由大数据到智能医学课件

由大数据到智能医学由大数据到智能医学1Translational

MedicineTwo

strategic

requirement

Changeofmedicalmodel

Health

care

reformThe

engine

and

bridge

from

big

data

to

intelligent

medicineTranslationalMedicineTwostra2From

bench

to

bedsideFrom

big

data

to

intelligent

medicineGenomic

medicineTranslational

MedicineDigital

medicineBig

dataFrombenchtobedsideGenomicm3Intelligent

Medicine5P MedicinePredictive

medicine Preventive

medicine

Personalized

medicine Precision

medicineParticipatory medicineIntelligentMedicine5P Medicin4Intelligent

medicineRight

personRight

timeRight

treatmentRight

healthcareIntelligentmedicineRightpers5Big DataBig Data6Nature

498:

255

(2013)Nature498:255(2013)7THEBIG

CHALLENGES

OF

BIG

DATAAs

they

grapple

with

increasinglylarge

data

sets,

biologists

andcomputer

scientists

uncork

new

bottlenecks.Biologists

are

joining

thebig-data

club.With

the

advent

ofhigh-throughput

genomics,

life

scientists

are

starting

to

grapplewith

massive

data

sets,

encountering

challengeswith

handling,

processing

andmoving

informationthat

were

once

the

domain

of

astronomers

and

high-energyphysicists.Nature

498:

255

(2013)THEBIGCHALLENGESOFBIGDATA8Biomedical

big

dataBiological

dataMedical

dataReal

time

physiological

and

pathological

dateBiomedicalbigdataBiological9BiologicalDataBiologicalData10Standardizing

experimentalprotocolsCurrent

Opinion

inBiotechnology

19:354-359(2008)Systems

biology

aims

at

understanding

thebehavior

of

biologicalnetworks

by

mathematicalmodeling

basedon

experimentaldata.The

procedures

of

data

generation

are

insufficiently

documented

and

data

processing

is

arbitrary.Standardization

at

multiple

levelsis

essential.One

of

thekey

issues

isto

obtain

highly

reproducible

quantitative

data

for

mathematical

modeling.Standardizingexperimentalpro11Standardizationof

hypothesis-driven

research

insystems

biologyCurrent

Opinion

in

Biotechnology

19:354-359(2008)Standardizationofhypothesis-12Integration

of

complexmultidimensional dataNature

452:553

(2008)Integrationof complexmultid13OmicsGenomics

(

metagenomics

)Epigenomics

(

Rnomics

)TranscriptomicsProteomicsMetabolomicsInteractomicsPhenomicsOmicsGenomics(metagenomics)14Microbiome-wide

association

studies

link

dynamic

microbial

consortia

to

diseaseN

AT

U

R

E

5

3

5

：

9

4

，

2016

RapidadvancesinDNAsequencing,metabolomics,proteomicsand

computational

tools

are

dramatically

increasing

accessto

the

microbiome

andidentification

of

itslinks

with

disease.

In

particular,

time-series

studiesand

multiple

molecular

perspectives

are

facilitatingmicrobiome-wide

associationstudies,whichareanalogoustogenome-wideassociationstudies.

Earlyfindingspointtoactionableoutcomesofmicrobiome-wideassociationstudies,although

their

clinical

applicationhas

yet

to

be

approved.

Anappreciationofthe

complexityofinteractions

among

the

microbiome

and

the

host’s

diet,chemistry

and

health,as

well

asdetermining

the

frequency

of

observationsthat

are

needed

to

capture

and

integratethis

dynamic

interface,

is

paramount

for

developingprecision

diagnostics

and

therapies

that

arebased

on

the

microbiome.Microbiome-wideassociationst15Developing

a

microbial

Global

Positioning

System

to

stratifyindividuals

and

to

guide

their

treatmentDevelopingamicrobialGlobal16RnomicssnRNAsnoRNAmicroRNAlncRNACircular

RNARnomicssnRNA17OmicsGenomicsEpigenomicsTranscriptomicsProteomicsMetabolomicsInteractomicsPhenomicsOmicsGenomics18Maximizing

