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Tag: The Health Data Goldilocks Dilemma: Sharing? Privacy? Both

Why Should Anyone Care About Health Data Interoperability?

By SUSANNAH FOX

This piece is part of the series “The Health Data Goldilocks Dilemma: Sharing? Privacy? Both?” which explores whether it’s possible to advance interoperability while maintaining privacy. Check out other pieces in the series here.

A question I hear quite often, sometimes whispered, is: Why should anyone care about health data interoperability? It sounds pretty technical and boring.

If I’m talking with a “civilian” (in my world, someone not obsessed with health care and technology) I point out that interoperable health data can help people care for themselves and their families by streamlining simple things (like tracking medication lists and vaccination records) and more complicated things (like pulling all your records into one place when seeking a second opinion or coordinating care for a chronic condition). Open, interoperable data also helps people make better pocketbook decisions when they can comparison-shop for health plans, care centers, and drugs.

Sometimes business leaders push back on the health data rights movement, asking, sometimes aggressively: Who really wants their data? And what would they do with it if they got it? Nobody they know, including their current customers, is clamoring for interoperable health data.

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Thinking ‘oat’ of the box: Technology to resolve the ‘Goldilocks Data Dilemma’

Marielle Gross
Robert Miller

By ROBERT C. MILLER, JR. and MARIELLE S. GROSS, MD, MBE

This piece is part of the series “The Health Data Goldilocks Dilemma: Sharing? Privacy? Both?” which explores whether it’s possible to advance interoperability while maintaining privacy. Check out other pieces in the series here.

The problem with porridge

Today, we regularly hear stories of research teams using artificial intelligence to detect and diagnose diseases earlier with more accuracy and speed than a human would have ever dreamed of. Increasingly, we are called to contribute to these efforts by sharing our data with the teams crafting these algorithms, sometimes by healthcare organizations relying on altruistic motivations. A crop of startups have even appeared to let you monetize your data to that end. But given the sensitivity of your health data, you might be skeptical of this—doubly so when you take into account tech’s privacy track record. We have begun to recognize the flaws in our current privacy-protecting paradigm which relies on thin notions of “notice and consent” that inappropriately places the responsibility data stewardship on individuals who remain extremely limited in their ability to exercise meaningful control over their own data.

Emblematic of a broader trend, the “Health Data Goldilocks Dilemma” series calls attention to the tension and necessary tradeoffs between privacy and the goals of our modern healthcare technology systems. Not sharing our data at all would be “too cold,” but sharing freely would be “too hot.” We have been looking for policies “just right” to strike the balance between protecting individuals’ rights and interests while making it easier to learn from data to advance the rights and interests of society at large. 

What if there was a way for you to allow others to learn from your data without compromising your privacy?

To date, a major strategy for striking this balance has involved the practice of sharing and learning from deidentified data—by virtue of the belief that individuals’ only risks from sharing their data are a direct consequence of that data’s ability to identify them. However, artificial intelligence is rendering genuine deidentification obsolete, and we are increasingly recognizing a problematic lack of accountability to individuals whose deidentified data is being used for learning across various academic and commercial settings. In its present form, deidentification is little more than a sleight of hand to make us feel more comfortable about the unrestricted use of our data without truly protecting our interests. More of a wolf in sheep’s clothing, deidentification is not solving the Goldilocks dilemma.

Tech to the rescue!

Fortunately, there are a handful of exciting new technologies that may let us escape the Goldilocks Dilemma entirely by enabling us to gain the benefits of our collective data without giving up our privacy. This sounds too good to be true, so let me explain the three most revolutionary ones: zero knowledge proofs, federated learning, and blockchain technology.

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Protecting Health Data Outside of HIPAA: Will the Protecting Personal Health Data Act Tame the Wild West ?

Vince Kuraitis
Deven McGraw

By DEVEN McGRAW and VINCE KURAITIS

This post is part of the series “The Health Data Goldilocks Dilemma: Privacy? Sharing? Both?”

Introduction

In our previous post, we described the “Wild West of Unprotected Health Data.” Will the cavalry arrive to protect the vast quantities of your personal health data that are broadly unprotected from sharing and use by third parties?

Congress is seriously considering legislation to better protect the privacy of consumers’ personal data, given the patchwork of existing privacy protections. For the most part, the bills, while they may cover some health data, are not focused just on health data – with one exception: the “Protecting Personal Health Data Act” (S.1842), introduced by Senators Klobuchar and Murkowski. 

In this series, we committed to looking across all of the various privacy bills pending in Congress and identifying trends, commonalities, and differences in their approaches. But we think this bill, because of its exclusive health focus, deserves its own post. Concerns about health privacy outside of HIPAA are receiving increased attention in light of the push for interoperability, which makes this bill both timely and potentially worth of your attention.

HHS and ONC recently issued a Notice of Proposed Rulemaking (NPRM) to Improve the Interoperability of Health Information. This proposed rule has received over 2,000 comments, many of which raised significant issues about how the rule potentially conflicts with patient and provider needs for data privacy and security.

For example, greater interoperability with patients means that even more medical and claims data will flow outside of HIPAA to the “Wild West.” The American Medical Association noted:

“If patients access their health data—some of which could contain family history and could be sensitive—through a smartphone, they must have a clear understanding of the potential uses of that data by app developers. Most patients will not be aware of who has access to their medical information, how and why they received it, and how it is being used (for example, an app may collect or use information for its own purposes, such as an insurer using health information to limit/exclude coverage for certain services, or may sell information to clients such as to an employer or a landlord). The downstream consequences of data being used in this way may ultimately erode a patient’s privacy and willingness to disclose information to his or her physician.”

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HardCore Health Podcast| Episode 3, IPOs, Privacy, & more!

On Episode 3 of HardCore Health, Jess & I start off by discussing all of the health tech companies IPOing (Livongo, Phreesia, Health Catalyst) and talk about what that means for the industry as a whole. Zoya Khan discusses the newest series on THCB called, “The Health Data Goldilocks Dilemma: Sharing? Privacy? Both?”, which follows & discuss the legislation being passed on data privacy and protection in Congress today. We also have a great interview with Paul Johnson, CEO of Lemonaid Health, an up-and-coming telehealth platform that works as a one-stop-shop for a virtual doctor’s office, a virtual pharmacy, and lab testing for patients accessing their platform. In her WTF Health segment, Jess speaks to Jen Horonjeff, Founder & CEO of Savvy Cooperative, the first patient-owned public benefit co-op that provides an online marketplace for patient insights. And last but not least, Dr. Saurabh Jha directly address AI vendors in health care, stating that their predictive tools are useless and they will not replace doctors just yet- Matthew Holt

Matthew Holt is the founder and publisher of The Health Care Blog and still writes regularly for the site.

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