Towards Na*onal Scale Clinical Data Warehousing: Experiences … › conferences2019 › fileseTELEMED19 › LuisMarcoRuiz… · • In November 2015 several projects started exploring

TowardsNa*onalScaleClinicalDataWarehousing:ExperiencesandPerspec*vesonDataReusefortheLearningHealthcareSystem

LuisMarcoRuiz,PhD1,2

1NorwegianCentreforIntegratedCareandTelemedicine

2MedizinischenHochschuleHannover

©LuisMarco-Ruiz2018

Background

•  ComputerScienJst,MScAppliedStaJsJcs,PhDHealthScience(MedicalInformaJcs)

•  Since2013workingfortheNorwegianCentreforE-healthResearch(NSE)

•  PostdoctoralresearchfellowandadvisorforclinicalinformaJonstandardizaJon

•  SemanJcInteroperabilitySpecialistattheHannoverMedicalSchool(HiGHmedproject)


Agenda• TheLearningHealthcareSystem• ConceptualizaJonofclinicaldatawarehousing(DW)• ComputaJonalmodelsinvolved•  InformaJonrepresentaJonforclinicalDW• KnowledgerepresentaJonforclinicalDW• ExperiencesinNorwayandGermany• OrganizaJonandchallenges• Acknowledgements




TheLearningHealthcareSystem

5

Evidence Based Medicine paradigm is facing many challenges (Djulbegovic 2009, Greenhalgh 2014). Among others, it is needed to decrease the 17 years that currently elapse since knowledge is generated until it is exploited at the bedside (Balas 2000, Friedman 2010). The IOM proposed in 2007 the Learning healthcare system as a paradigm to overcome these challenges. The LHS heavily relies on the use of technologies for (IOM 2007, ESF 2016): •  Implementing that knowledge to exploit latest evidence at several levels (clinicians, patients,

citizens, populations).

•  Providing communication channels and tools across the participants in care processes. •  Facilitating secondary use of data to generate new knowledge.

->data reuse networks and Clinical Data Warehousing (DW)

Budrionis A, Bellika JG. The Learning Healthcare System: Where are we now? A systematic review. J Biomed Inform 2016;64:87–92. doi:10.1016/j.jbi.2016.09.018. ©LuisMarco-Ruiz2018



ClinicalDataWarehousing•  IntherecentyearsthereuseofclinicaldatahasreceivedlotofaYenJonforimplemenJngtheLHS.

•  ThishasledtothebirthofmanydatareusenetworksandtheClinicalDataWarehousing(DW)discipline.

•  ClinicalDWhassignificantdifferenceswithrespecttotradiJonalenterpriseDW.•  WhileinenterpriseDWthefocusisondealingwithlargeamountsofdata,clinicalDWfocusesonpreservingthemeaningofdata.

DATA

CONTEXT

CLINICALDATA

CONTEXT

EnterpriseDW ClinicalDW

UsefulInformaJon

UsefulInformaJon


GeneraJngknowledgefromdata

8(AdaptedfromShethetal.2013)

DataAnalyJcs

SemanJcs(concepts)



ComputaJonalmodelsinvolved


RepresenJnginformaJonandknowledge

•  ThemeaningofinformaJonwhenaccessingitacrossdifferentinsJtuJonsmustbepreserved.

•  Datausers(e.g.researchers,healthindicators,etc.)needtobeabletounderstandthemeaningoftheinformaJonaccessed.

•  DatausersmaybelongtodifferentorganizaJons.

•  AlackofprecisionincommunicaJngthemeaningofadatasetmayresultininaccurateorerroneousconclusionsinqualitystudiesirrespecJvelyofthealgorithmused.

AVOIDAMBIGUITY!MAXIMIZEDATAQUALITY!

Dataaccessisnecessarybutnotenough…


•  InordertopreservethemeaningofinformaJonacrossdisparateorganizaJons,representaJonmechanisms(languages)forboththeinformaJonandthemeaningareneeded.

•  ClinicalInformaJonstandardsareusedtorepresentinformaJonstructures.

