Query Health: Distributed Population Queries Farzad Mostashari, National Coordinator for Health IT (ONC) Todd Park, Chief Technology Officer (HHS) Doug.

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Presentation transcript:

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

Q&A Instructions for WebEx Connection Problems? to: 1.Select the “Q&A” button in the WebEx toolbar. 2.Select “All Panelists” in the Q&A box. 3.Type your question and hit send. The moderator will select questions for the panelists from the queue.

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” buttonQueryHealth.org This session will be live tweeted on Twitter Hashtag: #QueryHealth#QueryHealth Notices

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

Strategic Rationale Summer Concert Series Query Health Alignment Topics

What if?

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

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

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

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. Vision

1.Eyes on the prize: Deliver better population health and care 2.Build on what’s available today and adapt - don’t rip & replace 3.Foster innovation and use the market 4.Watch out for the little guy – minimize burden to providers and use information available in the routine course of care 5.Open, transparent, and democratic process. Keep the patients at the center Principles

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 Context and Opportunity

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 The Challenge

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

Summer Concert Series

Summer Concert Series: Speed, Adaptability and Patient Coverage Mini-Sentinel Rich Platt and Jeff Brown i2b2 / SHRINE Zak Kohane and Shawn Murphy References:

Summer Concert Series: Condition Counts and Disease Prevalence Regenstrief Shaun Grannis OMOP Patrick Ryan, Marc Overhage, Tom. Scarnecchia References:

Summer Concert Series: Disease Outbreak Monitoring Distribute David Buckeridge CDC’s BioSense Taha Kass-Hout References:

Summer Concert Series: Proactive and Preventative Care DARTNet Wilson Pace Hub Population Management System Jesse Singer and Michael Buck References:

Summer Concert Series: Performance and Quality Reporting Population CCR Steven Waldren hQuery Andy Gregorowicz and Marc Hadley References:

Summer Concert Series: Methods to Distribute Services & Queries caGrid Ken Buetow Universal Public Health Node Ivan Gotham, Lee Jones and Vince Lewis References:

Summer Concert Series: Challenges Distributed Population Queries Best Practices for Data Use / Sharing Sustainability Organization, Management and Coordination Auditability Privacy, Security and Consent Consistency of Clinical Concepts Data Extensibility Queries Across Organizations Multiple Networks

Query Health Scope and Approach Practice drives standards 1.Rough consensus 2.Running code (open source) 3.Pilot 4.Specifications 5.Standards Query Health – Distributed Population Queries Standards & Service Public / Private Partnership Project Community Driven, Consensus- based EHRs & Other Clinical Records HIT Policy Committee: Policy Guideposts

Query Health: Example User Story – Case Control, Vaccine Efficacy 1.Quality Compliance : Number of patients over the age of 50 who have received the flu vaccine (NQF 0041). 2.Surveillance: Determine what patients have received the vaccine and have contracted the flu. 3.2 x 2 of Vaccine and Flu Diagnosis 4.Refine Query (for example for H1N1). –Add GI symptom –Specify H1N1 vaccine Individuals Who Contracted the Flu Individuals Who Did Not Contract the Flu Population Total Received Vaccine Did Not Receive Vaccine Population Total

Query Health: Example User Story – Case Control, Statin Efficacy Hyper- lipidemic Not Hyper- lipidemic Population Total Individuals Who Take a Statin Individuals Who Do Not Take a Statin Population Total1, ,600 1.Quality Compliance : Number of patients over the age of 18 who have been diagnosed with CAD and are taking a statin (NQF 0074) 2.Surveillance: Determine how many patients are hyperlipidemic. 3.2 x 2 of Statin and Hyperlipidemia 4.Refine Query Select two statins Compare efficacy of two statins Hyper- lipidemic Not Hyper- lipidemic Population Total Patients on Medication A Patients on Medication B Population Total

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

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

Query Health Org & Timeline Clinical Current State Presentations CIM, Query, Result Feedback to Standards & Pilot Support Technology Current State Presentations Standards & Reference Implementation Alternatives, Convergence & Consensus Business Current State Presentations Alternatives, Convergence & Consensus Pilots Privacy, Security, Consent, Sustainability DUA, & Best Practices Alternatives, Convergence & Consensus Pilots Query Health Implementation Group Clinical Workgroup Technical Workgroup Business Workgroup

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 Goals Alignment with: S&I Framework

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 Goals Alignment with: Digital Infrastructure for a Learning Health System Reference IOM Digital Infrastructure for the learning healthcare system: Workshop series summary. National Academies Press.

Query Health Recap

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 Discussion Download to your calendar: QueryHealth.org Scroll towards the bottom New Time

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For more information and to register for Query Health, please visit QueryHealth.org