title: Mining electronic health records: towards better research applications and clinical care.
abstract: Clinical data describing the phenotypes and treatment of patients represents an underused data source that has much greater research potential than is currently realized. Mining of electronic health records (EHRs) has the potential for establishing new patient-stratification principles and for revealing unknown disease correlations. Integrating EHR data with genetic data will also give a finer understanding of genotype-phenotype relationships. However, a broad range of ethical, legal and technical reasons currently hinder the systematic deposition of these data in EHRs and their mining. Here, we consider the potential for furthering medical research and clinical care using EHR data and the challenges that must be overcome before this is a reality.
authors.affiliation: NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Peter B
authors.initials: PB
authors.lastname: Jensen
authors.forename: Lars J
authors.initials: LJ
authors.lastname: Jensen
authors.forename: Søren
authors.initials: S
authors.lastname: Brunak
mesh_terms: D035843:Biomedical Research / Q000379:methods* / Q000592:standards; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D056726:Genetic Association Studies / Q000379:methods; D006801:Humans; D033181:Information Dissemination / Q000379:methods; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*; D005791:Patient Care / Q000379:methods* / Q000592:standards; D011320:Primary Health Care / Q000379:methods / Q000592:standards; D011634:Public Health / Q000379:methods / Q000592:standards