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

Francisco S Roque, Peter B Jensen, Henriette Schmock, Marlene Dalgaard, Massimo Andreatta, Thomas Hansen, Karen Søeby, Søren Bredkjær, Anders Juul, Thomas Werge, Lars J Jensen, Søren Brunak*

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftArtikelForskningpeer review

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.

OriginalsprogEngelsk
Sider (fra-til)e1002141
TidsskriftPLoS Computational Biology
Vol/bind7
Udgave nummer8
DOI
StatusUdgivet - aug. 2011

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