•  DescripJonLogicsareusedtodefineontologiesthatareformal(mathemaJcal)representaJonsofthesemanJcsconveyedbyclinicalinformaJonmodels.

RepresenJnginformaJonandknowledge

Informa*onrepresenta*on Knowledgerepresenta*on

Expressivityneedsofphenotypingalgorithms

(*)ConwayM,BergRL,CarrellD,DennyJC,KhoAN,KulloIJ,etal.AnalyzingtheHeterogeneityandComplexityofElectronicHealthRecordOrientedPhenotypingAlgorithms.AMIAAnnuSympProc2011;2011:274–83.




InformaJonrepresentaJonforclinicalDW


BuildingclinicalinformaJonmodelsforDW

16©LuisMarco-Ruiz2018

BuildingclinicalinformaJonmodelsforDW•  OpenEHRhasbeenselectedasstandardforrepresenJngclinicalinformaJoninEHRsby3outof4healthregions.

•  In2013theNaJonalICTHealthTrustcreatedtheNa*onalEditorialGroupforArchetypes(NRUA)forcoordinaJngthedevelopmentofthenaJonalrepositoryofclinicalmodels(archetypes).

•  InNovember2015severalprojectsstartedexploringthemappingofSNOMED-CTtowardsthemostcommonlyusedElectronicMedicalRecord(EMR)funcJonaliJes.

•  AmongthesuggesJonsofthedirectorateistheelicitaJonofclinicalinformaJonmodels(archetypes)andterminologyassetsforbuildingthepaJentsummaryforconJnuityofcare(SNOMED-CTvaluesets).


18


CKMClinicalModelSelecJon Extension/AdapJon

•  Archetypereusemustbeattemptedcheckingnationalandinternationalrepositories.

•  Often,CKMarchetypesneedtobeextendedtoaccommodatedatareuserequirements.

•  Thesetofarchetypeschosenmustguaranteethehighestlevelofreusability.

•  Archetypesshouldnotbeinfluencedbyaparticularreusescenario.

•  KeepanyneworextendedArchetypesunconstrainedasmuchaspossible.

Setofarchetypes


Marco-RuizL,MonerD,MaldonadoJA,KolstrupN,BellikaJG.Archetype-baseddatawarehouseenvironmenttoenablethereuseofelectronichealthrecorddata.IntJMedInf2015;84:702–14.doi:10.1016/j.ijmedinf.2015.05.016. ©LuisMarco-Ruiz2018

Agenda• TheLearningHealthcareSystem• ConceptualizaJonofclinicaldatawarehousing(DW)• ComputaJonalmodelsinvolved•  InformaJonrepresentaJonforclinicalDW• RepresentaJonsofsemanJcsinclinicalDW• ExperiencesinNorwayandGermany• OrganizaJonandchallenges• Acknowledgements


RepresentaJonofsemanJcsinclinicalDW




Heartdisease(disorder)SCTID:56265001

Familyhistorywithexplicitcontext(situaJon)SCTID:57177007

SCTconcept

…

SituaJonwithexplicitcontext243796009

Disease(disorder)64572001

AcuteHeartFailure AcuteMiocardiJs AtrialFibrillaJon ….

:(57177007|Familyhistorywithexplicitcontext(situaJon)|:246090004|Associatedfinding|=56265001|Heartdisease|)


Marco-RuizL,PedrinaciC,MaldonadoJA,PanzieraL,ChenR,BellikaJG.PublicaJon,discoveryandinteroperabilityofClinicalDecisionSupportSystems:ALinkedDataapproach.JBiomedInform2016;62:243–64.doi:10.1016/j.jbi.2016.07.011.

