From EHRs to Linked Data-Representing and Minining Encounter Data

7/28/2019 From EHRs to Linked Data-Representing and Minining Encounter Data

1/20

FromEHRstoLinkedData:

represen5ngandminingencounter

dataforclinicalexper5se

evalua5on

CarloTorniai

ShahimEssaid,ChrisBarnes,MikeConlon,StephenWilliams,JanosHajagos,ErichBremer,JonCorson-Rikert,MelissaHaendel


2/20

www.ctsaconnect.orgCTSAconnect

Reveal Connections. Realize Potential.

CTSAConnectProject

Goals: Iden?fypoten?alcollaborators,relevantresources,and

exper?seacrossscien?ficdisciplines

Assembletransla?onalteamsofscien?ststoaddressspecificresearchques?ons

Approach:

Createaseman?crepresenta?onofclinicianandbasicscience

researcherexper?setoenable

Broadandcomputablerepresenta?onoftransla?onalexper?se

Publica?onofexper?seasLinkedData(LD)foruseinotherapplica?ons


3/20

4/5/13 3



MergingVIVOandeagle-i

eagle-iisanontology-drivenapplica?on...forcollec?ngandsearchingresearchresources.

VIVOisanontology-drivenapplica?on...forcollec?nganddisplayinginforma?onaboutpeople.

BothpublishLinkedData.Neitheraddressesclinicalexper5se.

CTSAconnectwillproduceasingleIntegratedSeman5cFramework,amodularcollec?onofontologiesthatalso

includesclinicalexper?se

eagle-i

Resources

VIVO

People

Coordina?on

eagle-i

VIVO

Seman5c

Clinical

ac5vi5es


4/20



ISFClinicalmodule

ARG:Agents,Resources,Grantsontology

CM:Clinicalmodule

IAO:Informa?onAr?factOntologyOBI:OntologyforBiomedical

Inves?ga?ons

OGMS:OntologyforGeneralMedical

Science

FOAF:FriendofaFriendvocabulary

BFO:BasicFormalOntology


5/20



ISFClinicalmodule:encounter

ARG:Agents,Resources,Grantsontology

CM:Clinicalmodule

OGMS:OntologyforGeneralMedical

Science

FOAF:FriendofaFriendvocabulary


6/20



ISFClinicalmodule:encounteroutput

CM:ClinicalmoduleOBI:OntologyforBiomedical

Inves?ga?ons

OGMS:OntologyforGeneral

MedicalScience


7/20



ISF:Clinicalexper5serepresenta5on

Leveragingbillingcodestorepresentclinicalexper?se-exper?seasweightsassociatedtobillingcodes


8/20



Compu5ngandpublishingclinical

exper5se

Step1Aggregate

ClinicalData

Step2Compute

Exper5se

Step4Publish

LinkedData

Step3MapDatato

ISF


9/20



Aggregateclinicaldata

Step1Aggregate

ClinicalData

Step2Compute

Exper5se

Step4Publish

LinkedData

Step3MapDatato

ISF

Provider

ID

ICD

CodeValue

Code

Count

UniquePa5ent

Count CodeLabel

1234567 552.00 1 1Unilateralorunspecifiedfemoralhernia

withobstruc?on(ICD9CM552.00)

1234567 553.02 8 6Bilateralfemoralherniawithoutmen?on

ofobstruc?onorgangrene(ICD9CM

553.02)

1234567 555.1 4 1Regionalenteri?soflargeintes?ne

(ICD9CM555.1)

1234568 745.12 10 5Correctedtransposi?onofgreatvessels

(ICD9CM745.12)


10/20



Computeexper5se:weigh5ngthecodes

Step1Aggregate

ClinicalData

Step4Publish

LinkedData

Step2Compute

Exper5se

Step3MapDatato

ISF

CodeWeight=codefrequency*percentageofpa5ents

Aproviderwith500pa?entshasusedSyndactyly(ICD9:755.12)for30

uniquepa?ents75 ?mes

Percentageofpa?entswithcode:6%

Codefrequency:75/30=2.5Codeweight:6*2.5=15


11/20



Computeexper5se:footprint

Step1Aggregate

ClinicalData

Step4Publish

LinkedData

WegroupthecodesaccordingtothetoplevelICDcodeandgetthe

top10codestogeneratetheexper?sefootprintforeachprac??oner

Step3MapDatato

ISF

Step2Compute

Exper5se

ICDcode Weight

366.1 24.42

250 24

366.9 18.4

250.2 19.2

. .

ICDcode Weight

250 43.2

366 42.82

. .

. .

. .


12/20


13/20



PublishLinkedData

Step1Aggregate

ClinicalData

Step2MapDatato

ISF

Step4Publish

LinkedData

Step3Compute

Exper5se

LinkedData

cloud

SPARQL

Endpoints

OtherAPIs

TripleStoresSeveralmeans

toaccessand

querydata


14/20



Whatcanbedonewiththepublished

datasetSELECT ?expertise ?label ?weight!WHERE!{!obo:BFO_0000086 ?expertise.!!!!!?expertise_measurement obo:IAO_0000221 ?expertise.!!!!?expertise_measurement obo:ARG_2000012 ?label.!?expertise_measurement obo:IAO_0000004 ?weight. !!}!

Selecttheexper?sefor

provider

hp://ohsu.dev.eagle-i.net/i/1235281379

Selecttheweightandthelabel

formeasurementsrela?vetotheexper?se

Selecttheweightandthelabel

formeasurements

Theinforma?onisenoughtorepresentclinicalexper?seasa

tagcloud


15/20



SampleencounterdatapublishedasLOD

InferredTypes

Annota5onsand

Proper5es

HealthCareEncounter

InstanceURI


16/20

www.ctsaconnect.org CTSAconnectReveal Connections. Realize Potential.

Queryingthesampleencounterdata


17/20


Nextsteps:enhanceexper5se

representa5onbymappingICD9toMeSH


18/20


Nextsteps:enhanceexper5secalcula5on

Moresophis?catedalgorithmleveragingMeSHhierarchy


19/20


Beyondexper5se

Exper5selinkedtoMeSHwillenablemeaningfulconnec5ons

betweenclinicians,basicresearchers,andbiomedicalknowledge


20/20


Team

CTSA10-001:100928SB23

PROJECT#:00921-0001

OHSU:

MelissaHaendel,CarloTorniai,NicoleVasilevsky,Shahim

Essaid,EricOrwoll

CornellUniversity:

JonCorson-Rikert,DeanKra,

BrianLowe

UniversityofFlorida:

MikeConlon,ChrisBarnes,

NicholasRejack

StonyBrookUniversity:

MoisesEisenberg,Erich

Bremer,JanosHajagos

HarvardUniversity:

DanielaBourges-Waldegg

SophiaCheng

ShareCenter:

ChrisKelleher,WillCorbe,RanjitDas,Ben

Sharma

UniversityatBuffalo:

BarrySmith,Dagobert

Soergel

CTSAconnectproject

ctsaconnect.org

Theclinicalmodulesource:

hp://bit.ly/clinical-isf

CTSAconnectontologysourcehp://code.google.com/p/connect-isf/

Datasetandqueriesdocumenta5onhps://code.google.com/p/ctsaconnect/w/list

Resources

Support : NCATS through Booz Allen

Hamilton

CTSA 10-001: 100928SB23

Documents

From EHRs to Linked Data-Representing and Minining Encounter Data