Query Health:Distributed Population Queries
Update & Demo fromONC’s Office of Standards & Interoperability
Rich ElmoreCoordinator, Query Health
Provide a look at how Query Health is progressing
• How do the different parts of the Query Health solution fit together?
• How might a distributed query work in a real technical environment?
Objectives
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.
Distributed queries unambiguously define a population from a larger set
Questions about disease outbreaks,
prevention activities, health research,
quality measures, etc.
Distributed Query NetworksVoluntary, No Central Planning
Community of participants that voluntarily agree to interact with each other. There will be
many networks; requestors and responders may participate in multiple networks.
Requestors ParticipatingResponders
Query
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New York City / New York State Pilot
Dr. Michael Buck, Primary Care Information Project
Aggregated Data Patient Data
Query & Results Reviewer
Data Source
How would a distributed query work?
Information Requester
5. Sends Query Results to Information Requestor
Firewall
3. Distribute Query to Data Sources
1. EHR / Clinical Record
(Patient Data)
2. Query Health Data Model
Note: All patient level data stays behind the firewall.
Translate patient data
4. Execute Query , format
& return Results
Responding Organization
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Type II DiabetesExpanded Analysis Example Result Set
Example Result SetQuery Result for Provider X (where X is each reporting provider):
Gender Age Range Zip Code Setting Encounter
Type Race Ethnicity Insurance Coverage
For specified time frame: (MM-DD-YYYY - MM-DD-YYYY) Total Male Female <18 18 - 64 ≥65 10021 10031 10041 Inpatient Outpatient ED ….. ….. ….. …..
Numerator Counts Risk Score
0-1 2-3 4-5 6-7
HbA1c > 9.0% Blood Pressure ≥ 140/90 mm Hg
LDL ≥ 130 mg/dl Microalbumin > 30 microgram/mg
Creatine BMI ≥ 25 kg/m^2
Smoking Status Foot Examination Eye Examination
Medication - Statin Medication - Asprin
Medication - Ace Inhibitor/ARB Denominator Counts Diagnosis of Diabetes Type I Type II
And all Risks Scores And Hb A1c Result
And BP Reading And LDL Result
And Microalbumin And BMI
And Medications
NYS DOH
NYC PCIP
Information Requestors Data Sources
Axolotl RHIO
Inter-systems
RHIO
eCWEHR
Sends Query to Data Sources
Distributes Query Results to Information Requestor
New York City / New York StatePilot
Sends Query to Data Sources
Distributes Query Results to Information Requestor
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Query Health Technical Approach and Proposed Standards
Vocabulary & Code Sets
Develop modular, testable portfolio of Query Health standards and specifications that can adopted by the industry, and support key HITECH and govt. priorities
Content Structure
Queries & Responses
Privacy & Security
Foundation: Distributed
Query Solutions
SNOMED-CT
Clinical Element Data Dictionary
i2b2
The ResultsNew QRDA 2 & 3
PopMedNet
LOINC ICD-10 RxNorm
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Query Health Standards and Reference Implementation Stack
Reference Implementation
Stack
The QuestionNew HQMF
Query Envelope Privacy Policy Enablement
hQuery
The QueryNew HQMF
• Health Quality Measure Format• HQMF newly modified to
support the needs for dynamic population queries:– More executable – Simplified
• Advantages for query– Avoids “yet another standard”– Secure (vs procedural approach)– Works across diverse platforms
• Benefits – Speed and Cost
The Query Envelope
• Query agnostic• Content agnostic• Metadata facilitates privacy
guidance from HIT Policy Committee
• RESTful interface specification
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The DataClinical Element Data Dictionary
– Demographic– Patient Contact Information– Payer Information– Healthcare Provider – Allergies & Adverse Reactions
– Encounter – Surgery – Diagnosis – Medication – Procedure – Immunization
– Advance Directive – Vital Signs – Physical Exam – Family History – Social History – Order – Result – Medical Equipment– Care Setting– Enrollment– Facility
• ONC S&I Framework deliverable• Standards independent• UML representation underway
The ResultsNew QRDA
• Quality Reporting Document Architecture– Category I – Patient Level– Category II – Patient Populations– Category III – Population Measures
• Query Health will use new definitions of Categories II and III – Not yet specified and balloted– Needs implementation guide– Needs to align with eMeasures
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Query Health How it works together
The path to critical mass
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• Today, distributed queries are generally limited to – Organizations with large IT &
research budgets– Some exceptions (e.g., NYC PCIP,
MDPHNet)• Missing: Primary Care, FQHCs,
CAHs, HIEs, etc… In other words, most places where clinical care is delivered and recorded
• Path to critical mass depends on – Query Health Standards– Health IT vendor participation
Health IT vendorsAllscripts Amazing ChartsAZZLY CernerdbMotion ClinicalWorksEpic eRECORDSIBEZA InterSystemsMedicity MicrosoftNational Health Data SystemsNextGen RelayHealthSiemens
Check back - more to come at QueryHealth.org
The Way Ahead for Query Health
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Demonstrations
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DemonstrationDistributed Query Execution
• What you’ll see– Life cycle of a Distributed Query (1
requestor, 2 data providers)– Policy Enablement Layer (control
of queries execution and results by data providers) – RESTful interface
– Query Envelope metadata for work flow integration and policy enforcement
– Integration of hQuery (Query execution) and PopMedNet (policy enablement)
– Open source components• Presenting
– Marc Hadley, MITRE Corporation– Rob Rosen, Lincoln Peak
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DemonstrationQuery Language• What you’ll see
– Query Composition using i2B2 query builder
– Query representation of i2B2 using internal formats and ontologies
– Translation of composed Query to new HQMF
– Translation of new HQMF to SQL
– Open source components• Presenting
– Shawn Murphy, Partners Healthcare
– Keith Boone, GE Healthcare
Query Health Recap
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