AHC Information Exchange (MIX)

1. AHC Information Exchange (MIX) Executive Committee Kickoff Meeting

2. Agenda 1. Overview, charters and committee roles Cerra 2. The user need and the pilot project Cooley 3. The AHC MIX Project Klauer 4. Organization Cerra/Delaney 5. Key questions and subcommittees All 6. Introduction of Project Manager Cerra/Delaney 7. Meeting schedule Cerra/Delaney Eclipse Data Systems, Inc.

3. Data Integration for Clinical Research: User Needs } Requirements for “miniTACO” Pilot • Uses of Integrated Data: • Scientific Clinical Research Investigation • Patient Care/Safety in the context of research • Regulatory Reporting (IRB, DMSC, FDA, NIH, Sponsors, etc.) • Clinical Outcome Reporting (i.e. scTOD/CIBMTR, BCBS, FHS, etc.) • Operational Management (Admin, Financial, Operational, QA/QC, efficiency) • Data Sources • Clinical (EMR) • Research Laboratory • Regulatory (CTMS) • Product (i.e. cellular infusions, vaccines) • Financial Systems • Internal/External Collaborators • Goals • Participate in national networks (CTSA, caBIG, etc.) • Adopt internationally recognized standards • Comply with ICH/WHO GCP standards on clinical research • Comply with NIH data security and data sharing requirements • Cost efficient infrastructure and services • Manage access to vital information and preserve integrity of data through appropriate rights management Eclipse Data Systems, Inc.

4. AHC-MIX Platform: Technical Requirements “Free the data!” from the systems used to collect it • AHC-MIX platform will serve Academic Health Center community of clinical investigators and research staff by responding to frequent and complex demands for integrated data • Infrastructure to manage data access and preserve data integrity through appropriate rights management • Resources to provide tools and applications to manage and use the data • Cross-organizational data sharing – data exchange between AHC, Fairview, UMP, caBIG, CTSAs and other organizations to support collaborative clinical, research and, regulatory needs. • Governance – establishment of executive council, policies, working group with representatives from AHC, Fairview, OIT and UMP. • Privacy, Security and Data Rights Management – Standards, policies and procedures developed and adopted across organizations Eclipse Data Systems, Inc.

5. AHC-MIX Organizational Support Structure Biomedical Health Informatics (BMHI) AHC-MIX Executive Committee OIT Data Warehouse • Oversight • Governance • Common • Infrastructure • OS • DB • Architecture • Data Rights • Data Governance • Policies & Procedures • Standards DATA • Shared Tools • & Applications • caTissue • Shrine • I2B2 • CTMS BMHI MIX Technical Support UMP UMII i.e. Genomic Data & MSI Collaboration EMR DATA Fairview National Networks i.e. caBIG & CTSA EMR MIX - AHC-IS Infrastructure Common Data Exchange Platform DATA Bus Unit 1 Bus Unit 2 Bus Unit 3 Bus Unit 4 AHC-IS Research Application Development Team • Bus Unit Level Support • Local applications • Local policies • Data Stewardship • Local Governance Committee • Priorities Bus Unit 7 Bus Unit 6 Bus Unit 5 Eclipse Data Systems, Inc.

6. Guiding Principles for AHC-MIX • Use industry standards to ensure consistency, resulting in data integrity and interoperability. • Determine the ‘System of Record’ for each data element captured and stored – This will establish the ‘source of truth’ and enable a solid data governance plan that will ensure the efficacy of the information available • Accessible to everyone with the proper authorization • Flexible to meet the diverse needs of the entire user community • Dynamic to stay abreast of the changing needs for new protocols, requests from regulatory or collaborative organizations for multi-site studies • Responsive so that researcher, biostatistician, clinician and management needs are met quickly • Reduce redundancy of data entry into multiple systems and redundant reporting and database applications developed for individual research needs • State of Art Technology User Interface to manage requests and deliver reports and access to data Eclipse Data Systems, Inc.

7. Data Reporting to: • Co-Investigators (local or multi-site studies) • CIBMTR/scTOD • Clinicaltrials.gov • CTRP • FDA • NIH/NCI • Insurance reports • Industry reports • Etc. AHC-MIX Platform Data sets SAS, flat file, etc. PI Data Management Applications Reports Data Analysis & Reporting PI Clinical Dashboard • MIX Data Management • Daily refresh • Exact copies of data • Used for reporting, analytics • Data profiling for QA • Reference Data Sets, Xref Tables • Common or shared transformations • Data Standards (caDSR CDE etc) • Data Rights Management • Data Governance Policies • Data Security (HIPAA) Data Repository Researcher and Biostatisticians Data Reporting Environment Integration & Transformation caDSR Data Management HL7 Legacy Databases Staging Area Fairview, UMP, etc. Information Exchange Data Entry Applications Clinical (EMR, LAB) Research Lab Regulatory Product Admin Financial Registry Other PI Applications Eclipse Data Systems, Inc.

8. Components of AHC-MIX Platform • MIX Integration Platform – managed by BMHI and AHC-IS • Landing Area to scheduled download data from data entry systems • Staging Area – apply standards, quality checks • Integration Area – join data across multiple systems based on common keys • Metadata layer – manage reference data, master data, standards, cross-reference, data rights • Data Access – structure data to deliver to reporting tools, analytical environments, dashboards • Service layer – manage requests for data across platforms • Data Entry Applications – managed business units • EMR, Research and clinical lab, tissue bank, CTMS, financial, regulatory, registry • Reporting Applications and Tools – BMHI support standard reporting tools and local BI applications • BI Tools (Dashboard) • Reporting Tools (Crystal) • Analytics (SAS) Eclipse Data Systems, Inc.

