Digital Health Update: Getting to the Right Data

by Design Science

At various events this spring, experts discussed the challenges of how to get and use data captured from digital health devices.

“Data still isn’t at the center of healthcare.” That was a resonating phrase, uttered by big data proponent Atul Gawande at the 5th Annual Health Datapalooza, as reported by the website Government Health IT. The digital health event was held June 1-3, by the Data Health Consortium in Washington, DC and featured thought leaders in the healthcare data sector, including Gawande as a keynote speaker. Gawande is a professor of surgery at Harvard Medical School and published author on the subject of data in healthcare.

And of course, Gawande wasn’t talking about the bulk of data, but the Right Data—the information that gets to the root of a patient’s problems, particularly those that go beyond a doctor visit ending with a prescription.

He told Datapalooza attendees that to make healthcare scalable “we have to make the invisible visible."

It means that care providers can and should try to obtain data about the whole experience of a patient, including home, work, and hobbies. With access to better data, providers might see possible misdiagnoses or miscalculations. For example, Gawande brought up a few case studies that he learned about through working with RiskAnalytics Inc. The patients he discussed were among the sickest in the particular study: a blind diabetic was failing to properly load his syringe; an allergy patient was living in a condemned home with exposed mold—he also needed a vacuum cleaner; a migraine patient racked up 29 visits in 10 months to the emergency room after having been prescribed the incorrect medication.

Such cases seem to have obvious, even simple, solutions, but to find the right solutions the caregivers need the right data—data about the those aspects of a patient’s life that matter for a given condition.

Wearable Sensors and Notions of Privacy

This is where wearable sensors, like those from the consumer space, can serve a great purpose in collecting health metrics and providing data to all relevant parties. However, a few things would have to change for this approach to be effective.

Compliance is one issue. Patients would have to consistently generate the necessary data. I recently had a conversation over Twitter with Aaron Sklar, Managing Director of Experience Strategy and Design at Healthagen, during which I asked him how we could ensure wearables compliance. His response was understandable: “The word compliance feels out of place to me. Aren’t wearables voluntary?”

Wearables are certainly voluntary—in fact, at least a third of users abandon wearable fitness tools after only a few months. Fitbits and Jawbones, Galaxy Gear, and other products of hip tech trends are often left on the shelf or sold on eBay long before lasting behavioral changes can take place.

And if actually collecting data is a challenge, sharing those data may be an even bigger challenge. As of yet, there is no system for putting data sharing in place to truly ensure that information gets to someone (e.g., a primary caregiver) who can look at the big picture. In April, Leslie Saxon, Chief of Cardiovascular Medicine at the USC’s Keck School of Medicine, spoke to a Wired UK audience about getting data to the right people. Saxon told the audience that “excessive concern about digital privacy will impede the progress of global health.”

Her point was that “indiscriminate multisource data streams” are absolutely essential to patient care, but our notions (and laws) regarding medical privacy may have to change to have access to these data streams. The solution proposed by Saxon is to leverage social media and gaming, which already has personal data.

Are we ready to leverage Facebook in order to provide better data to our physicians? Saxon suggests that the compromise of privacy would be worth it for the improved healthcare. Do you agree?

 

Share this entry

Previous
Previous

Hi from Sunny California!

Next
Next

Seven Mistakes to Avoid During Usability Testing