Home > Recent Projects > EPCS

Measuring HIE on a National Level
via Direct Data Collection

The Office of the National Coordinator (ONC) commissioned Sujansky & Associates to explore the feasibility of measuring health information exchange (HIE) via objective data collected from health information networks (HINs), as a supplement to the subjective survey instruments currently used to measure HIE. Examples include lists of organizations that participate in HINs, logs of HIE transactions, and quality assessments of exchanged documents. ONC hypothesizes that this method of data collection may provide more objective, consistent, and comprehensive metrics for assessing the extent and nature of health information exchange in the U.S., both across regions and over time.

Sujansky & Associates conducted structured interviews with 10 prominent health information networks, including national, regional, and vendor-based organizations. Based on interview findings, recommendations were made for near-term, medium-term, and long-term metrics that can be comparable across geographic regions and time periods, and that data collected from HINs will be able to support.

Relevant documents:

Measuring Health Information Exchange On a National Level Via Direct Data Collection: An Initial Study of Feasibility and Next Steps (PDF)

Sujansky & Associates' role in this project included:

  • Developing a structured interview guide to solicit key information from health information networks.

  • Recruiting major U.S. HINs and conducting in-depth interviews with key personnel.

  • Based on findings, developing a reference model for measuring HIE participation rates, transaction types, transaction volumes, and transaction value.

  • Proposing feasible near-term (1 year), medium term (2-4 years), and long-term (5+ years) measures of health information exchange based on objective data from HINs.

  • Delivering a comprehensive report on the project findings and recommendations.



Significant variability exists among the data currently collected by HINs.

As a result, the only metrics that can be aggregated across HINs in the near term will be general and high level.

However, in the medium and long terms, HINs should be able to refine their data-collection processes to support much more granular and informative metrics.