1. Strictly confidential NHIN Slipstream Project Executive Briefing Meeting – Hand-out materials April 9, 2007 This presentation discusses a NHIN Architecture Prototype project made possible by a contract from the Office of the National Coordinator for Health Information Technology (ONC), DHHS. The content is solely the responsibility of the authors and does not necessarily represent the official view of ONC.

2. Copyright © 2007 Accenture All Rights Reserved. 209 Apr 2007 Setting the context – –Background – what is the NHIN –The objectives for the NHIN Slipstream project What is the current state and context for today –What did we accomplish with NHIN Slipstream project –Use case activities – Matching patients to trials, Clinical data capture, Drug safety surveillance –The current environment: The NHIN – RHIO shift Advice and recommendations –Process to follow on opportunities –Opportunities going forward Meeting Agenda

3. Copyright © 2007 Accenture All Rights Reserved. 309 Apr 2007 Background 2005 – National Health Information Network (NHIN) contracts awarded by Office for the National Coordinator for Healthcare Information Technology (ONCHIT) to build prototypes. 2006 – Slipstream established by Accenture (one of the contract winners) to understand the NHIN capabilities and understand what is needed to fully leverage them from a pharma perspective. 2006 – AZ, BMS, Pfizer, Wyeth invest $150K each to participate. 2007 – Slipstream Phase 1 completed, NHIN prototype demonstrations conducted, Slipstream use cases made public.

4. Copyright © 2007 Accenture All Rights Reserved. 409 Apr 2007 There are local, regional, and national components of the Health Information Exchange landscape – Due to gaps in records of care and lack of standards in local health records, regional and nationally exchanged health records have greater potential to support continuity of care and other critical use cases. Local National Regional Local Illustrative NHIN RHIO Local Local health record examples – hospital systems, outpatient, physician offices, home care, pharmacy, labs, etc.

5. Copyright © 2007 Accenture All Rights Reserved. 509 Apr 2007 The US Federal Healthcare IT Landscape AHIC Breakthrough Workgroups & Use Cases Guides ONC Activities Consortia-based NHIN Prototype Contracts HISPC Privacy NHINHITSP Standards CCHIT Certifications IBMNorthrup GrummanCSC Accenture NHIN Forum: Public Comment on Requirements and Policy Issues Consumer Empowerment Electronic Health Records Bio Surveillance

6. Copyright © 2007 Accenture All Rights Reserved. 609 Apr 2007 Characteristics of Accenture’s NHIN Prototype Characteristics of health care markets: –Rural –Have RHIOs but do not have regional information infrastructures for sharing health data –Hospital and provider systems are all different with few systems based on federal health standards Accenture Consortium Technical Partners: –Accenture –Oracle –Cisco –Quovadx –Apelon –Orion Health –Sun Microsystems Appalachian Region Tennessee Kentucky Virginia West Virginia CareSpark from the tri-cities region of northeastern Tennessee and southwestern Virginia; West Virginia eHealth Initiative; Eastern Kentucky Regional Health Information Organization –CGI-AMS –Creative Computing Solutions –eTech Security Pro –Intellithought –Lucent Glow –Oakland Consulting Group

7. Copyright © 2007 Accenture All Rights Reserved. 709 Apr 2007 Why are these national efforts important to Pharmaceutical companies? Able to determine answers to critical questions - –What are the Pharma-specific use cases that could leverage Clinical Data Exchanges and a Nationwide Health Information Network? –How can this lead to improvements – reduced costs or improved insights – through- out the development, administration, patient safety and surveillance of drugs and medical products? –What additional value can be derived through data capture and integration with new sources of data (e.g., genotypic data)? –What are the obstacles and key enablers to the pharmaceutical industry realizing the benefits of this emerging infrastructure? Legal and Policy Standards Data Ownership Financing Governance Technical