LinkedKnowledgeBase

LODCloud

sawsdl:modelReference


SOAP RESTful

SOAP

sawsdl:modelReference sawsdl:modelReference


TimeGene

Ontology

...SNOMED-CT ICDATC

BindingClinicalInformaJonModelstodomainontologies


0

50

100

150

200

250

300

1 2 3 4

Processing*me

Datasize

OWL2EL++

OWL2DL

OverdoseofformalsemanJcs

•  ComputaJonalrestricJons•  HumanrestricJons

Marco-RuizL,NicolaisenK,PedersenR,MakhlyshevaA,BakkevollPA.Ontology-basedterminologiesforhealthcare-ImpactassessmentandtransiJonalconsequencesforimplementaJon.vol.1.1sted.Tromsø:NorwegianCentreforE-healthResearch;2017.




NaJonwideclinicaldatawarehousinginiJaJves

LHS-toolbox(Norway)&HiGHmed(Germany)


ClinicalDWinNorway:theLHS-Toolbox

TheLHS-toolboxprojectisfundedbytheNorwegianResearchCouncilwith12,000,000NOK.TheprojectisbasedontheevoluJonoftheSNOWsystemfordistributed

computaJons.


LHSandSNOW

sdsdsds

©JohanGustavBellika2017

DeployedSnowsystemnodes•AcommonsystemforextracJonofdatafromlabsandhealthinsJtuJons•AcommonsystemforpresentaJonofhealthdata•AcommonsystemforcomputaJonofdistributedhealthdata

LHS-toolbox(SnowandEmnet)

GP1

Lab1

GPn

SNOW

Labn …

…

EMNET


31

ExtracJonandcaching

Integratedview

Transformation into openEHR extracts

GP1

Lab1

SNOW

TRANSFORMSTAGE

openEHRGP1

ExtracJonandcaching

Integratedview

SNOW TRANSFORM

STAGE

openEHRGP2

Archetypes

Archetypes


VirtualopenEHR-basedview

32

AQ

L openEHRpersistenceplatform

Extractserver

OpenEHRcompliantextract



OtheropenEHRsources

CDS

Clinicalresearch

Publichealth

Surveillance

Adapter(groupsdifferentarchetypesintotheemplatesandsubmitsthemtotheDW

usingit’sAPI)

Transform



VirtualopenEHRrepository



HiGHmedSummary

©HiGHmed2018

ClinicalDWinGermany(HiGHmed)

TheHiGHmedprojectisfundedbytheFederalMinistryofEducaJonandResearch

(BMBF)with30,000,000.Euro.ThisfundingschemewasdesignedtofundiniJaJvesthatwillfosterthedigitalizaJoninthefieldofmedicine

34HaarbrandtB,SchreiweisB,ReyS,SaxU,ScheithauerS,RienhoffO,etal.HiGHmed–AnOpenPlasormApproachtoEnhanceCareandResearchacrossInsJtuJonalBoundaries.MethodsInfMed2018;57:e66–81.doi:10.3414/ME18-02-0002. ©HiGHmed2018

PrivateandNetworkingPartners

Ada Health

AcademicPartners

AssociatePartnersHiGHmed-Partners

©HiGHmed2018

HiGHmed

36©HiGHmed2018

Requirements•  HealthInforma*onExchange:TogainaholisJcviewonpaJents’diseaseprogresses,informaJonhastofollowpaJentsacrossorganizaJonalboundaries.

•  Cross-EnterpriseDataAnalysis:TosupportallkindsofanalyJcsbasedonstructuredandunstructureddatafromclinicalcare,researchandtrialdatabases,andqualityregistriesinadistributedenvironment,wewanttosupportcomplexqueriesonagranularpa*ent-recorddatalevel.

•  Cross-EnterpriseKnowledgeManagement:TherearesJllbarrierstopracJce-basedevidenceandevidence-basedpracJceinhealthcare.Therefore,weneedtoiteraJvelyworkontheestablishmentofalearninghealthcaresystem,inwhichthelatestresultsofresearchanddataanalysisarereadilyavailabletocaregiversatthebedside,and,inturn,healthoutcomesofpaJentshelpresearcherstogainnewknowledge.

37©HiGHmed2018

BasicPrinciples•  Pa*entsfirst:InaddiJontofine-graineduseandaccesscontrol,paJentswillbeabletoviewandobtaintheirhealthdatathroughuserfriendlytools.