9. Sophistication of Information ManagementEvolves… “Comprehensive data integration architecture and process can significantly increase IT ROI” Advanced Formal • Situation: • Automated Data Quality monitoring processes • MDM automated and integrated • SOA with real time updates • Event triggered response • Semantic data interoperability • Rule driven data management Sophistication Structured • Situation: • Formal methodology • Executive Steering Committee • Data Governance and Stewardship in place • Policies for change management • MDM Standards are established Today Ad-Hoc • Situation: • Dev, test, prod environments in place • Daily ETL processes • Standards, QA and mapping applied • Data Mart designed and populated • BI reporting tool • Report templates developed and users receive regular reports Informal • Situation: • Some full-time report developers • Some processes are defined • Data downloaded into tables that reflect source system but not modeled • Situation: • Basic reporting using Excel or MS Access • Data is accessed directly from source applications by users Time Eclipse Data Systems, Inc.

10. AHC-MIX Development Approach • Pilot project in the cancer center based on sophisticated integrated data access requirements • Multi-institutional site studies and intra and inter institutional data exchange requirements • Rigorous regulatory reporting • Complex application requirements • Critical clinical care management needs • Create cross-organizational governance structure to establish standard policies for: • Data Governance • Security • Metadata Management - Standards • Establish and follow a methodology to support ongoing development • Support project development in the MIX environment • Ensures consistency in applying data governance and rights management • Service Request Tracking Platform • Single point of entry for information requests for the clinical and research user community • Triage requests to be performed by the appropriate service support group • Manage ongoing development for reports, integrated datasets, applications etc. • Assessment • Determine the integrated information needs across all AHC organizations • Identify shared functions and opportunities to establish consistent data management services • Determine the organizational relationships and funding mechanisms to support a common platform • Understand AHC and cross organizational requirements with OIT, Fairview, UMP and other institutions for standard data exchange formats • Determine roll out strategy to move from pilot to AHC program Eclipse Data Systems, Inc.

11. SVPHS BMHI Program Manager MIX Executive Committee Infrastructure and Standards Data Governance And Security MIX Pilot Committee Finance Inventory and Needs Assessment AHC-MIX Governance ModelRoles and Responsibilities Executive Committee: • Sets overall project scope, goals and objectives • Sets policy for the MIX and for its use • Approves the workplan for the MIX Steering Committee • Provides oversight to the MIX Steering Committee • Sets, approves budgets and arranges funding • Manages communications for the project Steering Committee • Responsible for the technical plan and its implementation • Identifies areas where policy is needed and refers to the MIX Executive committee • Appoints the necessary working groups • Develops and manages budget and timelines • Makes periodic reports to the MIX Executive Committee on progress against the workplan Working Group • Develops proposals for policies and procedures for cross organizational plans, policies, and standards to be approved by the Steering Committee • Composed of subject matter experts (SMEs) and process owners • Examples: data governance, security, standards Eclipse Data Systems, Inc.

12. Data GovernanceRoles and Responsibilities Data Owner Data Steward Oversee the safe transport and storage of data. design, deploy, and maintain the underlying infrastructure and activities required to keep the data intact and available to users Research data issues and inquiries, implement data transformations, resolve data issues, and collaborate on system changes Document all data movements, conduct data validation and reconciliation processes Define, capture and maintain technical metadata. • Establish, maintain, and document processes and standards, and monitor for compliance • Responsible for quality control activities, such as defining metrics and validation rules, performing validation and monitoring, and utilizing data profiling tools and processes. • Create and submit for approval new policies  Define, capture and maintain business metadata, such as vocabulary definitions and valid values. • Help define data rights and access. • Define business rules and data transformations for MIX, maintaining the rules engine for transformation and implementing transformations as close to the source as possible. • Examples: research associates, postdoctoral fellows, statisticians, etc. • Member of senior management that is ultimately responsible for the protection and use of the data. • Responsible for the policy and practice decisions of the data, for its accuracy, and authorization for its access to others. An example of a data owner is the principal investigator of a study. Data Custodian Eclipse Data Systems, Inc.

13. Initial Outcomes - December 2010 • Data governance working group report • Security working group report • Environmental inventory and needs assessment • Definition of needed policies and procedures • Workplan for first 6 months • Workplan for second 6 months Eclipse Data Systems, Inc.

14. 6 Month Work Plan

15. Challenges for rolling out MIX • Unique needs for research application environment • Need flexibility to install, configure and run software required by a dynamic research organization • Application and data access needs are best understood by SMEs within the business or academic unit • Common policies, processes and standards must be well defined and an infrastructure available to apply these across multiple platforms • Varying levels of support services across multiple AHC organizational units • System-wide data governance, Data rights management, regulatory, common vocabularies, standards, common applications (CTMS or bio-repository) master and reference data management • Domain specific – BMT, Urology, Labs, Genomics etc. • Business Unit Level report development, application support, QA/QC • Shared Architecture and Support Services • Interoperability, scalability, extensibility, security, availability, usability and maintainability are the basic principles used to determine choices for the technical platform • Establishing robust layered data standards and rights management that satisfy all stakeholders across AHC including other institutions and regulatory bodies • Balance enterprise-wide standards with business unit specific needs and competency • Determine whether to scale horizontally within the architecture or harness the core functionality of the MIX platform to plug into other existing frameworks of integrated, secure data. • Choice of technology: database, tools, operating systems etc. will be based on architecture design principles, balancing enterprise standards with evolving applications, tools and approaches Eclipse Data Systems, Inc.

16. Critical Success Factors/Risks • Getting resources onboard • Cross-organizational communication and agreement on standards and support • Performing AHC-wide needs assessment • Avoiding ‘scope-creep’ • Service level agreements in place for technical support • Adapt and follow methodology • Break down ‘silos’ and foster a continuous learning environment Eclipse Data Systems, Inc.