A collaborative team of researchers from the Digital Medicine Society (DiMe) and biomedical engineers at Duke University have developed a framework that will help data scientists and other researchers use better digital health tools for clinical purposes.
As smartwatches and other wearable technologies are becoming more popular, researchers are exploring how they can use biometric data collected by these tools to create beneficial health insights about the users. Although some of these devices are marketed as being clinically validated, there are currently no standards t oensure that the data from digital medicine tools is evaluated and fit for clinical purposes.
In a new paper, Jessilyn Dunn, an assistant professor of biomedical engineering at Duke University, worked with an interdisciplinary, international team of 16 researchers from the DiMe community to propose a three-step framework that evaluates and documents the clinical usefulness of these tools, addressing shortcomings with the current approach to evaluating digital health tools.
The project is one of several collaborations between Dunn and the expert DiMe community that include co-participation in a World Economic Forum initiative focused on managing epidemics with consumer wearables.
The paper appeared on April 14 in the journal npj Digital Medicine.
“In the last decade alone we’ve seen digital biomarker research increase by more than 325 percent, but we haven’t caught up with this growth in terms of standards and evaluation of digital medicine tools,” said Brinnae Bent,” a Ph.D. student in the Dunn lab and one of the authors of the paper. “Our main goal was to develop a common framework for evaluating these new technologies, but we also wanted to create a unifying language for the field so there’s structure as it grows.”
During the evaluation of more traditional medical devices, engineers will verify