1. Prof. Dr. C. Ohmann Coordination Centre for Clinical Trials (CCCT) Heinrich-Heine-University Düsseldorf, Germany Primary and secondary use of EHR: Enhancing clinical research 11 October 2007, Brussels Data interoperability – short term practical solutions: IT perspective

2. Prof. Dr. C. Ohmann, CCCT 2 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

3. Prof. Dr. C. Ohmann, CCCT 3 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

4. Prof. Dr. C. Ohmann, CCCT 4 EHR and clinical research: different worlds medical care EHR basic research clinical research HL7 XDT DICOM ICD OPS MeSH.... CDISC SAS MedDRA LOINC SNOMED.... BSML MAGE-HL XMLgene HGNC GO MGED....

5. EHR and clinical research: current status of interoperability* *Turisco et al., J Investig Med 2005; 53: 425-433

6. Prof. Dr. C. Ohmann, CCCT 6 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

7. Prof. Dr. C. Ohmann, CCCT 7 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

8. Prof. Dr. C. Ohmann, CCCT 8 EHR and clinical research: support of patient recruitment by a clinical trial alert system* *Embi et al., Arch Intern Med 2005;165:2272-2277 parameterClincal Trial Alert System beforeafter no. of referrals (per month) no. of enrollments (per month) 5.7 2.9 59.5 6.0

9. Prof. Dr. C. Ohmann, CCCT 9 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)

10. Prof. Dr. C. Ohmann, CCCT 10 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 health care 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

11. Prof. Dr. C. Ohmann, CCCT 11 investigator final report monitorsponsorstudy managerdata manager integration queries Database study software Clinical research: flow of information and user roles

12. Prof. Dr. C. Ohmann, CCCT 12 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 requirements Industry standard: GAMP Guide for the Validation of Automated Systems, Version 4

13. Prof. Dr. C. Ohmann, CCCT 13 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

14. Prof. Dr. C. Ohmann, CCCT 14 EHR and clinical research: CDISC http://www.cdisc.org

15. Prof. Dr. C. Ohmann, CCCT 15 EHR and clinical research: CDISC-standards

16. Prof. Dr. C. Ohmann, CCCT 16 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

17. Prof. Dr. C. Ohmann, CCCT 17 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 of established messaging standards (e.g. HL7) specification of Integration Profiles based on actors 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)

18. Prof. Dr. C. Ohmann, CCCT 18 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

19. Prof. Dr. C. Ohmann, CCCT 19 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

20. EHR and clinical research: - “single source project”* *Kush et al., Implementing Single Source: The STARBRITE Proof-of-Concept Study. JAMIA 2007; 14:662-673

21. 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 Integration Engine Validation Buffer Research-Portal = User Interface EDC Research DB Non-Image-Data Image-Data External Center Oct - 07 Siemens Medical Solutions Copyright © Siemens AG 2007. All rights reserved.

22. Prof. Dr. C. Ohmann, CCCT 22 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