rss
J Am Med Inform Assoc 21:650-656 doi:10.1136/amiajnl-2014-002707
  • Research and applications

Query Health: standards-based, cross-platform population health surveillance

Open Access
  1. Shawn N Murphy1,2,3
  1. 1Partners Healthcare, Boston, Massachusetts, USA
  2. 2Harvard Medical School, Boston, Massachusetts, USA
  3. 3Massachusetts General Hospital, Boston, Massachusetts, USA
  4. 4New York City Department of Health and Mental Hygiene, Queens, New York, USA
  5. 5Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
  6. 6MITRE CORP, Burlington, Massachusetts, USA
  7. 7Allscripts, Burlington, Vermont, USA
  8. 8Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
  1. Correspondence to Dr Jeffrey G Klann, Research Computing, Partners Healthcare System, One Constitution Center, Charlestown, MA 02129, USA; jeff.klann{at}mgh.harvard.edu
  • Received 5 February 2014
  • Accepted 11 March 2014
  • Published Online First 3 April 2014

Abstract

Objective Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level health queries across diverse clinical systems with disparate data models. Here we review Query Health activities, including a standards-based methodology, an open-source reference implementation, and three pilot projects.

Materials and methods Query Health defined a standards-based approach for distributed population health queries, using an ontology based on the Quality Data Model and Consolidated Clinical Document Architecture, Health Quality Measures Format (HQMF) as the query language, the Query Envelope as the secure transport layer, and the Quality Reporting Document Architecture as the result language.

Results We implemented this approach using Informatics for Integrating Biology and the Bedside (i2b2) and hQuery for data analytics and PopMedNet for access control, secure query distribution, and response. We deployed the reference implementation at three pilot sites: two public health departments (New York City and Massachusetts) and one pilot designed to support Food and Drug Administration post-market safety surveillance activities. The pilots were successful, although improved cross-platform data normalization is needed.

Discussions This initiative resulted in a standards-based methodology for population health queries, a reference implementation, and revision of the HQMF standard. It also informed future directions regarding interoperability and data access for ONC's Data Access Framework initiative.

Conclusions Query Health was a test of the learning health system that supplied a functional methodology and reference implementation for distributed population health queries that has been validated at three sites.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/

Related Article

Open Access

Free Sample

This recent issue is free to all users to allow everyone the opportunity to see the full scope and typical content of JAMIA.
View free sample issue >>

Access policy for JAMIA

All content published in JAMIA is deposited with PubMed Central by the publisher with a 12 month embargo. Authors/funders may pay an Open Access fee of $2,000 to make the article free on the JAMIA website and PMC immediately on publication.

All content older than 12 months is freely available on this website.

AMIA members can log in with their JAMIA user name (email address) and password or via the AMIA website.

Navigate This Article