pcbi.1002141
[Indexed for MEDLINE]
Free PMC Article

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