8. Copyright © 2007 Accenture All Rights Reserved. 809 Apr 2007 The NHIN Slipstream Project Context Why: –Recognition that the Pharma industry is not fully contributing to activities and opportunities in the Health Information Technology (HIT) arena –Recognition that Pharma companies can help to define the key HIT use cases for enabling clinical research and monitoring the safety and effectiveness of medicines –Assessment that the Pharma industry would have greater impact if it were able to speak with a unified voice in national, regional, and local HIT efforts –Desire to identify opportunities to pilot the use case concepts and help move toward realizing the value offered by HIT Who: –Four pharmaceutical companies: AstraZeneca, Bristol-Myers Squibb, Pfizer, and Wyeth –Steering committee with working groups comprised of subject matter experts –Meetings & deliverables facilitated by Accenture What: –Ongoing monitoring of national & regional HIT activities, including the NHIN prototypes –List of use cases relevant to Pharma, prioritized down to the top three –Three detailed use cases, including value propositions and proof of concept opportunities –Internal / external communication planning

9. Copyright © 2007 Accenture All Rights Reserved. 909 Apr 2007 Setting the context – –Background – what is the NHIN –The objectives for the NHIN Slipstream project What is the current state and context for today –What did we accomplish with NHIN Slipstream project –Use case activities – Matching patients to trials, Clinical data capture, Drug safety surveillance –The current environment: The NHIN – RHIO shift Advice and recommendations –Process to follow on opportunities –Opportunities going forward Meeting Agenda

10. Copyright © 2007 Accenture All Rights Reserved. 1009 Apr 2007 Clinical ResearchClinical DevelopmentRegulatory / Safety Commercial 1.Genetic Association and Linkage Analysis 2.Clinical Validation – Target, Biomarker, and Diagnostic 3.Clinical Trial Execution a.Connect Patients to Trials b.Data Collection & Mgmt c.Investigator Services d.Compliance e.Placebo Populations 4.Clinical Trial Simulation 5.New Indication Identification 6.Interim analyses 10.Post-Marketing a.Safety / Adverse Event Monitoring b.Pharmaco- vigilance c.P-Epi & Data Mining 11.Manufacturer’s Recall 12.Pharmaco- economics 13.Marketing Comparative Studies 14.Pharmaceutical/ Disease Management Programs 15.e-Prescribing The group looked across the Pharmaceutical value chain and determined a set of priority Use Cases 7. Personalized Medicine – Pharmacogenomics 8. Outcomes Studies 9. Disease and Care Management Modeling Prioritized High-Level Use Cases

11. Copyright © 2007 Accenture All Rights Reserved. 1109 Apr 2007 Connecting Patients to Trials Use Case Scope: –Determine value-added outputs and services that can be provided to patients, physicians, investigator sites, and clinical trial sponsors based on improved matching of patients to trials via electronic health record information. Value-added Services Identified: –Direct to Patient Clinical Trial Matching Service Compare a patient’s health record and indication preferences and against pre-screening criteria of all registered clinical trials. Provide report of matching trials to patient with information about how to get screened for the trial. –Service for Site / Physician to Match Patients to Trials Allow investigator sites and physician offices to run a report that will match their patients to clinical trials for which the patients meet the pre-screening criteria based on the patients’ electronic health records. –Clinical Trial Recruitment Feasibility Analysis Service Allow clinical trial sponsors to determine the patient populations that meet the pre-screening criteria of their trials, stratified by location –Inform Investigator of Qualifying Patients in His/Her Geography Allow trial investigator sites to run reports that will identify the physicians in their geographic area that currently treat patients that match the pre-screening criteria of a trial being run at their sites. Key Obstacles: –Privacy & Consent: policies regarding patient consent and privacy protections to share health information for purpose of clinical trial matching. This includes agreement of who can access identified and de-identified patient data. –Standards: terminology standards necessary to create consistent, computable, interoperable health record data for comparison against structured clinical trial pre-screening criteria –Data Ownership & Governance: agreements of who owns patient data, how it will be governed, whether it can be aggregated and by whom, and who can use it for what purposes.

