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Snoop Last Year’s Bayer G4A Startups, Then Apply

SPONSORED POST

By JESSICA DA MASSA, WTF HEALTH

With the application deadline for Bayer’s G4A Partnerships program coming up on Friday, I thought I’d throw out a little inspiration to would-be applicants by featuring an interview I did with one of last year’s program participants at the grand-finale Launch Event.

Not only was this a great party, but a microcosm of the G4A program experience itself: a way to meet Bayer execs en-masse, an opportunity to sell directly to key decision-makers across Bayer’s various global business units, and a chance to feed off the energy of like-minded innovators eager to see ‘big health care’ change for the better.

While the G4A program itself has changed a bit this year to be more streamlined and to allow for bespoke deal-making that may or may not involve giving up equity (my favorite new feature), startups questioning whether or not they have what it takes should take a look at some alums.

There’s a playlist with nearly two dozen interviews waiting for you here if you’re REALLY up for some procrastinating, or you can click through and just check out my chat with Joe Curcio, CEO of KinAptic. A healthtech startup taking wearables to the bleeding edge, Joe shows us a mock-up of the KinAptic ‘smart shirt’ which features their real innovation: printed ink electronics that look and feel like screenprinting ink, but work bi-directionally to both collect data from the body AND apply signals back to it. Is it AI-enabled? Did you have to ask? Listen in for a mindblowing chat about how this tech can change diagnostic analysis and treatment and completely redefine our current limitations when it comes to healthcare wearables.Once you’re inspired, don’t forget to head over to www.g4a.health and fill out your own application for this year’s partnership program.

Jessica DaMassa is the host of the WTF Health show & stars in Health in 2 Point 00 with Matthew Holt

We Are Not A Dashboard: Contesting The Tyranny Of Metrics, Measurement, And Managerialism

By DAVID SHAYWITZ

The dashboard is the potent symbol of our age. It offers the elegant visualization of data, and is intended to capture and represent the performance of a system, revealing at a glance current status, and pointing out potential emerging concerns. Dashboards are a prominent feature of most every “big data” project I can think of, offered by every vendor, and constructed to provide a powerful sense of control to the viewer. It seemed fitting that Novartis CEO Dr. Vas Narasimhan, a former McKinsey consultant, would build (then tweet enthusiastically about) “our new ‘control tower’” – essentially a multi-screen super dashboard – “to track, analyse and predict the status of all our clinical studies. 500+ active trials, 70+ countries, 80 000+ patients – transformative for how we develop medicines.” Dashboards are the physical manifestation of the ideology of big data, the idea that if you can measure it you can manage it.

I am increasingly concerned, however, that the ideology of big data has taken on a life of it’s own, assuming a sense of both inevitability and self-justification. From measurement in service of people, we increasingly seem to be measuring in service of data, setting up systems and organizations where constant measurement often appears to be an end in itself.

My worries, it turns out, are hardly original. I’ve been delighted to discover over the past year what feels like an underground movement of dissidents who question the direction we seem to be heading, and who’ve thoughtfully discussed many of the issues that I stumbled upon. (Special hat-tip to “The Accad & Koka Report” podcast, an independent and original voice in the healthcare podcast universe, for introducing me to several of these thinkers, including Jerry Muller and Gary Klein.)

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ONC & CMS Proposed Rules – Part 5: Business Models

Grant Barrick
Dave Levin

By DAVE LEVIN, MD and GRANT BARRICK

The Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) have proposed final rules on interoperability, data blocking, and other activities as part of implementing the 21st Century Cures Act. In this series, we will explore the ideas behind the rules, why they are necessary and the expected impact. Given that these are complex and controversial topics open to interpretation, we invite readers to respond with their own ideas, corrections, and opinions. In part five of this series, we look at how competition unlocks innovation, and how the proposed rules may disrupt the balance between innovation, intellectual property (IP), and supporting business models.  