thepotential

of

themouseasa

modelorganismNature

Review/Genetics

10:372

(2009)Maximizingthepotentialofth19The

biological

organization

ofthe

'-omics'Thebiologicalorganizationof20由大数据到智能医学课件21Globalviews

of

the

human

interactomeGlobalviewsofthehumaninte22Medical DataClinicaldataStructured

medical

recordMedicalimageCohord

research

dataClinical

research

dataMedical DataClinicaldataCohor23Real

time

physiological

andpathological

date

from

in

situ sensorsWearable

devicesFilmChipsImplantable

chipsRealtimephysiologicalandpa24Fully

integrated

wearable

sensor

arrays（FISA

）for

multiplexed

perspiration

analysisN

AT

U

R

E

529:

5

0

9

(2016)Fullyintegratedwearablesens25Sensing

a

shift

in

health

careScience

TranslationalMedicine

7

(283),

283rv3,2015Sensingashiftinhealthcare26由大数据到智能医学课件27Epidermal

ElectronicsScience

333,

838

(2011)EpidermalElectronicsScience328LifeWatch获得远程患者可粘贴监测设备FDA许可瑞士远程心脏监测公司LifeWatch获得其LifeWatch

VSP(生命体征贴片）的FDA许可，是远程患者监测贴片。

LifeWatch尺寸小、易粘贴、穿戴舒适，与现在使用的为数众多的有线设备相比，限制更少。VSP可用于医院、救护车、护理和家庭环境。用一个舒适得多且非常便宜的方式替代多个硬件设备。同时设备还可定制参数、设定提醒，可配置数据并兼容EMR系统。LifeWatch是一次性粘贴带，包含检测心电图、心率、呼吸频率、体温、血氧饱和度和运动的传感器。他还包含电池，可通过设备连续收集数据五到七天。针对VSP系统的许可还包括无线连接血压腕带和用于处理及传输数据的安卓app。app还能监测患者，同时在发生异常生命体征时发出警报。LifeWatch获得远程患者可粘贴监测设备FDA许可瑞士29Soft,

stretchable,

fully

implantable

chipsSoft,stretchable,fullyimpla30Soft,

stretchable,

fully

implantable

miniaturized

chipsSoft,stretchable,fullyimpla31由大数据到智能医学课件32mHealth

taking

centerstageScienceTranslational

Medicine

7

(283),

283rv3,

2015mHealthtakingcenterstage33Heterogeneous

and

non-traditional

sources

of big

dataGenomics

Proteomics

Bioinformatics

14：

31–41

(2016)Heterogeneousandnon-traditio34Time

to

Integrate

Clinical

and

ResearchInformaticsScience

Translational

Medicine

2012

Vol

4

Issue

162162fs41Integration

of

clinical

andresearch

informatics

canstreamline

clinical

research,

patient

care,

and

the

building

of

a

learning

health

care

system.EHRsaredominatedbyunstructurednarrativedatathatarenot

available

for

research

orquality

improvement

efforts.Clinical

research

databases

—which

contain

well-defined

andstructureddata—arecreatedindependently,andclinically

relevantdatawithintheseresearchdatabasesarenotavailable

for

purposes

ofclinical

care.A

meaningfully

integrated

approach

to

clinical

and

research

data

informaticsisneededtopromoteimprovedhealthoutcomes

andmore

rational

allocation

ofhealth

care

resources.TimetoIntegrateClinicaland35TheElectronic

Medical

Records

and

Genomics

(eMERGE)

NetworkGenetics

in

medicine

15:

