Prof. Dr. C. Ohmann Coordination Centre for Clinical Trials (CCCT) Heinrich-Heine-University Düsseldorf, Germany Primary and secondary use of EHR: Enhancing.

Prof. Dr. C. OhmannCoordination Centre for Clinical Trials

(CCCT)Heinrich-Heine-University

Düsseldorf, Germany

Primary and secondary use of EHR:Enhancing clinical research11 October 2007, Brussels

Data interoperability – short term practical solutions:

IT perspective

2

Prof. Dr. C. Ohmann, CCCT

Data interoperability – short term practical solutions : IT perspective

- aim of the presentation -

differences between medical care and clinical research

status of interoperability

benefits/challenges of interoperability

models and standards for data interoperability

examples of data interoperability

summary

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: different worlds

different targets

different regulations

different processes, actors, roles

different ontologies, classifications,

terminologies

different and distributed databases

different software solutions

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: different worlds

medical care

EHRbasic

research

clinical research

HL7 XDT DICOM

ICD OPS MeSH

....

CDISC SAS

MedDRA LOINC SNOMED ....

BSML MAGE-HL XMLgene

HGNC GO MGED ....

EHR and clinical research: current status of interoperability*

*Turisco et al., J Investig Med 2005; 53: 425-433

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: promising examples

single source project (CDISC/HL7)

centralized clinical research data warehouses- Mayo Clinic: Life Science System-IBM- Partners Health Care: University of Pittsburgh‘s Medical Archival System- Information Warehouse of Ohio State University Medical Center- Mount Sinai‘s General Medicine Outpatient database- etc.

Siemens Medical Solutions (TU Munich)

support of patient recruitment in clinical trials- Mayo Clinical System- Kaiser EHR System health connect

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: support of patient recruitment*

„Integrating EHRs with clinical trials has major potential to increase recruitment rate,

as could be demonstrated in first studies“

*Ohmann, Kuchinke:Meeting the challenges of patient recruitment. A role for electronic health records.Int J Pharm Med 2007; 21: 263-270

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: support of patient recruitment by a clinical trial alert system*

*Embi et al., Arch Intern Med 2005;165:2272-2277

parameter Clincal Trial Alert System

before after

no. of referrals (per month)

no. of enrollments (per month)

5.7

2.9

59.5

6.0

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: benefits of interoperability

similar needs and goals of healthcare industry and biopharmaceutical industry

improve patient safety and access to treatment

reduce costs for clinical trials(reduce redundant data entry, queries, source data

verification)

speed up trials by improving patient recruitment with access to clinical data

improve workflow and increase quality of clinical trials(e.g. reduce data transcription errors, improve

timeliness of data, facilitate information flow, increase personnel efficiency)

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: requirements/challenges

harmonisation of standards between health care and research

(common data standards, data transfer standards, standard interfaces, etc.)

common regulations and guidelines for privacy, security, record integrating

cooperation between biopharmaceutical and healthcare industries, between EDC and EHR System vendors

modification of regulatory guidelines to support the use of eSource

application of FDA 21 CFR part 11 and other rules/regulations fo EHR

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Prof. Dr. C. Ohmann, CCCT

investigator final report

monitor sponsorstudy manager data manager

integration

queries

Database

study software

Clinical research: flow of information and user rolesClinical research: flow of information and user roles

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Prof. Dr. C. Ohmann, CCCT

EC 2001/ 20/ EG Guideline (04.04.2001) EC 2005/28/EC Guideline (084.04.2005) Arzneimittelgesetz (12. Gesetz zur Änderung des AMG vom 06.08.2004) ICH E6: Good Clinical Practice (Mai 1996) ICH E9: Statistical Principles for Clinical Trials FDA 21 CFR Part 11: Electronic Records: Electronic Signatures (March 1997) FDA Guidance for Industry: Computerised Systems used in Clinical Trials (April 1999) Annex 11 – European Commission Directive

2003/ 94/ EC

Clinical research: regulatory requirementsClinical research: regulatory requirements

Industry standard:

GAMP Guide for the Validation of Automated Systems, Version 4

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Prof. Dr. C. Ohmann, CCCT

Technologies to capture clinical trial data*

Paper Medical Record Case Report Form (CRF)

- Paper CRF- eCRF

- Thin (Web Browser) Client- Thick Client

Diaries- Paper Diary- eDiary

- Connected System- Semi Connected System- Disconnected System

Electronic Health Records- Printed Records from an Electronic Health Record

(EHR) system- EHR System Used to Capture CRF Data

*CDISC Electronic Source Data Interchange Group:Leveraging the CDISC standards to facilitate the use of electronic source data within clinical trials, 2006

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: CDISC

http://www.cdisc.org

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: CDISC-standards

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: BRIDG*

A clinical research domain analysis model (UML) bridging organisations (CDISC, HL7, FDA, NCI) standards research and healthcare (CDISC and HL7)semantic foundation for application and message development in HL7, caBIG and CDISC

*Biomedical Research Integrated Domain Group (BRIDG) Model

http://www.bridgproject.org

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: HL7/IHE

Health Level 7 (HL7)

regulated Clinical Research Information Management (RCRIM)Technical Committee

(focus on standards that involve clinical research liaison to CDISC) version 3 based on Referenz Information Model (RIM) HL7 Clinical Document Architecture (CDA)

(exchange model for clinical documents)

Integrating the Healthcare Enterprise (IHE)

technical framework for implementation ofestablished messaging standards (e.g. HL7)

specification of Integration Profiles based onactors that interact through transactions

Integrated Profile „Refrieve Form for Data Capture (RFD)“

(gathering data with a user‘s current application to meet the requirements of an external system)

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Prof. Dr. C. Ohmann, CCCT

EHR and clinical research: solutions for interoperability

recording care data with EDC system and transfer to EHR

local site system with copy to EDC/EH

incorporation of EDC into EHR

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Prof. Dr. C. Ohmann, CCCT

The vision: EHR and electronic clinical research data capture*

*eClinical Forum and PhRMA EDC/eSource Taskforce:The future vision of electronic health records as

eSource for Clinical Research, Vers. 1.0, 2006

EHR and clinical research: - “single source project”*

*Kush et al., Implementing Single Source: The STARBRITE Proof-of-Concept Study. JAMIA 2007; 14:662-673

increasing efficiency in clinical research with an integrated trial platform based on

electronic and integrated data acquisition / management

optimized processes and information flows integrating clinical practice and clinical research.

Benefits for the Medical Center:

All data are electronically available, fast availablity

Research data are integrated High-quality data Adapted to workflow of users Standardization of internal processes Transparency Data security considers high efficiency Attractive for external Sponsors

Benefits for external sponsors:

All data electronical with Audit Trail Verifable quality High satisfaction of users

TUM

HIS

PACS

Clinical Routine

Processes

Clinical Research

Processes

Lab

Mapping/ Filtering

IntegrationEngine

Validation Buffer

Research-Portal = User Interface

EDC

Research

DB

Non-Image-Data Image-Data

External Center

Oct - 07 Siemens Medical SolutionsCopyright © Siemens AG 2007. All rights reserved.

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Prof. Dr. C. Ohmann, CCCT

Data interoperability – short term practical solutions: IT-perspective

- summary/ conclusions -

major differences between health care and clinical research

data interoperability of EHR and EDC rarely implemented

major benefits but demanding requirements/challenges for interoperability

systematic approaches for data interoperability between EHR and EDC available/under development and promising show-cases/proof-of-concept studies performed

major activities and ressources needed in the near future to come to practical solutions working in routine