The K entucky D iabetes and O besity C ollaborative (KDOC)

1. The Kentucky Diabetes and ObesityCollaborative (KDOC) Kevin Pearce, MD, MPH UK Department of Family and Community Medicine Jeff Talbert, PhD UK Department of Pharmacy Practice and Science Mark Dignan, PhD, MPH UK Department of Internal Medicine David Bolt, MA Kentucky Primary Care Association F. Douglas Scutchfield, MD UK College of Public Health Supported by NIH grants: NIDDK # 1RC4DK809866 NCATS # UL1TR000117

2. The Kentucky Diabetes and ObesityCollaborative (KDOC) KDOC partnering organizations • Kentucky Primary Care Association (KPCA) • Individual FQHCs • Kentucky Medicaid • University of Kentucky • Academic Health Center • Center for Clinical and Translational Science • Center for Public Health Systems and Services Research

3. Overarching goal: Activate new collaborations to improve quality and create opportunities for research

4. The Kentucky Diabetes and ObesityCollaborative (KDOC) Vision: Develop a healthcare data repository that will be used to improve the health of Kentuckians via QI activities and research. The KDOC data repository will bring together up-to-date clinical data from multiple primary care safety-net providers, plus Medicaid claims data, all linked at patient level. Secure web-based portals and special software will facilitate use while maintaining appropriate levels of privacy and security.

5. The Kentucky Diabetes and ObesityCollaborative (KDOC) Project Rationale • High prevalence of obesity and diabetes in a large rural and medically-underserved population; much of which relies on “safety-net” providers, such as FQHCs • Utility of being able to monitor and use clinical and claims data linked at patient level, and across healthcare facilities • Built-in utility for more broadly improving healthcare

6. The Kentucky Diabetes and ObesityCollaborative (KDOC) Project goals • Develop a secure data repository • clinical data from rural PCPs • Linked Medicaid claims data • Develop secure, user-friendly data interfaces for providers and researchers • Assess related training and support needs, and provide the training/ support to KDOC users • Facilitate research and healthcare QI collaborations

7. The Kentucky Diabetes and ObesityCollaborative (KDOC) Project goals (cont’d) Address gaps in generalizable knowledge about: • The effective use of HIT for chronic care coordination and related research in rural settings • Systems-oriented collaborative QI strategies for improving the management of chronic conditions in primary care • Effectively connecting AHC-based researchers and rural health disparity populations

8. Participating Federally-Qualified Community Health Centers Eight Community Health Centers (FQHCs) serving 39 mostly rural Kentucky counties; diabetes prevalence as high as 17% and obesity prevalence as high as 51% 2 to 15 clinic sites / FQHC with 6 to 31providers / FQHC 19,900 to 143,000 annual patient visits per FQHC Approx124,000patients served by the 8 FQHCs, total Five different EMR brands across the 8 FQHCs; time since EMR implementation: from < 1 year to several years

9. KDOC 3-Yr Project Approach • Establish leadership, steering and advisory groups • Simultaneously pursue interpersonal and technical aspects of KDOC development Interpersonal • build KDOC-specific collaborative relationships (BAAs, MOUs) • establish stakeholder priorities for HIT tools and functions • understand stakeholder opportunities and barriers related to collaboration around QI and research Technical • Understand technical aspects of data storage and sharing capabilities of each EMR system • establish HIPAA compliant methods for developing and using the KDOC Data Warehouse • explore utility of KHIE for KDOC • build or buy user-friendly data interfaces for QI and research

10. KDOC Project Approach (cont’d) 3. Simultaneously: (a) Obtain IRB approval for data transmission, storage, and general use (b) design and pilot a DM QI project involving the FQHCs 4. Populate KDOC data repository with clinical data from each FQHC, and with Medicaid claims data for matching time periods; data de-identified but coded for linkage at patient level 5. Simultaneously:(a) Perform pilot clinical QI project (b) facilitate use of KDOC infrastructure for research Throughout: plan for sustainability of infrastructure

11. KDOC Focus Groups • Conducted at 6 FQHC offices in rural Kentucky • Included providers, office staff, IT representatives • 45-60 minutes • Tape recorded, transcript analysis

