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