761(2013)The

Electronic

Medical

Records

and

Genomics

Network

is

a

National

Human

Genome

Research

Institute–funded

consortium

engaged

in

the

development

of

methods

and

best

practices

for

using

the

electronic

medical

record

as

atool

for

genomic

research.The

network

has

played

a

major

role

in

validating

the

concept

thatclinical

data

derived

from

electronic

medical

records

can

be

used

successfully

for

genomic

research.Current

work

isadvancing

knowledge

inmultiple

disciplines

at

the

intersection

of

genomics

and

healthcare

informatics,

particularly

for

electronic

phenotyping,

genomewide

association

studies,genomic

medicine

implementation,

and

the

ethical

and

regulatory

issues

associated

with

genomics

research

and

returning

results

to

study

participants.TheElectronicMedicalRecords36A

vision

and

a

prescription

forbig

data–enabled

medicineNATUREIMMUNOLOGY

16:

435

(2015)

Genetic,environmentalandsocioeconomic

factors

render

humanity

remarkably

diverse.‘-Omic’andsensortechnologiespermitthe

captureofthisdiversitywithunprecedented

precision.Leveragingthesetechnologiesinclinicaldecision

makingwillhelptobringaboutthelong-heralded

personalization

of

medicine.Avisionandaprescriptionfo37Big

data–enabledmedicineNATURE

IMMUNOLOGY

16:

435

(2015)Bigdata–enabledmedicine38From

Big

Data

to

Intelligent

MedicineData

qualificationand digitizationData

annotation

andknowledge

formationSimulation

and

mathematic

modelingPrecise

andsmart

actionFromBigDatatoIntelligentM39From

Big

Data

to

Intelligent

MedicineData

qualificationand digitizationData

annotation

andknowledge

formationSimulation

and

mathematic

modelingPrecise

andsmart

actionFromBigDatatoIntelligentM40由大数据到智能医学课件41Knowledge

management

systemA

knowledgemanagementsystemisdefinedasa

tool

that

selectively

provides

information

relevant

to

a

specific

to

the

characteristics

or

circumstances

of

a

clinicalsituation

but

which

requires

human

interpretation

for

direct

applicationpatient.Electronic

KMSs

includeinformation

retrieval

tools

and

knowledge

resources

that

consist

of

distilled

primary

literature

onevidence-based

practicesKnowledgemanagementsystemAk42Clinical

decision

support

systemA

clinical

decision

support

system

is

defined

asany

electronic

system

designed

to

aid

directly

inclinical

decisionmaking,in

which

characteristicsof

individualpatients

are

usedto

generate

patient-

specific

assessments

or

recommendations

that

are

then

presented

toclinicians

for

consideration.ElectronicCDSSsincludealerts,reminders,order

sets,drug-dosagecalculations,andcare-summary

dashboardsthatprovideperformancefeedbackon

quality

indicators

or

benchmarks.Clinicaldecisionsupportsyst43From

Big

Data

to

Intelligent

MedicineData

qualificationand digitizationData

annotation

andknowledge

formationSimulation

and

mathematic

modelingPrecise

andsmart

actionFromBigDatatoIntelligentM44Digital

liver

and

digital

manFederalregulatorshopecomputer

modeling

can

identify

drugsthatdamagetheliver

before

they

doharmDRUG-INDUCED

LIVER

INJURY

is

theleadingcauseofacuteliverfailure—andthe

single

greatest

reason

the

U.S.Food

andDrug

Administration

refuses

to

approve

adrug

or

pullsadrugfrommarket..TheFDAseemsto

agree

on

the

potentialtobuild

predictive

computermodelswhichcouldidentifyliver

toxicityproblemsearlyinthedrugdevelopment

process.Digitalliveranddigitalman45Clinical

decision

support

systemA

clinical

decision

support

system

is

defined

asany

electronic

system

designed

to

aid

directly

inclinical

decisionmaking,in

which

characteristicsof

individualpatients

are

usedto

generate

patient-

specific

assessments

or

recommendations

that

are

then

presented

toclinicians

for

consideration.ElectronicCDSSsincludealerts,reminders,order

sets,drug-dosagecalculations,andcare-summary

dashboardsthatprovideperformancefeedbackon

quality

indicators

or

benchmarks.Clinicaldecisionsupportsyst46Metabolomicsindrugdiscovery

and

precision

medicineNATURE

REVIEWS

DRUG

DISCOVERY

15

：473

，

2016

Metabolomicsisanemerging‘omics’scienceinvolvingthecomprehensivecharacterizationofmetabolitesandmetabolismin

