Query Health: Distributed Population Queries

1. Query Health:Distributed Population Queries Farzad Mostashari, National Coordinator for Health IT (ONC) Todd Park, Chief Technology Officer (HHS) Doug Fridsma , Director Standards & Interoperability (ONC) Rich Elmore, Coordinator – Query Health (ONC) September 6, 2011

2. Q&A Instructions for WebEx Select the “Q&A” button in the WebEx toolbar. Select “All Panelists” in the Q&A box. Type your question and hit send. The moderator will select questions for the panelists from the queue. Connection Problems? Email to: admin@siframework.org

3. Notices Please note that this presentation and the Q&A session are being recorded and will be available on QueryHealth.org To download any of the “Summer Concert Series” presentations, visit QueryHealth.org and click on the “Summer Concert Series” button This session will be live tweeted on Twitter Hashtag: #QueryHealth

4. Query Health:Distributed Population Queries Farzad Mostashari, National Coordinator for Health IT (ONC) Todd Park, Chief Technology Officer (HHS) Doug Fridsma , Director Standards & Interoperability (ONC) Rich Elmore, Coordinator – Query Health (ONC) September 6, 2011

5. Topics • Strategic Rationale • Summer Concert Series • Query Health • Alignment

6. What if?

7. What if? … you could ask questions about quality and performance that helped you to be proactive in improving population health in your community?

8. What if? … you could compare effectiveness of treatments for patients in your community? And refine the analysis as you learn more about the underlying conditions and treatments.

9. What if? … you could provide answers about performance and quality without exposing patient level information?

10. What if? … you could deploy scarce vaccines in the right quantities to the right locations because you understood the at-risk populations at that moment in time across your community?

11. What if? … you could improve your understanding of public health hazards in your community, with timely responses to questions about an outbreak?

12. Vision Enable a learning health system to understand population measures of health, performance, disease and quality, while respecting patient privacy, to improve patient and population health and reduce costs.

13. Principles • Eyes on the prize: Deliver better population health and care • Build on what’s available today and adapt - don’t rip & replace • Foster innovation and use the market • Watch out for the little guy – minimize burden to providers and use information available in the routine course of care • Open, transparent, and democratic process. Keep the patients at the center

14. Context and Opportunity Context: The nation is reaching critical mass of deployed Electronic Health Records (EHRs) with greater standardization of information in support of health information exchange and quality measure reporting. The Opportunity: Turbo charge your understanding of population health, performance and quality • Enable proactive patient care in your community • Deliver insights for local and regional quality improvement • Facilitate consistently applied performance measures and payment strategies for your community (hospital, practice, health exchange, state, payer, etc.) based on aggregated de-identified data • Provide treatments that are most effective for your community

15. The Challenge • High transaction and “plumbing” costs • Variation in clinical concept coding, even within organizations • Lack of query standards • Lack of understanding of best business practices • Centralizing tendency • Moves data further away from source • Increases PHI risk exposure • Limits responsiveness to patient consent preference – less actionable • Limited to large health systems • With larger IT or research budgets • Few notable exceptions

16. Turbo-charge your understanding of patient population health in your community Clinical Information Question Aggregate Result Clinical Information Question Aggregate Result Questions about disease outbreaks, prevention activities, health research, quality measures, etc.

17. Summer Concert Series

18. Summer Concert Series: Speed, Adaptability and Patient Coverage Mini-Sentinel Rich Platt and Jeff Brown i2b2 / SHRINE Zak Kohane and Shawn Murphy References: http://wiki.siframework.org/file/view/ONC+Summer+Series-+Query+health_Brown+PlattV1.pdf http://wiki.siframework.org/file/view/i2b2-SHRINE+Query+Health+Presentation+8-30-2011.pdf

19. Summer Concert Series: Condition Counts and Disease Prevalence Regenstrief Shaun Grannis OMOP Patrick Ryan, Marc Overhage, Tom. Scarnecchia References: http://wiki.siframework.org/file/view/Regenstrief+Query+System+Grannis+20110829.pdf http://wiki.siframework.org/file/view/OMOP+Ryan+ONC+29Aug2011+final.pdf

20. Summer Concert Series: Disease Outbreak Monitoring Distribute David Buckeridge CDC’s BioSense TahaKass-Hout References: http://wiki.siframework.org/file/view/Distribute.pdf http://wiki.siframework.org/file/view/BioSense_Redesign_S%26I_20110826_Kass-Hout.pdf

