BOSTON—An interdisciplinary team was key to the successful implementation of interactive visualization within the EMR at The Ohio State University, said Randi Foraker, PhD, of the university’s College of Public Health, speaking at the Bio-IT World Congress on April 7.

With a background in public health, Foraker collaborated with clinicians and biomedical informaticists to achieve the visualization that brings information to life—“the promise of the EMR.”

They started with cardiovascular health in primary care. “We chose cardiovascular disease as a test case because it’s my area of expertise but also the leading cause of death. Less than 1 percent of the U.S. population is at ideal levels for the risk factors that contribute to cardiovascular disease.”

The visualization is created within the EMR through autopopulation of patient data at the point of care. The app displays the information for quick and easy understanding by both the provider and the patient.

“We recognize the huge opportunity to leverage the EHR to effect change in these elements by bringing to bear all of these risk factors at the point of care,” Foraker said. Clinicians can target the ones that need to be improved to move the whole patient population toward better health.

Foraker views this process as an "informatics intervention where we are applying personalized medicine at a population level."

Users of the tool see the patient’s overall cardiovascular health score where 100 percent is the goal. They can scroll down to find diet parameters, physical activity and more. That information probably is not in the EHR or there in a format that can’t be sent to this app, she noted. So, they created a questionnaire in the PHR for patients to complete before their appointment. They usually end up with the app about halfway prepopulated. For the other half, the provider fills it in with the patient, which allows for some counseling and behavior and lifestyle advice.

Foraker and her team also made the app capable of querying historical data for medications and lab results, bringing together various components of the EHR in one convenient tool. “In terms of public health, we turned prevention into clinical guidelines providers can follow and made it easy for them to follow those guidelines.” They also incorporated the American Heart Association’s cardiovascular health metric algorithm.

The app uses the stoplight scheme which has been shown to help address those with low health literacy better understand their risk, she said.

The app was implemented in a random trial among clinics. Those that used the app found that patients improved their healthy body weight from baseline as well as the fasting blood glucose score. Those that didn’t use the app found that patients’ weight stayed the same from baseline and their fasting blood glucose worsened.

The team also wanted provider feedback on the app and, on a scale of 1 to 5, earned relatively high scores: for example, 3.8 for content, 4.3 for accuracy and 4.1 for format.

Looking forward, Foraker said she wants to try the app for oncology assessments because most cancer survivors should be more worried about their cardiovascular health than the risk of a recurrence. Feedback from cardiologists will “allow us to continue to develop this app and apps like it.”

The app was developed to be platform-independent although Foraker has been running it in an Epic environment. There is potential to use similar apps in other settings and expand the included guidelines. “This doesn't have to be only about cardiovascular health. We are only limited by the features of EHR platforms in terms of which guidelines we include.”

The app testing has garnered lots of lessons, she said. She found they could query data from different places in the EHR quickly and make these data actionable which is “going to be critical moving forward. There is huge potential to leverage the EHR for interventions like this—to really engage people not around sick care but around healthcare.”