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The recent publication of proposed rules by ONC and CMS set off a flurry of activity. In anticipation of their implementation, the health care industry is wrestling with many questions around business models. What practices inhibit competition and innovation? How do we balance the need for competition while protecting legitimate intellectual property rights? How can vendors ensure profit growth when pricing is heavily regulated? In this article, we will examine how competition unlocks innovation and the possible disruptions the proposed rules may bring for innovation, intellectual property (IP) and supporting business models.

Unlocking Innovation via Competition

In most markets, innovation is driven forward by competition. Businesses compete on equal footing, and their investment in R&D drives innovation forward. Innovation in health care has been dramatically outpaced by other markets, leading to an urgent need for both disruptive and evolutionary innovation.

What is inhibiting health care innovation? The rules identify a combination of tactics employed in health care that restrict the free flow of clinical data, such as:

  • NDAs
  • Confidentiality Clauses
  • Hold-harmless Agreements
  • Licensing Language

These tactics slow innovation by contributing to an environment where stakeholders resist pushing the boundaries — often because they are contractually obligated not to. The legislation and proposed rules are designed to address the ongoing failure of the market to resolve these conflicts.

As the rules are finalized, we will continue to monitor whether the ONC defines these practices as innovation stifling and how they will implement regulations — both carrot and stick — to move the industry forward.

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ONC & CMS Proposed Rules – Part 4: Information Blocking

By DAVE LEVIN MD

The Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) have proposed final rules on interoperability, data blocking and other activities as part of implementing the 21st Century Cures Act. In this series, we will explore ideas behind the rules, why they are necessary and the expected impact. Given that these are complex and controversial topics open to interpretation, we invite readers to respond with their own ideas, corrections and opinions.

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When it comes to sharing health data, the intent of the 21st Century Cures Act is clear: patients and clinicians should have access to data without special effort or excessive cost. To make this a reality, the act addresses three major areas: technical architecture, data sets and behaviors. Part two of our series looked at how APIs address technical issues while part three covered the new data requirements. In this article, we delve into information blocking. A companion podcast interview with ONC expert Michael Lipinski provides an even deeper dive into this complex topic.

Information Blocking Comes in Many Forms

The Public Health Services Act (PHSA) broadly defines information blocking as a practice that is “likely to interfere with, prevent, or materially discourage access, exchange, or use of electronic health information.” The overarching assumption is information will be shared though the Act does authorize the Secretary to identify reasonable and necessary exceptions.

The proposed rules focus on “technical requirements as well as the actions and practices of health IT developers in implementing the certified API.” Information blocking can come in a variety of forms. It can be direct and obvious (“No you can’t have this data ever!”) or indirect and subtle (“Sure, you can have the data, but it will cost you $$$ and we won’t be able to get to your request for at least 12 months.”). The proposed rules are designed to address both. This passage illustrates some of the concerns:

“Health IT developers are in a unique position to block the export and portability of data for use in competing systems or applications, or to charge rents for access to the basic technical information needed to facilitate the conversion or migration of data for these purposes.”

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XX Marks the Spot: Why Did Women Tech Experts Rule at DC Health Data Confab?

By MICHAEL L. MILLENSON

Three government experts on a health tech conference panel discuss the urgency of releasing actionable data; all are women. A more senior official, another woman, gives a TED-style talk making the same case. And a four-person, private-sector panel debates privacy and ethics; three of the four are female.

Health Datapalooza, a conference begun with government sponsorship a decade ago, proclaims its goal as “data liberación” – freeing health data from deep within federal agencies and giving it to patients and entrepreneurs. But in 2019, women’s “liberación” seems to have become an unspoken sub-theme.

Interestingly, while women’s status in tech was the focus of a plenary panel on diversity and inclusion, the panelists seemed oblivious to the robust participation of women in their own meeting.

To put some data behind my subjective impressions, I went back and examined the list of speakers, who came from a wide range of organizations and included individual patient activists. I counted 89 men and 99 women. Liberación, indeed.