21. Summer Concert Series: Proactive and Preventative Care DARTNet Wilson Pace Hub Population Management System Jesse Singer and Michael Buck References: http://wiki.siframework.org/file/view/ONC+Summer+Series-+Query+health_Brown+PlattV1.pdf https://cbmi.med.harvard.edu/shrine2011/sites/cbmi.med.harvard.edu.shrine2011/files/Harvard%20Catalyst%20SHRINE_%20Zak%20Kohane_0.pdf

22. Summer Concert Series: Performance and Quality Reporting Population CCR Steven Waldren hQuery Andy Gregorowicz and Marc Hadley References: http://wiki.siframework.org/file/view/queryHealth-popCCR-20110824.pdf http://wiki.siframework.org/file/view/hQuery+Summer+Concert+Presentation.pdf

23. Summer Concert Series: Methods to Distribute Services & Queries caGrid Ken Buetow Universal Public Health Node Ivan Gotham, Lee Jones and Vince Lewis References: http://wiki.siframework.org/file/view/Query+Health+08.19.11.pdf http://wiki.siframework.org/file/view/Summer+Concert+Series+2011+-+introduction+v5.pdf

24. Summer Concert Series: Challenges

25. Query HealthScope and Approach HIT Policy Committee: Policy Guideposts Practice drives standards Rough consensus Running code (open source) Pilot Specifications Standards

26. Query Health:Example User Story – Case Control, Vaccine Efficacy • Quality Compliance : Number of patients over the age of 50 who have received the flu vaccine (NQF 0041). • Surveillance: Determine what patients have received the vaccine and have contracted the flu. • 2 x 2 of Vaccine and Flu Diagnosis • Refine Query (for example for H1N1). • Add GI symptom • Specify H1N1 vaccine

27. Query Health:Example User Story – Case Control, Statin Efficacy • Quality Compliance : Number of patients over the age of 18 who have been diagnosed with CAD and are taking a statin (NQF 0074) • Surveillance: Determine how many patients are hyperlipidemic. • 2 x 2 of Statin and Hyperlipidemia • Refine Query • Select two statins • Compare efficacy of two statins

28. Query Health ObjectiveSimple scalable secure use case • Establish Standards and Protocols for: • Patient Data • Query / Case Definition • Results 2. Query / Case Defini-tion 3. Results 1. Patient Data Query Health

29. Bottom Up Use Case Development Within a Top-down Coordination Framework ENABLING Interoperability Framework =Focused Collaboration CORE PRINCIPLES Prioritization Transparency Engagement Rapid Results Focused Collaboration Commandand Control Focus Classic Trade-Off Low High A Thousand Flowers Bloom Low High Participation

30. Query HealthOrg & Timeline • Clinical • Current State Presentations • CIM, Query, Result • Alternatives, Convergence & Consensus • Pilots • Feedback to Standards & Pilot Support • Technology • Current State Presentations • Standards & Reference Implementation • Privacy, Security, Consent, Sustainability DUA, & Best Practices • Alternatives, Convergence & Consensus • Business • Current State Presentations • Alternatives, Convergence & Consensus • Pilots

31. Goals Alignment with:S&I Framework S&I Framework Governance • Open Government Initiative • Engaging leaders from providers, health IT vendors, states / HIOs, federal partners, and research community Meaningful Use and Standards • Standardized information models and terminologies, e.g., SNOMED, LOINC – vocabulary value sets associated with patient care and quality metrics • CIM model to support user stories, leveraging S&I initiatives and existing distributed query models • Transport approach will leverage the NwHIN

32. Goals Alignment with: Digital Infrastructure for a Learning Health System • Build a shared learning environment • Engage health and health care, population and patient • Leverage existing programs and policies • Embed services and research in a continuous learning loop • Anchor in an ultra‐large‐scale systems approach • Emphasize decentralization and specifications parsimony • Keep use barriers low and complexity incremental • Foster a socio‐technical perspective, focused on the population • Weave a strong and secure trust fabric among stakeholders • Provide continuous evaluation and improvement Reference IOM 2011. Digital Infrastructure for the learning healthcare system: Workshop series summary. National Academies Press.

33. Query HealthRecap

34. Discussion New Time Implementation Group Tuesdays 1:30pm-3:00pm EDT (Starting 9/13) Technical Work Group Wednesdays 11am-12pm EDT (Starting 9/7) Clinical Work Group Wednesdays 12pm-1pm EDT (Starting 9/7) Business Work Group Thursdays 11am-12pm EDT (Starting 9/8) First Face to Face Meeting October 18-19 Sign Up at QueryHealth.org Follow on Twitter hashtag: #QueryHealth Download to your calendar: QueryHealth.org Scroll towards the bottom

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