DARTNet Institute log
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:: New Grants and Awards
DI CEO Wilson Pace received the first ever Distinguished Research Mentor Award from the North American Primary Care Research Group (NAPCRG) on October 26. Visit our news page for details. You'll also find details about a number of new DI grants and contracts.

Meaningful Use Stage 2 Specialized Registry option of the Public Health Objective

Participating in the Practice Performance quality improvement registry allows  for Meaningful Use 2 attestation.

Specifically, participation in the DI specialized registry allows Eligible Providers to attest to the Meaningful Use Specialized Registry option of the Public Health Objective.

All physicians who participate in the DI Practice Performance Registry and use a certified EHR technology to provide data meet the Specialized Registry option of the Public Health Objective (and consequently can receive increased revenue).

:: Contact us About the Registry
To learn more about the Registry, complete our online form, email DIRegistry@DARTNet.info, or call Colleen Long at 1-800-434-0278, ext. 8.










Informing Practice: Improving Care

The DARTNet Institute is a rapidly growing collaboration of practice-based research networks that are building a national collection of data from electronic health records, claims, and patient-reported outcomes.

At a glance, the DARTNet Institute is:

A quality improvement registry endorsed by a  national professional society for Meaningful Use 2 attestation.

Secure, reliable datasets of health information from many organizations for improving quality and fostering research.

Researchers examining patient health information to determine what's happening in real-life practice.

Healthcare providers engaging with their peers across the country to learn the best way to care for patients.

The 12 distinct research networks that make up DARTNet Institute offer access to over 12 million patient visits per year, 5 million patient lives, and approximately five billion data points.  

The networks blend quality improvement, effectiveness, and translational research with a data driven-learning system.