Open source software that allows for sharing and integration of mHealth data poses tremendous benefit for diagnosing, treating and preventing disease as well as the development of a more tailored patient healthcare strategy, according to Ida Sim, Ph.D, professor of medicine at University of California, San Francisco.
But attaining that next level in healthcare requires overcoming more than a few challenges, such as establishing data standards to eliminate ambiguity and improved integration of data streams from the various mHealth devices and apps, Sim says in an interview with Scope, the Stanford University School of Medicine blog. Sim is co-director of Biomedical Informatics at UCSF's Clinical and Translational Sciences Institute and co-founder of nonprofit Open mHealth.
"Currently, wearable devices and other healthcare tools describe the data they collect using their own languages that are not shared or integrated with other devices," she says. "For clinicians, these kinds of ambiguities are show stoppers that lock up the potential of digital health data."
Patients are eager for a tailored, or customized, treatment approach. Diabetics age 50 and older are interested in mobile apps in treatment and care, but say the apps should be customized, according to a study published in the Journal of Medical Internet Research. And a recent Intertek whitepaper notes obstacles to mHealth apps also include a lack of specific healthcare knowledge and ignorance on required privacy protection for data.
The Open mHealth organization is developing application program interface tools to drive data interoperability and build clinically valid schemas that meld with existing clinical standards to eliminate confusion on data point references, Sim says.
"Beyond creating a common language for understanding what data points mean, we must also represent them in ways that allow clinicians to make healthcare decisions with the greatest ease and effectiveness," she says.
Regarding the issue of privacy with digital health data, Sim says users should have data ownership and control to allow or deny access, as well as the ability to transfer data from one system to another.
"Patients should also be able to have much more granular control over their data, deciding which data can be shared with which systems under which circumstances," she says. "We are still a ways off from this model of data ownership, but as more and more devices and digital health systems are introduced, it seems likely that our existing, quite limited framework of patient privacy will change."
For more information:
- read the blog interview
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