biologicalsystems.Recentadvancesinmetabolomicstechnologiesare

leading

to

a

growing

number

of

mainstream

biomedical

applications.

Inparticular,metabolomicsisincreasinglybeingusedtodiagnosedisease,understanddiseasemechanisms,identifynoveldrugtargets,

customizedrugtreatmentsandmonitortherapeuticoutcomes.This

Reviewdiscussessomeofthelatesttechnologicaladvancesin

metabolomics,focusingontheapplicationofmetabolomicstowards

uncoveringtheunderlyingcausesofcomplexdiseases(suchas

atherosclerosis,

cancer

and

diabetes),the

growing

role

of

metabolomics

in

drug

discoveryandits

potential

effecton

precision

medicine.Metabolomicsindrugdiscovery47Metabolites

play

a

central

part

in

disease

developmentMetabolitesplayacentralpar48A

decisiontreeformetabolite-baseddrugdiscovery

anddevelopmentAdecisiontreeformetabolite49iKnifeMass

spectrometry-linked

intelligent

surgical

devicesiKnifecan

distinguish

cancer

and

normal

tissue

in

2

seconds

by

analyzing the

smell.NATURE

REVIEWS

GASTROENTEROLOGY

&

HEPATOLOGY

12

:459,2015iKnifeMassspectrometry-linked50iKnifeiKnife51iPad帮助外科医生更好的完成肝脏手术德国Bremen的一位外科医生在一台iPad和虚拟现实软件的帮助下，完成了一次肝脏手术。iPad的摄像头将实时的肝脏拍下来，并且会层叠在虚拟的3D模型上。通过iPad查看肝脏中各种构造，这样可以更好的完成手术並计算肝脏部分是否能提供充足的供血，评估剩下的器官能否维持患者的生命。iPad帮助外科医生更好的完成肝脏手术德国Bremen的一位52由大数据到智能医学课件53智能医疗系统电脑医生智能医院智能医联网智能医疗系统电脑医生54IBM

Watson

IBM

Watson’s

cognitive

computing

capabilities

has

been

growing

throughout

2014,followingthepublicly

disclosed

launch

ofitsWatson

Genomics

project

and

a

relationship

with

the

New

York

Genome

Center.

More

recently,

ithas

publicized

collaborations

with

theCleveland

Clinic

and

the

Mayo

Clinic.

The

Watson

Genomics

project

aims

tosignificantly

shorten

theweek

or

more

it

currently

takes

bioinformaticians

toexamine

a

patient’sunique

molecular

profile

and

identify

drugs

for

his

or

her

individual

treatment.IBMWatson IBMWatson’scognit55IBM

Watson

answersquestionsposed

in

natural

language,processes

Big

Data

to

uncover

new

patterns

and

learns

from

each

interaction.IBMWatsonanswersquestionsp56IBM

Wants

toLoadDoctor

Watsonto

Your

SmartphoneIBM

hasinvestedintoa

genetic

testingservices

laboratory

inabid

to

give

Watson,

its

self-learning

computing

system

that

can

be

controlled

by

human

voice,

the

ability

to

answer

questions

a

user

may

have

about

their

personal

health.TheinvestmentmakesPathwayGenomicsCorp.