•  DataSafetyandPrivacy:DatasafetyandprivacyandthepaJents’rightofself-determinaJonarehighestprioriJes.Dataaccessisregulatedunambiguouslyinatransparentandtraceableprocess.

•  ClinicallyledDataModelling:HealthcareprofessionalsandresearchersalikeneedtobeacJvelyengagedtoestablishsemanJcinteroperability.Thiscreatesanewclinico-technicalrole,theso-calledDataSteward,responsibleforthemanagementandfitnessofdataelementswithintheclinicians.

•  Scalability:TechnicalsoluJonsmustbeopJmizedtohandlehighvolumesofcomplex,constantlychanginginformaJonandclinicalworkflows.

38©HiGHmed2018

TechnicalConcept•  EveryHiGHmedSitehasestablishedaDataIntegra*onCenteraccordingtocommonHiGHmedstandards

•  Establishsharedservicesanddatamodels

•  UseIHEXDSCross-EnterpriseDocumentSharingtoestablishvendor-neutralarchivesandtosupportcon*nuityofcareprocesses

•  WorkingonjointsemanJcsthroughopenEHR;withcommonArchetypesandAQLquerylanguageinterface

•  ImplementFHIRinterfacestoenhancedataexchangecapabiliJes(vendorneutral)

©HiGHmed2018

HiGHmedTechnicalInfrastructure

AuthenticationService

CrossCommunityAccess(XCA,XCPD)

FHIRTerminologyService PseudonymizationServiceKnowledgeService

XCAGateway

ManagementServiceClinicalKnowledgeManager

MedicalDataIntegrationCenterMHH

XDSAffinityDomain

openEHR/IHEXDSDataRepositories

SourceLa

yer

LocalInfrastructure&DataSources

HANNOVERMEDICALSCHOOL

Integrat

ionLa

yer

HIS

Registries

MPIDocumentRegistry

Audit

Norm

alizat

ionLa

yer

Federat

ionLa

yer

PEHR

MHHCDWH ETLTooling(MSSSIS)

SiteSpecificDataAnalyticsInterfaces

Registry Trial

EHR

Cross-ConsortiaService OMICSServices

NLPEngine

...AP

Is XDR FHIR AQL

Apps SMICS

VirtualOncoCenter

CardioAnalytics

CohortExplorer

Data

Marts

DataConverter(CDISC,FHIR,v2)

RIS

...

OMICsDataIntegrationCenterDKFZ/UKHD

XDR

openEHRenabledOMICsDB

SourceLa

yer


DKFZ/UKHD

Integrat

ionLa

yer

OTP

D:cipher ...

Norm

alizat

ionLa

yer

Federat

ionLa

yer

DKFZDataWarehouse

API

Apps Metadata

Catalogue


SAP

XDR FHIR AQL

SAP

Audit

VirtualOncoCenter

XCAGatewayXCAGateway

MedicalDataIntegrationCenterUMG

XDSAffinityDomain


SourceLa

yer


UMGöttingen

Integrat

ionLa

yer

HIS

Registries

MPIDocumentRegistry

Audit

Norm

alizat

ionLa

yer

Federat

ionLa

yer

PEHR

ETLTooling(MSSSIS)


Registry Trial

EHR

NLPEngine

APIs XDR FHIR AQL

Apps SMICS

VirtualOncoCenter

CardioAnalytics

CohortExplorer

Data

Marts


RIS

...

XCAGateway

MedicalDataIntegrationCenterUKHD

XDSAffinityDomain


SourceLa

yer


UKHeidelberg

Integrat

ionLa

yer

HIS

Registries

MPIDocumentRegistry

Audit

Norm

alizat

ionLa

yer

Federat

ionLa

yer

PEHR

ETLTooling(MSSSIS)


Registry Trial

EHR

NLPEngine

APIs XDR FHIR AQL

Apps SMICS

VirtualOncoCenter

CardioAnalytics

CohortExplorer

Data

Marts


RIS

...