12. Copyright © 2007 Accenture All Rights Reserved. 1209 Apr 2007 Post-Marketing Drug Safety & Surveillance Use Case Scope: –Evaluate how electronic health records can be used to improve post-marketing safety and surveillance of medicines, including receipt, evaluation, and reporting of individual adverse events, signal detection for patterns of drug effects, and longitudinal data mining for hypothesis testing and pharmacoepidemiology. –This use case focuses only on “spontaneous” reporting, and will not include safety and surveillance of drug reactions occurring during clinical trials. Scenarios Identified: –EHR-enabled Adverse Drug Reaction Reporting (ICSR) Enable healthcare professionals to more easily report adverse events with higher quality supporting data available in electronic medical record and other electronic systems. Create a central repository & workflow capabilities that can shared by drug manufacturers and regulatory agencies for collection, management, and reporting of adverse events. –Signal Detection of Drug Reactions Detection of patterns of drug reactions using signal detection algorithms against comprehensive, longitudinal electronic patient health records available through health information exchanges. –Epidemiology, Hypothesis Testing, & Longitudinal Data Mining Allow researchers to execute data queries to test hypotheses and evaluate patterns of drug effects against one or more repositories of standardized, anonymized patient health information for large numbers of patients across the country. Key Obstacles: –AE Reporting: physicians and other healthcare professionals must be given incentive to report adverse events through EMR systems with high quality supporting data. –Regulatory Agreement: gain agreement from regulators to change current processes for adverse event reporting to a new model that allows manufacturers and regulators to use one central system for AE collection and reporting. –Data Ownership & Governance: agreements of who owns patient data, how it will be governed, whether it can be aggregated and by whom, and who can use it for what purposes. –Privacy & Consent: policies regarding patient consent and privacy protections to share health information. This includes agreement of who can access identified and de-identified patient data. –Standards: terminology standards necessary to create consistent, computable, interoperable health record data.

13. Copyright © 2007 Accenture All Rights Reserved. 1309 Apr 2007 How does this map to AZ objectives Slipstream Use Case / POC Opportunity Clinical Objectives Connecting Patients to Trials 1.Using the local Strategic development model, deliver US phase IV Studies to time, cost and quality 2.Through the Study Recruitment Center of Excellence, effectively leverage key areas of partnership with External Scientific Affairs (ESA) and Commercial to optimize delivery of Clinical programs 3.Increase Diversity in recruitment of US Clinical Studies by partnering with key stakeholder groups Safety Surveillance 1.Provide necessary drug safety and Medical Science support for specific US safety issues – IOM, benefit-risk plans 2.Identify needs for ‘ongoing, real-time safety surveillance’ in clinical programs and propose plan to clinical team by end of Q2 to meet these needs Superior Patient Safety Work stream

14. Copyright © 2007 Accenture All Rights Reserved. 1409 Apr 2007 Slipstream Use Cases – Communication has been extensive and is on-going CRIX International December 9, 2006 CRIX International December 9, 2006 FDA Sentinel Network Meeting March 7-8, 2007 Meeting Summary and Outcomes http://www.fda.gov/oc/op/sentinel/ Meeting Summary The FDA held a two-day public meeting to explore opportunities to collaborate with other public and private organizations to create a Sentinel Network to monitor the safety of medical products. Andrew von Eschenbach and Janet Woodcock kicked off the meeting and laid out three main components of the network: Data Collection Identifying data source systems, including EMRs and large databases (claims, clinical, lab, etc) Risk Identification and Analysis Integrated networks to connect data sources Tools and methods for data mining for safety signals Agreement on methodologies used for signal detection and validation Ability to study subgroups, biomarkers, & genomic markers Risk Communication How to get new information into physicians’ workflows (decision support) The panelists for the meeting were made up of different FDA departments, CDC, DoD, VA, CMS, ONC, & AHRQ. Participating speakers came from academic medical centers, industry associations, health information exchanges, payers, pharma companies (GSK, J&J, Pfizer), and technology companies to present their ideas on the Sentinel Network. FDA Sentinel Network Meeting March 7-8, 2007 Meeting Summary and Outcomes http://www.fda.gov/oc/op/sentinel/ Meeting Summary The FDA held a two-day public meeting to explore opportunities to collaborate with other public and private organizations to create a Sentinel Network to monitor the safety of medical products. Andrew von Eschenbach and Janet Woodcock kicked off the meeting and laid out three main components of the network: Data Collection Identifying data source systems, including EMRs and large databases (claims, clinical, lab, etc) Risk Identification and Analysis Integrated networks to connect data sources Tools and methods for data mining for safety signals Agreement on methodologies used for signal detection and validation Ability to study subgroups, biomarkers, & genomic markers Risk Communication How to get new information into physicians’ workflows (decision support) The panelists for the meeting were made up of different FDA departments, CDC, DoD, VA, CMS, ONC, & AHRQ. Participating speakers came from academic medical centers, industry associations, health information exchanges, payers, pharma companies (GSK, J&J, Pfizer), and technology companies to present their ideas on the Sentinel Network. Over 35 opportunities to brief stakeholders on Slipstream use cases: NIH AHIC NCVHS CRIX FasterCures PhRMA FDA MHRA CDC eClinical Forum Additional Pharma companies And on-going…