oneofthebestcapitalizedhealthcarestartups,with

$80

million

raised

total,according

to

IBM.IBMWantstoLoadDoctorWatso57智能医疗系统电脑医生智能医院智能医联网智能医疗系统电脑医生58More

data-driven

digital

hospitalsEden

Estopace

|

2015-01-02Againstthebackdropofaglobaleconomythatisstill

struggling,healthcarecostisrisinganywhereintheworld,

whiledemandfor

better

health

outcomesis

also

increasing.ResearchfirmIDCpredictsthatoperationalefficiencyin

thehealthcaresystemwillbecomesocriticalthatby2016,

25percentof

hospitals

will

be

budgetingfor

a

data-driven

digital

hospital

strategy.“Aswe

know,

hospitalsare

inthemiddle

of

aprofoundtransformationandacrosstheglobewecanseealotof

modernizationinitiativesthatareaimedataccommodating

theevolvingroleofhospitalsinthehealthsystem,”said

SilviaPiai,ResearchManageratIDC,atarecentIDCHealth

Insights

webinar.Moredata-drivendigitalhospi59Transcutaneous

monitoringNATURE

COMMUNICATIONS

|

5:4779

|

DOI:10.1038/ncomms5779Transcutaneousmonitoring60Airstrip

TechnologiesRemotecontinuousvitalsign

monitoring

via

theiPhone.Thissoftwaredeliversreal-timedataabout

the

vital

signs(including

bloodpressure,heartrhythmand

rate,bloodoxygenlevel,andbody

temperature)ofanypatientwhois

inahospitalintensivecareunittoa

doctor’s

or

nurse’ssmart

phoneScience

translationalmedicine

2:16cm4

(2010)AirstripTechnologiesRemoteco61由大数据到智能医学课件62智能医疗系统电脑医生智能医院智能医联网智能医疗系统电脑医生63

Remote

clinics

and

education

centerLarge-scalehospitalCommunityhealth

servicescenterHouseholdsNew

model

of

health

care

services

Science

330:759

(2010)Remoteclinicsandeduca64河南智能医联网河南智能医联网65河南智能医联网省中心省村人省远程医疗协同平台国家远程医疗监管与服务中心远程急救服务点远程医疗网络视讯设备卫生信息平台急救平台市18家/个+++乡/50000+国家中心县医院乡/镇/村家庭/个人县118省医院市医院市医院二级分中心

二期：14Q2数据中心四期：15H2大数据、IMS

、双活一期：2011年118个远程点双活数据中心规划：覆盖基层、健康管理网络医院大数据合平台融规划：网络医院、远程门诊三期：15H118地市分中心五期：16大数据二期、双活完善业务上跨省覆盖、技术上4K/VR应用、体征监测/移动终端…河南智能医联网省中心省村人省远程医疗协同平台国家远程医疗监管66中国智能医联网国家远程医疗监管与服务中心省市远程医疗网络家庭社区大医院研究机构与产业中国智能医联网国家远程医疗监管与服务中心省市远程医疗网络家67EnvironmentGenotype

PhenotypeMolecular

Profiling

Mobile

Sensor

and

App

Clinical

PhenotypePersonal

BigData

PopulationBigData

DataMining

Simulation(CDSS)Data

Safety

Regulation

EthicSocioeconomicIntelligentMedicine

Computer

Doctor

Intelligent

Hospital

Intelligent

medical

NetworkFive

Circles

of Intelligent

MedicineEnvironmentGenotypePhenoty68谢谢谢谢69由大数据到智能医学由大数据到智能医学70Translational

MedicineTwo

strategic

requirement

Changeofmedicalmodel

Health

care

reformThe

engine

and

bridge

from

big

data

to

intelligent

medicineTranslationalMedicineTwostra71From

bench

to

bedsideFrom

big

data

to

intelligent

medicineGenomic

medicineTranslational

MedicineDigital

medicineBig

dataFrombenchtobedsideGenomicm72Intelligent

Medicine5P MedicinePredictive

medicine Preventive

medicine

Personalized

medicine Precision

medicineParticipatory medicineIntelligentMedicine5P Medicin73Intelligent

medicineRight

personRight

timeRight

treatmentRight

healthcareIntelligentmedicineRightpers74Big DataBig Data75Nature

498:

