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Lesson 9: Data Query in a Federated Environment

• Distributed query: securely obtaining useful data from diverse EHR systems and other sources.
• ONC supported Query Health initiative.
• Query Health initiative related video (The first 18 minutes is a good general introduction to distributed query that you should watch. The rest describes individual query reporting systems.)

Slides from the video

• Govern is more important

why do we need distributed systems

hQuery

• hQuery's goal: simplicity. limited but well standardized data set (in quality measurement and other common clinical activities).
• point-and-click interface (called the hQuery composer) to non-technical healthcare providers.
• the possible queries are somewhat limited.
• hQuery uses a simple patient information model to facilitate query building by nontechnical users.
• hQuery Gateway
  • located at source system
  • receives queries in a standard format
  • forwards queries to an adapter
  • the adapter translates the query, receives response and converts it into the standard data model for transmission back.
• Video about hQuery.
• HQuery presents results in an attractive way (frequency, time and geographic distributions). 

• the curly braces problem is a technical sub-issue of interoperability problem

 Informatics for Integrating Biology and the Bedside (i2b2)

• is NIH-funded effort based at Partners HealthCare System in Boston, Mass. * mission: enable clinical investigators to conduct research using genomics and biomedical informatics.
• is sophisticated to support complex research environments
• provides an easily understood database schema

• i2b2 “cells” communicate via web services and are together called a “hive”.
• Custom cells can be added to the hive.
• i2b2 users group (share information and applications; create the potential for translational research)

• extracting clinical concepts or features from free text format clinical notes

PopMedNet

• each source to maintain control of its data (sometimes referred to as “data lockers”)
• be capable of accepting and responding to queries.
• PopMedNet is intended to support medical product safety analysis

Query Health

distributed query standards.

Four kinds of standards:

1. Envelope standards: define the package for sending/receiving queries
2. Format standards: provide a Declarative specification of the query
3. Results standards (such as QRDA): specify the format and packaging of the query results
4. Data Model standards (such as CEDD common data element definitions): specify the data model that will link data from the contributing systems.

• Declarative specification: expresses the desired result.
• Procedural specification: provides a recipe for achieving the goal
• E.g. 1 Curly braces problem with the Arden syntax. Arden provides a declarative standard but the procedure will be different depending on the system that is the source of the data.
• e.g. 2 The hQuery Gateway receives a standard query on one side but knows how to get it done on the other.

Query envelope standard

The Query Envelope standard serves to provide

• identification that is unique within the network;
• the information requestor ID including name, email and organization;
• the purpose, priority and type of the query
  • 7 purpose codes (e.g. TREAT for treatment),
  • its Priority from 1-5 (1 highest),
  • its type Type, 1-20 characters
• PHI level (Aggregated, Limited, De-identified, PHI)
• its Timing, Submission date/time and optional execution date/time.

Query Format

• the Health Quality Measure Format (HQMF): an HL7 standard format for documenting the content and structure of a quality measure in an XML document format based on the HL7 RIM.
• It can consist of three levels of detail:
  • metadata: who wrote it, the dates over which it is valid, who validated it, and other details about how the measure works or is used;
  • human narrative: measure description, data criteria, measure population and measure observations;
  • computer instructions: how to count and compute the results of the measure.
• The example XML provides instructions to the computer to only include patients who have had a weight measured, presumably in the numerator of a weight screening quality metric that, as you should recall from Lesson 2, is a requirement of Meaningful Use.

the standard for query results

• QRDA in Lesson 8. Results can be reported at three levels of detail: patient-level, patient-list level or aggregate level.
• Example: the two result templates refer to NQF defined quality measures for inpatient asthma care.

 Query Data Dictionary

• The Clinical Element Data Dictionary (CEDD): use in setting up source data in support of distributed queries within a larger Query Health solution.
• it is not intended as a new standards development effort and began with the elements already specified in the CCD and which most EMRs already support
• Here’s a simple example for the patient allergy data element showing how it ties to already accepted standards used in the CCD.

Recap

In this lesson we

• examined how data from multiple EHR systems can be queried and aggregated for diverse purposes.
  • e.g. quality reporting and advanced clinical research.
• All of these technologies provide a framework over the many non-interoperable EHR systems.
• Different technological solutions each of which is optimized for a specific problem in a specific cross-institutional context.

Supplementary resources

Key Concepts/Vocabulary

●Distributed query ● Distributed query standards ● Data warehouse ● Data lockers ● hQuery ● i2b2 ● PopMedNet ● Query Health ● Health Quality Measure Format (HQMF) ● Quality Reporting Document Architecture (QRDA)

Readings

• QDM Version 4.1 Specification
• QRDA Implementation Guide for category I and III reporting

Videos

• Query Health Initiative
• i2b2 demo
• i2b2 and PopMedNet integration

Graphics

• hQuery query screen
• Query Health pilot proposal

2015-10-19 初稿