15. Copyright © 2007 Accenture All Rights Reserved. 1509 Apr 2007 Progress towards stated goals

16. Copyright © 2007 Accenture All Rights Reserved. 1609 Apr 2007 Update on AHIC’s NHIN Prototype Efforts Successfully completed the NHIN prototype effort – –Achieved all objectives in SOW including connecting 15 health care organizations in three distinct markets and demonstrating that data extraction and normalization are possible. Presentation at AHIC National Forum on January 24 th -25 th, 2007 well received by over 600 attendees Presented at HIMSS to International audience Over twenty requests from agencies and clients for demonstrations ONC Regional Implementation RFPs expected May 2007 –Expect 10-14 awards for total of $20M –Still not a lot of details on RFPs

17. Copyright © 2007 Accenture All Rights Reserved. 1709 Apr 2007 What We Set Out To Do Build a secure NHIN prototype that leveraged existing infrastructure and: Allow patient control of their health information Connect systems with a wide variety of IT platforms Deal with the critical issues of data normalization Provide enough flexibility to allow local choice in the degree of centralization of data Meet the requirements of the three use cases Show we could quickly build out RHIOs

18. Copyright © 2007 Accenture All Rights Reserved. 1809 Apr 2007 The shift from the NHIN to RHIOs So now what happens… Lots of talk and emerging efforts at regional and state levels –Few $’s –Governance still an issue –Business Case less than compelling Look to: –State Medicaid programs as nexus for efforts (ability to leverage MMIS matching federal funds) –Emergence of PHR information aggregators –Health IT Bill seeking to make owners of data HIPAA “covered entities”

19. Copyright © 2007 Accenture All Rights Reserved. 1909 Apr 2007 How should a company “play” during different stages of market maturity? Stage DescriptionStrategic ObjectiveSuccess Measure Concept/ IncubationIdeas“Get Ahead of the Market with the Idea” Awareness Reputation as innovator Proof of ConceptPilots“Gain Experience on Key Success Factors/Create Credentials” Innovative credentials on key issues Clarity on key success factors needed for positioning Early Adopters<20% market adoption“Be the Logical Choice for Early Adopters” Invitation to bid on all relevant opportunities Wins on key early trendsetting projects Wide Spread Adoption20%-75% market adoption“Be the One to Beat and Scale/Defend” High % of Wins Business as Usual>75% market penetration“Harvest”Market share Market Maturity: Strategy and Tactics

20. Copyright © 2007 Accenture All Rights Reserved. 2009 Apr 2007 Setting the context – –Background – what is the NHIN –The objectives for the NHIN Slipstream project What is the current state and context for today –What did we accomplish with NHIN Slipstream project –Use case activities – Matching patients to trials, Clinical data capture, Drug safety surveillance –The current environment: The NHIN – RHIO shift Advice and recommendations –Process to follow on opportunities –Opportunities going forward Meeting Agenda

21. Copyright © 2007 Accenture All Rights Reserved. 2109 Apr 2007 Advice and recommendations for going forward Implement a best practice-based approach for managing Healthcare IT roadmap and investments –Start with a real business challenge on a real drug project and ask “how could Health IT help solve this” Ensure linkage to business goals, objectives, and priorities Execute projects that support actual drug development projects –Establish a governance and portfolio approach for managing proof of concept and/or scale-up projects Develop and maintain strong connections with the broader Clinical Research and Health IT communities Pursue convergence opportunities wherever possible – CRIX, PhRMA, NIH, Regulators, others