12. Focus Group Discussion Topics • Perceptions about obesity and diabetes rates in rural Kentucky • Perceived role of research in prevention and control of diabetes and obesity…probing: • Experience with research • Barriers and facilitators of research with rural FQHCs • What is needed to increase participation in research • Communication and collaboration between providers and researchers • Implementation of Evidence Based Practices in DM mgmt

13. Focus Group Findings • There is interest in participating in and promoting research in FQHCs (and in partnering with UK) • Research is most likely to be successful when initiated by researchers • Participating with KDOC can help FQHCs with capturing clinical data, developing reporting, and perhaps QI • Use of EHR, or similar mechanism, for data collection is preferred – something that can be integrated into the flow of the practice • FQHCs not hesitant to share data as long as patient privacy protections are in place

14. More Focus Group Findings • Mild concern that KDOC will not be able to deliver information needed for HEDIS reporting – concern about responsiveness of KDOC to changes in guidelines • FQHC experience with EHRs and government has been mixed • Ability to better manage practice is a plus • Concern about monitoring by those outside the practice is a concern • Employee time for research is a barrier, need outside resources and staffing • IT assistance is needed for most projects • Research partnerships are built on trust between patients and clinics – and then researchers

15. Technical Strategy • KDOC vision: build QI tools that also serve as a research platform • FQHCs – de-identified data beyond own site—need for regional benchmark and peer comparison • UK-infrastructure for rural translational research network • 8 initial FQHCs: using 5 EMR vendors • Kentucky Medicaid as a project partner

16. Technical Process • Diverse site technical infrastructure • Very vendor dependent (new EMR users) • Limited site IT staff (contractors, part time, busy with day job) • Limited site database capacity (required flexible after hours connectivity, multiple small reports) • Process: 1)Special KDOC data extracts 2)Core database access 3)Core EMR reporting tool

17. Technical Workflow

18. Regulatory: QI/ operations use • All sites have MOU and BAA with UK • Sites limited access to their own data, with regional and national benchmarks for most measures • Research use requires additional limits and protections

19. Regulatory: using data for research • BAA and MOU required for each site • IRB #10-0493 The Kentucky Diabetes and Obesity Collaborative (KDOC) • Uses UK EDT third party “honest broker” • Researcher access to de-identified data • IRB #13-0275-F6A, Kentucky Diabetes and Obesity Collaborative (KDOC) • All users sign DUA, Complete HIPAA training • Data Use Advisory Committee reviews research protocols

20. DUAC: Data Use Advisory Committee • Address concerns over use of data • Function to advise on research data used from the collaboration • Composed of providers and administrators representing sites • All research protocols will be reviewed by committee

21. KDOC Data Repository: Claims Data Progress and Challenges • Medicaid MCOs established during first project year • Now working with Ky Medicaid QA/QI Department to goal of having claims data linked to clinical data in repository with proper security

22. Reporting Tools for QI • Intent:develop custom reporting tools • Go beyond current reporting platforms (greater flexibility than ‘canned’ reports) • AdoptedTableau analytic platform • Allows dashboards that are dynamic and interactive---allows visualization of data to generate new questions

23. Diabetes Care Monitoring • Tableau reporting models

24. Hypertension Care Monitoring

25. Conclusions so far • Interfacing with EMRs for data transfer into a shared repository cannot yet be standardized. EMR vendor characteristics and practice-based concerns must be addressed one-by-one • Expert technical assistance is required for practices to share clinical data for QI or research • EMR Vendors should be at the table from the beginning

26. Conclusions so far • Benefits for each collaborating practice, payer and research stakeholder cannot all be anticipated; they will fluctuate, but staying focused on benefits and value to each stakeholder is essential • e.g. Initial QI focus on UDS reporting, but later expanded to HEDIS measures and MCO gain sharing • Research and QI uses require different restrictions and protections…..development of shared trust among stakeholders across organizations is critical

27. And the biggest lessons… • Building a shared healthcare data repository for multiple stakeholders: • is a very complex undertaking that takes much longer than you imagine it will • has reward potentials that will grow and evolve • takes you outside your comfort zone, links you with fascinating new colleagues and opens up new vistas

28. Next steps • Expand into a much larger co-op that stakeholders can use for • QA/QI • Quality indicator capture and reporting • Gainsharing with payers • Research

29. Questions?