Multilevel collaborative platforms Linking Diabetes Medical Records to other sources Mark McGilchrist Senior Research Fellow University of Dundee Record-Linkage,

Multilevel collaborative platforms

Linking Diabetes Medical Records to other sources

Mark McGilchristSenior Research FellowUniversity of Dundee

Record-Linkage, BIRO Academy 2Copyright 2011 M. McGilchrist, University of Dundee

Register

Primary Care

Clinics

BMILifestyl

eRx

Lab

Eye

FootRenal

Hospital

CommunityPharmacy

Rx

Discharge

Education &

Social Care

DeathCertification

CancerRegistry

GeneticData

(Research)


Interoperability

Static, long-term collaborations requiring time and resource

SemanticsSyntax

SemanticsSyntax

Shared


Interoperability

Updating an existing collaboration is time-consuming and costly, so use RL


Register

Research

Recipient

Offers dynamic binding (loose coupling) of existing systems to create approximations to new systems, quickly and at low cost

Record-linkage

HospitalRecipient

Recipient

Must handle heterogeneity


Considerations?

ConsiderationsEthicsData Protection LawContractual arrangementsValiditySpecificationAuthorisationRegulatory complianceConfidentiality frameworkSecurityShared syntaxShared semanticsShared linkage standardsData flow modelsRecipient facilitiesDisclosure controlProvenanceBusiness modelsPolitical models

Local, national, internationalAre all different!


Ethics

Single/Multi-centre RECs?

Diverse data sources?

ClinicalBiobankLocal government authorityGovernment agency

So who decides, who takes responsibility?Benefits vs risks?


Data Protection Law

EU DirectiveNational LawsBorder flows


Contractual arrangements

Transfer agreements:

DataMaterialsRecipient obligationsPublication of results

Time consuming, but necessary?How do we hold others to account?


Specification


ActorsInteractionStandardsTools and Coding systemsTechnology UMLS®

Authorisation


Access committee - centralised or decentralised?Peer reviewSupporting documentation (Ethics, protocol, ...)Legal persons?How is decision made? Transparent?

Confidentiality Framework


Purpose: primary or secondary useConsent: implicit, explicit, informedAnonymous dataPseudonymous/coded dataPolicyResponsibilityData flowPETsTrustData controllers, processors, ownersGenetic data

Security


Data transfer routesPayload encryption: algorithms and protocolsCertificate authorities

Syntax and semantics


Data heterogeneityCommon Information modelVocabulary and terminology servicesOntology-driven mappingHealthcare data interchange standards

Linkage standards


Local/study identifiersInstitutional identifiersNational identifiersMappings

Probabilistic matching generates a ‘standard’

Recipient facilities


Recipient facilities

Terminal accessVirtual hardwarePre-defined software configurationsDisclosure control

Data

Data Flow Models


Model A – central conduit (relies on TTP)Model B – data bus (relies on Technology)Model C – multi-institutional

Each model has its own unique set of issues, e.g.:

Where is trust placed?Authorisation?Business obligations?Specification?Contracts?...

RulesRules

Architecture

System

Behaviour is sensitive to:

SystemsSystem rulesSystem relationshipsRelationship rules


Recipient

Model A – central conduit


TTP(PETs, Trust, controller)

DS DS DS

Recipient

Usually involves transfer of complete, identifiable data to a TTP. TTP releases anonymised, linked data to the recipient. The TTP may provide authorisation facilities. Resources concentrated at the TTP.

Identifiable data

Anonymised/anonymousdata

Model B – data bus


DS DS DS

Recipient

Encrypted identifiersand data

Does not involve the transfer of directly identifiable data.Encryption schemes permit SQL join type operations, but data flows are not known in advance and may move between sources.Although field-level RBAC may be implemented, actual queries cannot be anticipated.Authorisation is coarse grained.All parties are trustedResource requirements unclear

Model C – Multi-institutional


DS DS DS

Recipient

Link

Anonymised/Anonymous data

Mappings

Data sources only transfer anonymised data.Data flow is well defined in advanceActual requests are actionedAuthorisation is fine-grained.Trust levels required are lowDS must be resourced

Multi-level combined models


DS DS DS

TTP DS

Recipient

Link

Example: Local - WTCCC


NHS SCI-DC Pheno

HIC Geno

Analyst

Link

WTCCC

WTCCC Access committee

HIC Access committee

...

Example: National - SFHS


Family Pheno Geno

Recipient

Link

Anonymised/Anonymous data

Mappings

HE PAC

ConsiderationsEthicsData Protection LawContractual arrangementsValiditySpecificationAuthorisationRegulatory complianceConfidentiality frameworkSecurityShared syntaxShared semanticsShared linkage standardsData flow modelsRecipient facilitiesDisclosure controlProvenanceBusiness modelsPolitical models

Local, national, internationalAre all different!


Growth of Record-Linkage


Local

International

Pragmatic

Formal: modelling/standard

National

Scottish Health Informatics Programme


An ambitious, Scotland-wide research platform for the collation, management, dissemination and analysis of Electronic Patient Records (EPRs).

Partners:

University of DundeeUniversity of EdinburghUniversity of GlasgowUniversity of ST. AndrewsInformation Services of NHS Scotland (ISD)

Scottish Health Informatics Programme


Aims:

Provide access to an exciting new national research facility, firmly embedded within and supported by NHS Scotland, providing the basis for numerous future studies using EPRs. Create a research portal for EPRs already held by NHS Scotland that will provide rapid, secure, access to the type of data that clinical scientists require. Develop and evaluate systems that work across institutional boundaries to allow linkage between large, federated, third party research datasets and the NHS research portal

Example: European - TRANSFoRm


Generic, European-wide research platform based in primary care and validated with two use cases:

GWAS: genetic complications of diabetesRCT: QoL/outcomes in GORD

5-year formal approach to development and implementation:

Modelling of use cases and clinical researchRequirements analysis of data sources (clinical and genetic)Comparability of data sourcesData access and interchange modelOntology-driven integration and interoperabilityVocabulary servicesMeta-data repositoryRegulatory, security, confidentiality and provenance frameworks

All standards-based.

Multilevel collaborative platforms

Linking Diabetes Medical Records to other sources

Mark McGilchristSenior Research FellowUniversity of Dundee

[email protected]


mailto:[email protected]

Documents

Multilevel collaborative platforms Linking Diabetes Medical Records to other sources Mark McGilchrist Senior Research Fellow University of Dundee Record-Linkage,