Mining electronic health records: towards better research applications and clinical care

Peter B Jensen; Lars J Jensen; Søren Brunak

doi:10.1038/nrg3208

Mining electronic health records: towards better research applications and clinical care

Peter B Jensen, Lars J Jensen, Søren Brunak

797 Citations (Scopus)

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 u-derstanding 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.

Original language	English
Journal	Nature Reviews. Genetics
Volume	13
Issue number	6
Pages (from-to)	395-405
Number of pages	11
ISSN	1471-0056
DOIs	https://doi.org/10.1038/nrg3208
Publication status	Published - Jun 2012

Keywords

Biomedical Research
Electronic Health Records
Genetic Association Studies
Humans
Information Dissemination
Medical Records Systems, Computerized
Patient Care
Primary Health Care
Public Health

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1038/nrg3208

Cite this

@article{d9f5ec13a5db4a59b72c75b1e98ff8ae,

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 u-derstanding 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.",

keywords = "Biomedical Research, Electronic Health Records, Genetic Association Studies, Humans, Information Dissemination, Medical Records Systems, Computerized, Patient Care, Primary Health Care, Public Health",

author = "Jensen, {Peter B} and Jensen, {Lars J} and S{\o}ren Brunak",

year = "2012",

month = jun,

doi = "10.1038/nrg3208",

language = "English",

volume = "13",

pages = "395--405",

journal = "Nature Reviews. Genetics",

issn = "1471-0056",

publisher = "nature publishing group",

number = "6",

}

TY - JOUR

T1 - Mining electronic health records

T2 - towards better research applications and clinical care

AU - Jensen, Peter B

AU - Jensen, Lars J

AU - Brunak, Søren

PY - 2012/6

Y1 - 2012/6

N2 - 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 u-derstanding 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.

AB - 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 u-derstanding 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.

KW - Biomedical Research

KW - Electronic Health Records

KW - Genetic Association Studies

KW - Humans

KW - Information Dissemination

KW - Medical Records Systems, Computerized

KW - Patient Care

KW - Primary Health Care

KW - Public Health

U2 - 10.1038/nrg3208

DO - 10.1038/nrg3208

M3 - Journal article

C2 - 22549152

SN - 1471-0056

VL - 13

SP - 395

EP - 405

JO - Nature Reviews. Genetics

JF - Nature Reviews. Genetics

IS - 6

ER -

Mining electronic health records: towards better research applications and clinical care

Abstract

Keywords

UN SDGs

Access to Document

Fingerprint

Cite this