255

(2013)Nature498:255(2013)76THEBIG

CHALLENGES

OF

BIG

DATAAs

they

grapple

with

increasinglylarge

data

sets,

biologists

andcomputer

scientists

uncork

new

bottlenecks.Biologists

are

joining

thebig-data

club.With

the

advent

ofhigh-throughput

genomics,

life

scientists

are

starting

to

grapplewith

massive

data

sets,

encountering

challengeswith

handling,

processing

andmoving

informationthat

were

once

the

domain

of

astronomers

and

high-energyphysicists.Nature

498:

255

(2013)THEBIGCHALLENGESOFBIGDATA77Biomedical

big

dataBiological

dataMedical

dataReal

time

physiological

and

pathological

dateBiomedicalbigdataBiological78BiologicalDataBiologicalData79Standardizing

experimentalprotocolsCurrent

Opinion

inBiotechnology

19:354-359(2008)Systems

biology

aims

at

understanding

thebehavior

of

biologicalnetworks

by

mathematicalmodeling

basedon

experimentaldata.The

procedures

of

data

generation

are

insufficiently

documented

and

data

processing

is

arbitrary.Standardization

at

multiple

levelsis

essential.One

of

thekey

issues

isto

obtain

highly

reproducible

quantitative

data

for

mathematical

modeling.Standardizingexperimentalpro80Standardizationof

hypothesis-driven

research

insystems

biologyCurrent

Opinion

in

Biotechnology

19:354-359(2008)Standardizationofhypothesis-81Integration

of

complexmultidimensional dataNature

452:553

(2008)Integrationof complexmultid82OmicsGenomics

(

metagenomics

)Epigenomics

(

Rnomics

)TranscriptomicsProteomicsMetabolomicsInteractomicsPhenomicsOmicsGenomics(metagenomics)83Microbiome-wide

association

studies

link

dynamic

microbial

consortia

to

diseaseN

AT

U

R

E

5

3

5

：

9

4

，

2016

RapidadvancesinDNAsequencing,metabolomics,proteomicsand

computational

tools

are

dramatically

increasing

accessto

the

microbiome

andidentification

of

itslinks

with

disease.

In

particular,

time-series

studiesand

multiple

molecular

perspectives

are

facilitatingmicrobiome-wide

associationstudies,whichareanalogoustogenome-wideassociationstudies.

Earlyfindingspointtoactionableoutcomesofmicrobiome-wideassociationstudies,although

their

clinical

applicationhas

yet

to

be

approved.

Anappreciationofthe

complexityofinteractions

among

the

microbiome

and

the

host’s

diet,chemistry

and

health,as

well

asdetermining

the

frequency

of

observationsthat

are

needed

to

capture

and

integratethis

dynamic

interface,

is

paramount

for

developingprecision

diagnostics

and

therapies

that

arebased

on

the

microbiome.Microbiome-wideassociationst84Developing

a

microbial

Global

Positioning

System

to

stratifyindividuals

and

to

guide

their

treatmentDevelopingamicrobialGlobal85RnomicssnRNAsnoRNAmicroRNAlncRNACircular

RNARnomicssnRNA86OmicsGenomicsEpigenomicsTranscriptomicsProteomicsMetabolomicsInteractomicsPhenomicsOmicsGenomics87Maximizing

thepotential

of

themouseasa

modelorganismNature

Review/Genetics

10:372

(2009)Maximizingthepotentialofth88The

biological

organization

ofthe

'-omics'Thebiologicalorganizationof89由大数据到智能医学课件90Globalviews

of

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interactomeGlobalviewsofthehumaninte91Medical DataClinicaldataStructured

