Capturing Threats to Electronic Medical Records More Quickly

Software developed through DreamIt Health Baltimore identifies unauthorized access to electronic medical records in Epic.

Published in Insight - May 2015

With the adoption of electronic medical records, the incidence of medical identity theft is on the rise. According to a study sponsored by the Medical Identity Fraud Alliance, medical identity theft has nearly doubled over the last five years. A major challenge to stopping these incidents is that it can take months to discover them. 

On a mission to protect patients’ health information, The Johns Hopkins Hospital and Johns Hopkins Bayview Medical Center are testing new software designed to more quickly detect and analyze unauthorized access of electronic medical records everywhere Epic is deployed.

“We care deeply about protecting patient privacy,” says Peter Greene, chief medical information officer for Johns Hopkins Medicine. “We have an innovation imperative, and we’re trying to make these information technology systems smarter.”

The software is the product of Protenus, a startup company formed through DreamIt Health Baltimore. The four-month program, sponsored in part by Johns Hopkins, helps entrepreneurs accelerate product development for health IT startup companies.

The co-founders of Protenus — Robert Lord, a hedge fund associate, and Nick Culbertson, a Special Forces operator — left their careers to attend medical school at The Johns Hopkins University and later developed the software through the DreamIt program.

In testing, the software has identified patterns of access that deviate from the norm and has provided these tips to designated officers who can investigate. Soon, the software will provide daily and then real-time reports. By summer 2015, the system could be in use at institutions outside of Johns Hopkins.

“We’re not seeing any other companies doing what they are able to do in prototype form at the capacity they are doing it,” says Greene, an advisor to Protenus. “Their novel analytic techniques are uncovering some impressive findings, such as how access patterns differ between clinicians and researchers.”