22. Copyright © 2007 Accenture All Rights Reserved. 2209 Apr 2007 Opportunity = Use Case Testable Component Provider Partner(s) (or others, e.g., Regulators) Technology Vendor(s) ++ Business Engagement + Company Priorities HIT Roadmap Patient data source Compatible with Use Case Requirements Opportunity assessment framework – Critical elements to consider in evaluating an opportunity Other considerations Ability to execute Realistic expectations – where we are and what can be accomplished Scale and fit with use case Re-use and growth path Governance – how to control the effort

23. Copyright © 2007 Accenture All Rights Reserved. 2309 Apr 2007 Proof of Concept Opportunities The group has identified several Proof of Concept project ideas. Some are firm ideas, others are more speculative, and some are prospects. The table below organizes the ideas by use case: Use CaseFirm OpportunitiesSpeculative OpportunitiesOther Prospects 1. Matching Patients to Trials 1.a CRIX - National expansion of BreastCancerTrials.or g (powered by caMATCH) 1.b. Geisinger EPIC 1.c. W. Virginia Med Ctr - EPIC 1.d. Siemens matching technology Cleveland Clinic – EPIC InterMountain Health – GE Kaiser – EPIC Stanford U. U. Pittsburgh Med. Ctr. – EPIC/ Cerner 2. Drug Safety and Surveillance 2.a. Surface IHE RFD form for Drug AE reporting from within EMR – DONE 2.b. MHRA eYellow Card and Next Generation GPRD 2.c. Geisinger AE Reporting via EMR 2.d. W. Virginia Medical Institute 2.e. Signal detection on longitudinal health record data (Allscripts pilot, MHRA GPRD, Health Dialog data) Cleveland Clinic –EPIC InterMountain Health – GE Kaiser - EPIC Stanford U. - EPIC 3. Clinical Trial Data Collection / Mgmt 3.a. NIH CTSA CR NHIN 3.b. Allscripts pilot 3.c. IHE/CDISC – next phase of piloting (Cerner, Siemens) 3.d. EDC & EMR Vendor Pilot eClinical Forum EHR project Cleveland Clinic –EPIC InterMountain Health – GE Kaiser - EPIC Stanford U. - EPIC 4. Appropriate Care 4.a. Geisinger EPIC 2 nd -ary Use of Data Pilot 4.b. Allscripts pilot 4.c. Health Dialog pilot 4,d. Kaiser - EPIC Cleveland Clinic –EPIC InterMountain Health – GE Stanford U.

24. Copyright © 2007 Accenture All Rights Reserved. 2409 Apr 2007 Focused opportunities to put Slipstream Use Cases to practice – Projects under active consideration Matching Patients to Trials –Establish an “EHR enabled” Matching Patients to Trials capability under CRIX building upon lessons and capabilities under BreastCancerTrials.org at UCSF Drug Safety Surveillance –Design and implement a globally harmonized EHR enabled-AE collection capability and Signal Detection database capability leveraging the UK MHRA’s e- Yellow Card and next generation GPRD initiatives Clinical Data Capture, Management, and Control –Leverage the NHIN Prototype to “integrate” EHR-enabled Clinical Trial Administration and Data collection across a fragmented NIH GCRC / CTSA sites

25. Copyright © 2007 Accenture All Rights Reserved. 2509 Apr 2007 How should Slipstream proceed now? – Slipstream going forward can provide the following: Evolve into an “incubator” for PoC projects – focal point for planning and co- funding of emerging efforts Provide PoC planning, progress updates, and discussion forums to disseminate results Deliver educational / briefing sessions for participant senior management and other stakeholders Continued communication and influence planning and execution Marketing of the use cases – Slipstream would require “thinner” resourcing as most effort and investment would be pushed to PoC projects. – Incremental budget to support governance/operating model support. – Merge into CRIX? Merge with PhRMA HIT Forum? Future Slipstream Operating Model – Proposals for Moving Forward with Slipstream Phase 2

26. Copyright © 2007 Accenture All Rights Reserved. 2609 Apr 2007 Recommendations External –Establish an AZ cross functional team to participate in Slipstream Phase 2 Identify specific components of the use cases where proof of concept (POC) activities can be tested (2007 – 2008) Internal –Align Slipstream with Superior Patient Safety initiative –Align with the Information Strategy –CRIX Alignment

