SAFTINet: Partnership Development

1. Scalable Architecture for Federated Translational Inquiries Network SAFTINet: Partnership Development

2. Overview • SAFTINetOverview • What is SAFTINet? • Funding • Partners and collaborators • Information Technology Infrastructure • Distributed network based on TRIAD technology • Observational Medial Outcomes Partnership (OMOP) Common Data Model • ROSITA and TRIAD node • Data Extracts • Data Use • Use of ROSITA for population management, quality improvement • Use of the network for research and comparative reporting • Data Governance • Next Steps for SAFTINet and AppNet • What you can do

3. SAFTINet • Who is SAFTINet? • A network of stakeholders interested in improving health care delivery and outcomes of underserved populations • What is SAFTINet? • A practice-based research network and distributed data network with a distributed database of clinical and claims data collected during routine care, to support both research and quality improvement • SAFTINet Research and Quality Improvement Goals • Improve health care quality and value, and reduce health disparities, in low income patients with chronic conditions who receive care in public safety net clinics, by generating evidence that will inform health policy, health services delivery, and practice at the point of care

4. Funding • AHRQ (American Recovery and Reinvestment Act 2009): Scalable Distributed Research Networks for Comparative Effectiveness Research • Develop a distributed data network that collects and links data from multiple and different healthcare delivery settings • Clinical data from electronic health records (EHR) • Medicaid claims data • Demonstrate capabilities for conducting methodologically rigorous Comparative Effectiveness Research (CER) • Capability for enhanced data collection (e.g., patient-reported outcomes) • R01; PI: Lisa Schilling, MD, MSPH • Initial funding for infrastructure development: 9/30/2010 – 9/29/2013 • Enhancement and Sustainability: 9/30/13 – 3/31/15

6. Technology infrastructure: Multi-node Web Portal Queries and Data Transfers Internet

7. Observational Medical Outcomes Partnership Common Data Model (OMOP CDM v4)

8. Technology infrastructure: CINA solution FQHC1 FQHC2 FQHC3 FQHC4 FQHC5 FQHC6 FQHC7 FQHC8 CINA CDR CINA CDR CINA CDR CINA CDR CINA CDR CINA CDR CINA CDR CINA CDR XML XML XML XML XML XML XML XML ROSITA TRIAD Clear Text PHI LimitedDataset OMOP V4 Payer Database (Medicaid, BCBS, etc) Web Portal Queries and Data Transfers Firewall Firewall Secure Network Internet

9. Practice / Network Technical Requirements for CINA CDR Solution Practice Technical Requirements • Install hardware and software on Practice network (PC or VM) • Create access to EMR database • Practice must be able to create a new user login to the EMR dBase • Establish remote access to SAFTINet PC / VM • Set up EMR UI and user log in on SAFTINet PC / VM • Establish ability to pass files securely to ROSITA

10. CINA CDR Implementation Needs • Our responsibilities (may not apply in all cases) • Establish / create data connectors to EMR database • Map identified data elements for import into CDR • Testing / Validation of identified data elements in CDR • Create automated secure data upload from Practice to CDR • Create XML output for import into ROSITA

11. CINA CDR Implementation Needs • Practice responsibilities • Contract execution • Identify IT and Clinical / EMR documentation liaison • Perform activities defined under Technical Requirements • Serve as a resource for assisting with location of data elements understanding documentation patterns, if needed

12. Data Use: ROSITA • ROSITA-based queries • Single or multiple FQHC, linked clinical & claims data • Fully identified patient-level raw data • ROSITA administrator prepares reports as desired • SQL and analytic skills needed • Report writing within ROSITA • JasperReports • Current reports focused on data quality assessments • Access restricted to personnel with appropriate permissions • Collaborate to identify additional reporting needs and corresponding technology enhancements

13. Data Use: SAFTINet Query Portal • Queries to the AppNet and other TRIAD nodes • Single or multiple nodes • Limited dataset of patient-level raw data (requires IRB/DUA for research, access to others’ nodes) • Counts • Quality metrics • Access restricted to those with TRIAD accounts, with appropriate permissions

14. Data Use: SAFTINet Portal • Comparative Reporting and Benchmarking • DARTNet Institute Practice Performance Reports • Practice-level data in charts showing network-wide performance statistics (e.g., percent of patients at goal for blood pressure control) • Comparative Effectiveness Research • Analytic data sets to test relationships among different types of treatments, services, service delivery models and health outcomes

15. Data Governance • Master consortium agreement (MCA) • Describes the terms and conditions under which Consortium Members will participate in a network to permit the transfer, use and disclosure of data to a network-enabled database. • Data use agreements (DUAs) • A legally binding agreement between parties (e.g., contractor, private industry, academic institution, other Federal government agency, or state agency), when an external entity requests the use of Protected Health Information in the form of a Limited Data Set. • Service Level Objectives (SLO) • Defines roles, responsibilities and objectives for adoption and maintenance of SAFTINet technology and security

16. Next Steps • Introduction to Practice / IT contact to discuss technical installation (determine feasibility, potential hardware / software costs, etc) • If technical install feasible: Execute DARTNetAgreements • CINA software license agreement (through DARTNet Institute as software reseller) • Master Service Agreement (with DARTNet) • BAA • Statement of Work

17. What can you do? • Facilitate decision making • Approve technology solution • Execution of contracts / agreements • Champion this project with your providers and IT staff • Identify opportunities for collaboration and data use for research/QI