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recordMedicalimageCohord

research

dataClinical

research

dataMedical DataClinicaldataCohor92Real

time

physiological

andpathological

date

from

in

situ sensorsWearable

devicesFilmChipsImplantable

chipsRealtimephysiologicalandpa93Fully

integrated

wearable

sensor

arrays（FISA

）for

multiplexed

perspiration

analysisN

AT

U

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E

529:

5

0

9

(2016)Fullyintegratedwearablesens94Sensing

a

shift

in

health

careScience

TranslationalMedicine

7

(283),

283rv3,2015Sensingashiftinhealthcare95由大数据到智能医学课件96Epidermal

ElectronicsScience

333,

838

(2011)EpidermalElectronicsScience397LifeWatch获得远程患者可粘贴监测设备FDA许可瑞士远程心脏监测公司LifeWatch获得其LifeWatch

VSP(生命体征贴片）的FDA许可，是远程患者监测贴片。

LifeWatch尺寸小、易粘贴、穿戴舒适，与现在使用的为数众多的有线设备相比，限制更少。VSP可用于医院、救护车、护理和家庭环境。用一个舒适得多且非常便宜的方式替代多个硬件设备。同时设备还可定制参数、设定提醒，可配置数据并兼容EMR系统。LifeWatch是一次性粘贴带，包含检测心电图、心率、呼吸频率、体温、血氧饱和度和运动的传感器。他还包含电池，可通过设备连续收集数据五到七天。针对VSP系统的许可还包括无线连接血压腕带和用于处理及传输数据的安卓app。app还能监测患者，同时在发生异常生命体征时发出警报。LifeWatch获得远程患者可粘贴监测设备FDA许可瑞士98Soft,

stretchable,

fully

implantable

chipsSoft,stretchable,fullyimpla99Soft,

stretchable,

fully

implantable

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chipsSoft,stretchable,fullyimpla100由大数据到智能医学课件101mHealth

taking

centerstageScienceTranslational

Medicine

7

(283),

283rv3,

2015mHealthtakingcenterstage102Heterogeneous

and

non-traditional

sources

of big

dataGenomics

Proteomics

Bioinformatics

14：

31–41

(2016)Heterogeneousandnon-traditio103Time

to

Integrate

Clinical

and

ResearchInformaticsScience

Translational

Medicine

2012

Vol

4

Issue

162162fs41Integration

of

clinical

andresearch

informatics

canstreamline

clinical

research,

patient

care,

and

the

building

of

a

learning

health

care

system.EHRsaredominatedbyunstructurednarrativedatathatarenot

available

for

research

orquality

improvement

efforts.Clinical

research

databases

—which

contain

well-defined

andstructureddata—arecreatedindependently,andclinically

relevantdatawithintheseresearchdatabasesarenotavailable

for

purposes

ofclinical

care.A

meaningfully

integrated

approach

to

clinical

and

research

data

informaticsisneededtopromoteimprovedhealthoutcomes

andmore

rational

allocation

ofhealth

care

resources.TimetoIntegrateClinicaland104TheElectronic

Medical

Records

and

Genomics

(eMERGE)

NetworkGenetics

in

medicine

15:

761(2013)The

Electronic

Medical

Records

and

Genomics

Network

is

a

National

Human

Genome

Research

Institute–funded

consortium

engaged

in

the

development

of

methods

and

best

practices

for

using

the

electronic

medical

record

as

atool

for

genomic

research.The

network

has

played

a

major

role

in

validating

the

concept

thatclinical

data

derived

from

electronic

medical

records

can

be

used

successfully

for

genomic

research.Current

work

isadvancing

knowledge

inmultiple

disciplines

at

the

intersection

of

genomics

and

healthcare

informatics,

particularly

for

electronic

phenotyping,

genomewide

association

studies,genomic

medicine

implementation,

and

the

ethical

and

regulatory

issues

associated

with

genomics

research

and

returning

results

to

study

participants.TheElectronicMedicalRecords105