27. Copyright © 2007 Accenture All Rights Reserved. 2709 Apr 2007 Questions?

28. Strictly confidential Appendix Additional Detail on Slipstream Implementation Opportunities

29. Copyright © 2007 Accenture All Rights Reserved. 2909 Apr 2007 Focused opportunities to put Slipstream Use Cases to practice – Projects under active consideration Matching Patients to Trials –Establish an “EHR enabled” Matching Patients to Trials capability under CRIX building upon lessons and capabilities under BreastCancerTrials.org at UCSF Drug Safety Surveillance –Design and implement a globally harmonized EHR enabled-AE collection capability and Signal Detection database capability leveraging the UK MHRA’s e- Yellow Card and next generation GPRD initiatives Clinical Data Capture, Management, and Control –Leverage the NHIN Prototype to “integrate” EHR-enabled Clinical Trial Administration and Data collection across a fragmented NIH GCRC / CTSA sites

30. Copyright © 2007 Accenture All Rights Reserved. 3009 Apr 2007 ClinicalTrialsMatch.org The Vision: Speed drug approvals and new therapies by accelerating accrual to trials Providing consumers a platform to engage in clinical trial enrollment Nationally trusted non-profit portal for clinical trial information and matching Collaboration among stakeholders: –Patients/Physicians –Trial Investigators –Government Agencies –Pharma/Biotech Integrated with other healthcare data repositories: –EMR and PHR Data –Trial Registries and Management Systems –Disease Registries Conform to National/Industry Healthcare Standards Iterative development: Apply “lessons learned” to implement and evaluate a trial matching service that is extensible to other disease states BCT_Pilot BCT_NationCTM.org

31. Copyright © 2007 Accenture All Rights Reserved. 3109 Apr 2007 CRIX is interested in Matching Patients to Trials as a consortium service BreastCancerTrials.org: Overview of current operating model The near-term opportunity is to converge effort and build Matching Patients to Trials services under the CRIX service umbrella

32. Copyright © 2007 Accenture All Rights Reserved. 3209 Apr 2007 Focused opportunities to put Slipstream Use Cases to practice – Projects under active consideration Matching Patients to Trials –Establishing an “EHR enabled” capability under CRIX building upon lessons and capabilities under BreastCancerTrials.org at UCSF Drug Safety Surveillance –Design and implement a globally harmonized EHR enabled-AE collection capability and Signal Detection database capability leveraging the UK MHRA’s e- Yellow Card and next generation GPRD initiatives Clinical Data Capture, Management, and Control –Leverage the NHIN Prototype to “integrate” EHR-enabled Clinical Trial Administration and Data collection across a fragmented NIH GCRC / CTSA sites

33. Copyright © 2007 Accenture All Rights Reserved. 3309 Apr 2007 Overview of the Drug Safety Surveillance component of Slipstream 2 The concept –Upgrade the MHRA’s capabilities in AE collection and Signal Detection: Convert the Yellow Card Scheme from paper-based to electronic – create the eYC Upgrade the data collection and processing capabilities that underpin GPRD –In parallel…implement similar capabilities at an established Health Information Exchange Leverage RFD capability to simplify the collection of AEs and collect GPRD-like datasets –Merge the two efforts to create a global capability  Initial focus will be on the implementation of an Electronic Yellow Card concept  Next steps are to outlines the scope, high level solution, estimates and plans for the development of a production solution.

34. Copyright © 2007 Accenture All Rights Reserved. 3409 Apr 2007 Schematic of the collection of Safety Data – Currently this is a manual and costly process for both the MHRA and Pharmaceutical companies UK General Practitioner EMR File on Disk Yellow Cards (paper) Data Entry, Cleaning, etc. Data Entry, Cleaning, etc. Population Database PV Capabilities AE Database Pharma Company Sponsor Data Entry, Cleaning, etc. Global check AE Db Reporting CURRENT

