The Correct e- Mixtures (A fully validated EHR, the way forward) Brendan Delaney Guy’s and St Thomas’ Charity Chair in Primary Care Research

Requirements of observational research Data description Cohort management Data quality Data linkage –Semantic interoperability –Privacy –Matching

Requirements of interventional research Feasibility –Simple via distributed search –Complex via CPRD Recruitment –Privacy requirements Data management –eSource Adverse Event Reporting

What tools exist currently Legacy systems –Electronic Health Record Systems –Web based data collection forms and CTDMS –Clinical trial administration systems Projects in pilot and deployment CPRD Observational research platform Wellcome Trust eLung and RetroPro ePCRN FP7 TRANSFoRm

OBSERVATIONAL RESEARCH PLATFORM AND INCIDENT CASE RECRUITMENT

CPRD A Primary care clinical data warehouse Vision EHR (~20%) 600 clinics out 2500 clinics in the UK (out of clinics) provides a good sample UK primary care data Expanding to other three UK eHR vendors –50-60% coverage of UK pop –More streamlined and daily updates –Linkage

eLUNG and RETROPRO eLUNG: antibiotics vs standard care for COPD exacerbation RETROPRO: comparative study of different types of statins Recruitment at point of care (LEPIS) Feasibility studies funded by HTA and Wellcome Trust

The Approach Local autonomous agents to identify potential participants and facilitate their recruitment Interactive agents: with the physician Non-intrusive to the physician healthcare process Can easily be dismissed but yet has memory of GP actions Standardised and vocabulary controlled Scalable and highly configurable

Agent-based Technology Autonomous provides configurable flexibility adaptive to user requirements non-intrusive behaviour Asynchronous automation agents self-update their knowledge/registry configure for performance needs

Overall Architecture GPRD warehouse CTMS CCS LEPIS SiS Workbench Clinical trial data management system LEPIS: Local Eligible Participant Identification Service CCS: Central Control Service

FEASIBILITY AND RECRUITMENT OF PREVALENT CASES

 Funded by National Institutes of Health ‘Roadmap’ Program – pilot.  Facilitates recruitment by establishing a secure distributed query process for eHRs to identify eligible subjects  Proof of concept interoperable clinical trial data management system for Primary Care  NIHR NSPCR, Wellcome Trust (CPRD, ALSPAC), HTA, EU FP7 The electronic Primary Care Research Network (ePCRN)

Confidentiality and data security  Confidentiality - for subjects not having consented to use of their data for research  Search reports only ‘counts’ - NO DATA is extracted  Subjects are flagged locally  Security  OGSA-DAI & GTK4(certificates and authorisation)

Define eligibility criteria

Define the clinical problem semantically

Define further clinical problems, drugs or vital signs

Count eligible community subjects

Research network director approval tool

ADVANCED OBSERVATIONAL PLATFORM AND EMBEDDED ELECTRONIC CASE REPORT FORMS

Existing methods of trial data management are limited  No standardization of electronic case report forms (CRFs), timelines etc.  No reusability of data elements  No standardization of data structures  No automatic linkage of data elements and data structures

TRANSFoRm Consortium

Aims of TRANSFoRm To develop methods, models, services, validated architectures and demonstrations to support: –Epidemiological research using GP records, including genotype-phenotype studies and other record linkages –Research workflow embedded in the EHR –Decision support for diagnosis 22

Type 2 DM study Question: Relationship between SNPs and response to oral T2DM medication Genotype-Phenotype record linkage study –Privacy model –Record linkage (browsing, selecting, extracting) –Data quality tool –Provenance tool 23

GORD Treatment study Question: Effectiveness of on-demand v continuous PPI RCT with event-initiated patient-related outcome measures –Trigger within EHR –Semantic Mediator –eCRF tool (embedded in EHR) 24

Overall Architecture Distributed Nodes Middleware (Distributed Infrastructure) End User Tools and Services Support Services

Data source or collection Care Zone Non-care Zone Primary data Secondary data in DB Data use Research Zone Compatible use incompatibl e use Identifyng data Private data Identifiable data Genetic data Medical data Non- identifiable Data controller: Different national definitions for personal data, sensitive data, controller / processor, re-use of data for scientific purpose research

eSource two models

Discussion Ongoing mainly EU-funded projects will provide a stream of innovations in: –Computable representations of study designs –Interoperability –Data quality –Privacy, security and provenance –Workflow

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