The digital revolution’s merging of medicine with high tech has unleashed massive amounts of data about the most intimate details of our life — what we ate, how far we walked, how fast our heart beat. As a result, what constitutes health data is no longer so easily defined. Neither is how the information is used.
With rise of machine learning, those questions are becoming increasingly urgent, especially with the move of high tech companies into the clinical sphere, according to health data transparency advocate Dr. Eric Topol.
The first step is to put the power over those decisions in the hands of the people who are producing 2.5 quintillion bytes of data every day, according to Topol in a new commentary in Nature co-authored by John Wilbanks, chief commons officer at Sage Bionetworks, a biomedical research nonprofit in Seattle. The commentary, tellingly, is headlined, “Stop the privatization of health data.”
“The digital health revolution only works if we place the patient in control of how and where their data is shared,” they wrote.
Topol is the director of the Scripps Translational Science Institute, and chief academic officer of Scripps Health in San Diego. He has written about the issue of patient access starting with medical records. But the issue has reached a new urgency, he and Wilbanks argued, because of the increasing use of sophisticated programs to understand the treasure trove of machine-readable data.
“Many of the new entrants to health, unbound by fragmented electronic health-record platforms, are poised to amass war chests of data and enter them into systems that are already optimized (primarily for advertising) to make predictions about individuals,” as they put it.
A Deep-dive Into Specialty Pharma
A specialty drug is a class of prescription medications used to treat complex, chronic or rare medical conditions. Although this classification was originally intended to define the treatment of rare, also termed “orphan” diseases, affecting fewer than 200,000 people in the US, more recently, specialty drugs have emerged as the cornerstone of treatment for chronic and complex diseases such as cancer, autoimmune conditions, diabetes, hepatitis C, and HIV/AIDS.
They cited Google’s calculation that of the 40,000 or so searches people make every second, 2,000 are health-related. People may have dealt with the bureaucratic tug-of-war over getting their medical records. But Google subscribers (let alone users of data-generating wearables like Fitbit) may be surprised to find out just how hard it is to find out what the company knows about them and what it is doing with their search data.
Or consider the example in the commentary of the wearable device Enlite, which was made available by Medtronic to people with diabetes in 2013. Although patients could monitor their glucose levels at any instant, they didn’t have access to their aggregate records. The company refused patient requests their own heart data, as illustrated by the saga of activist patient Hugo Campos.
The commentary didn’t offer up solutions, but the authors did provide examples of alternative models. Participants in Sage’s mPower iPhone app-based study can access their data. Likewise, IBM customers who store their data in the cloud are given access to algorithms that can help them to make sense of the health data being collected. (Sage Bionetworks stores data from participants in a Stanford University study, MyHeart Counts. Stanford controls the access to data, Sage President Lara Mangravite said.)
The bottom line is that all studies that enroll participants should guarantee the right of data download and access to the participants, Wilbanks said in a follow-up email. Most will not access their data, he said. But those who do will be able spot errors and discriminatory health actions, he said.
Wilbanks also believes that given the choice individuals will share their data for the use in other research. “They will enable transformative change,” he said.
Photo: Flickr user Infocux Technologies