35. Copyright © 2007 Accenture All Rights Reserved. 3509 Apr 2007 Schematic of the collection of Safety Data from within an EMR – Automate e-Yellow Card and the loading of population data for signal detection UK General Practitioner EHR e-Yellow Cards Direct data load Data investigation Population Database PV Capabilities AE Database Pharma Company Sponsor Global check AE Db Reporting US RHIO EHR Direct data load FUTURE 1 2 3 1 e-Yellow Card from EHR 2 Auto-load of EHR data to GPRD 3 US Health Information Exchange extending GPRD

36. Copyright © 2007 Accenture All Rights Reserved. 3609 Apr 2007 Focused opportunities to put Slipstream Use Cases to practice – Projects under active consideration Matching Patients to Trials –Establishing an “EHR enabled” capability under CRIX building upon lessons and capabilities under BreastCancerTrials.org at UCSF Drug Safety Surveillance –Design and implement a globally harmonized EHR enabled-AE collection capability and Signal Detection database capability leveraging the UK MHRA’s e- Yellow Card and next generation GPRD initiatives Clinical Data Capture, Management, and Control –Leverage the NHIN Prototype to “integrate” EHR-enabled Clinical Trial Administration and Data collection across a fragmented NIH GCRC / CTSA sites

37. Copyright © 2007 Accenture All Rights Reserved. 3709 Apr 2007 Develop a Clinical Research NHIN to converge Health Record and Clinical Research data collection, management, and control The problem –Health care data exists in paper or if electronic, it exists in hundreds of disparate legacy systems. –Efficiently accessing it to improve clinical research currently is not practical Components needed to solve this problem –A functional health information exchange (HIE) that can extract and normalize data from legacy systems –Access to a governance body that can influence behavior of disparate organizations –Access to an organization with a huge need to share data –Participation by organizations who can help drive a market solution and influence governmental and industry –Access to people with the skill set and passion to pull this off –Funding

38. Copyright © 2007 Accenture All Rights Reserved. 3809 Apr 2007 The Solution –Identify two NIH CTSA (Clinical and Translational Science Award) consortium and pilot HIE implementations at both institutions to capture clinical data in a standard way. –Work with all twelve CTSA institutions, HL7, NLM and CDISC and the Pharma Industry to define requirements. Phase data requirements into prototypes. The 12 institutions forming the initial consortium: Columbia University Health Sciences - Irving Institute for Clinical and Translational Research (IICTR)Irving Institute for Clinical and Translational Research (IICTR) Duke University - Clinical Translational Science Institute (CTSI)Clinical Translational Science Institute (CTSI) Mayo Clinic College of Medicine - Center for Clinical and Translational Research (CCTR)Center for Clinical and Translational Research (CCTR) Oregon Health & Science University - Oregon Clinical and Translational Science Institute (OCTSI)Oregon Clinical and Translational Science Institute (OCTSI) Rockefeller University - Rockefeller University Center for Clinical and Translational SciencesRockefeller University Center for Clinical and Translational Sciences University of California, Davis - Clinical and Translational Science Center (CTSC)Clinical and Translational Science Center (CTSC) University of California, San Francisco - Clinical and Translational Science Institute (CTSI)Clinical and Translational Science Institute (CTSI) University of Pennsylvania - Institute for Translational Medicine and Therapeutics (ITMAT)Institute for Translational Medicine and Therapeutics (ITMAT) University of Pittsburgh - Clinical and Translational Science Institute (CTSI)Clinical and Translational Science Institute (CTSI) University of Rochester - University of Rochester Clinical and Translational Science Institute (UR CTSI)University of Rochester Clinical and Translational Science Institute (UR CTSI) University of Texas Health Science Center at Houston - Center for Clinical and Translational Sciences (CCTS)Center for Clinical and Translational Sciences (CCTS) Yale University - Yale Center for Clinical Investigation (YCCI)Yale Center for Clinical Investigation (YCCI) –Depending on funding, consider different architectures for data collection at the sites. The Value of this Approach –Engages 12 topic health care institutions, NIH and Pharma Industry around solving a critical, but doable project –Create learnings and excitement; impact the cost of doing business in the short-run –Public/Private/Academic involvement is a great model of cooperation –Tools, knowledge and personnel exist to solve this problem Develop a Clinical Research NHIN – Participation of NIH and key Academic Medical Center create an incentives driven operating model