XCAGateway

MedicalDataIntegrationCenterNewSite

XDSAffinityDomain


SourceLa

yer


AdditionalSite

Integrat

ionLa

yer

HIS

Registries

MPIDocumentRegistry

Audit

Norm

alizat

ionLa

yer

Federat

ionLa

yer

PEHR

... ETLTooling(...)


Registry Trial

EHR

NLPEngine

APIs XDR FHIR AQL

Apps SMICS

VirtualOncoCenter

CardioAnalytics

CohortExplorer

Data

Marts


RIS

...

DataLake DataLake

©HiGHmed2018

HiGHmedUseCases•  UseCase1Oncology:TheoncologyusecasewillhelpustoaddresschallengesinMedicalInformaJcswhenintegraJngomicsdatafromgenomesequencingandradiologyintoclinicalpracJce.New,mobilediagnosJcdevicesareexpectedtochangecurrentmedicalpracJceandresearchbycontribuJngtothelong-termmonitoringofpersonalhealthdataatanunprecedentedlevel.

•  UseCase2Cardiology:Withinthecardiologyusecase,wewillsystemaJcallyexploreandaddressITchallengesrelatedtotheintegra*onofdatafromwearableandconnecteddevicesintoourITarchitecture.

•  UseCase3Infec*onControl:TheinfecJoncontrolusecasewilldevelopanautomatedearlywarningandclusteranalysissystemtosupportthealgorithmicdetec*onofpathogenclusters.ItwillincludemulJdrug-resistantorganismswithinandacrossuniversityhospitals,theverificaJonofwhetherclustersrepresentoutbreaks,andtheidenJficaJonofpossiblecausesofoutbreaks.

10/03/19 41©HiGHmed2018


©HiGHmed2018

LHS-toolboxandHiGHmedsharerequirementsandchallenges


TechnicalrequirementsofclinicalDW

•  IntegraJonofheterogenousdatasourcesinstructureandmeaning•  Commonrepresenta*onformatsareneeded(openEHR,HL7FHIR,IHEXSD)•  Seman*cInteroperabilityisrequiredfortheconsistencyandmeaning•  Expressivequeries(e.g.Somekindof…)


HighlevelorganizaJonofteamsSharedforalltheproject

•  1Enterprisearchitect

•  1Projectmanager

•  2-4developers

•  1semanJcinteroperabilityspecialist

•  Others:Datastewards,PhDs,administraJonstaffetc.

Internaltoeachins*tu*on(dataintegra*oncenter)

•  Thestaffdependsdependingontheneedsandtheroleinthedatareusenetwork


OrganizaJonalchallengesinclinicalDW

•  Needformoreflexibilitymanagingprojectfunds.

•  ExcessofregulaJoninpublicfundedprojects->burocracyconsumeshugeamountofresources,slowprocurementprocess,slowhiringprocessesetc.

•  Thecomplexityofprocurementprocessesmayaffectsmall-mediumsizecompanies.

•  CollaboraJonamongdifferenthealthregionsmaybecomplex.

•  RecruithighlyskilledITprofessionalsforpublicprojectsisdifficult.WearenotcompeJJvewhencomparedwithprivatecompanies.Thismayaffectqualityofourdevelopments->wetrytoalleviatethisbypartneringwithvendorsthatareinterestedinourusecases/developments.


OrganizaJonalchallengesinclinicalDW

•  GDPR->currentlytheregulaJonisambiguousandnoclearanswersareprovided ->thisaffectsthewholedatareuseinfrastructure.

•  WeneedmoreefficientmechanismstoenablepaJentcontrol.

•  Theborderbetweenaresearchstudyandastudymeasuringhealthindicatorsisnotclear

->uncertaintyonhowtoproceed


LHS-toolboxteam

HiGHmedteam

Acknowledgements


Documents

Towards Na*onal Scale Clinical Data Warehousing: Experiences … › conferences2019 › fileseTELEMED19 › LuisMarcoRuiz… · • In November 2015 several projects started exploring