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ONC & CMS Proposed Rules – Part 3: Data Requirements

Matt Humphrey
Dave Levin

By DAVE LEVIN, MD and MATT HUMPHREY

The Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) have proposed final rules on interoperability, data blocking and other activities as part of implementing the 21st Century Cures Act. In this series, we will explore the ideas behind the rules, why they are necessary and the expected impact. Given that these are complex and controversial topics open to interpretation, we invite readers to respond with their own ideas, corrections and opinions. In part three of this series, we look at how the new USCDI draft helps foster innovation.  

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The U.S. Core Data for Interoperability (USCDI) draft is a step forward toward expanding the 21st Century Cures Act. The Cures Act was helpful in moving the needle for interoperability and defining data blocking. The latest draft of the USCDI is meant to further specify what data should be shared freely.

In this article, we’ll look at the data added to the Common Clinical Data Set (CCDS) used for ONC certification. We’ll walk through the proposed plan to add more data over time. And we’ll explore why this is a step in the right direction toward increased data sharing.

New Shared Data

The bulk of the datasets in the USCDI comes from the Common Clinical Data Set (CCDS), which was last updated in 2015. The new USCDI draft adds two types of data:

  • Clinical notes: both structured and unstructured. EHRs store these notes differently, but both are important and helpful in data analysis.
  • Provenance:  an audit trail of the data, showing where it came from. It is metadata, or information about the data, that shows who created it and when.

The Fast Healthcare Interoperability Resources (FHIR) have created standards around APIs used to access health care data. APIs developed under the FHIR standard aligns with the USCDI to meet the proposed certification rules. The USCDI draft recommends using a FHIR compliant API to access the data.

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ONC’s Proposed Rule is a Breakthrough in Patient Empowerment

By ADRIAN GROPPER

Imagine solving wicked problems of patient matching, consent, and a patient-centered longitudinal health record while also enabling a world of new healthcare services for patients and physicians to use. The long-awaited Notice of Proposed Rulemaking (NPRM) on information blocking from the Office of the National Coordinator for Health Information Technology (ONC) promises nothing less.

Having data automatically follow the patient is a laudable goal but difficult for reasons of privacy, security, and institutional workflow. The privacy issues are clear if you use surveillance as the mechanism to follow the patient. Do patients know they’re under surveillance? By whom? Is there one surveillance agency or are there dozens in real-world practice? Can a patient choose who does the surveillance and which health encounters, including behavioral health, social relationships, location, and finance are excluded from the surveillance?

The security issues are pretty obvious if one uses the National Institutes of Standards and Technology (NIST) definition of security versus privacy: Security breaches, as opposed to privacy breaches, are unintentional — typically the result of hacks or bugs in the system. Institutional workflow issues also pose a major difficulty due to the risk of taking responsibility for information coming into a practice from uncontrolled sources. Whose job is it to validate incoming information and potentially alter the workflow? Can this step be automated with acceptable risk?

It’s not hard to see how surveillance as the basis for health information sharing would be contentious and risk the trust that’s fundamental to both individual and public health. Nowhere is this more apparent than in the various legislative efforts currently underway to expand HIPAA to include behavioral health and social determinants of health, preempt state privacy laws, grant data brokers HIPAA Covered Entity status, and limit transparency of how personal data is privately used for “predictive analytics”, machine learning, and artificial intelligence.

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For Your Radar — Huge Implications for Healthcare in Pending Privacy Legislation

By VINCE KURAITIS and DEVEN McGRAW

Two years ago we wouldn’t have believed it — the U.S. Congress is considering broad privacy and data protection legislation in 2019. There is some bipartisan support and a strong possibility that legislation will be passed. Two recent articles in The Washington Post and AP News will help you get up to speed.

Federal privacy legislation would have a huge impact on all healthcare stakeholders, including patients.  Here’s an overview of the ground we’ll cover in this post:

  • Why Now?
  • Six Key Issues for Healthcare
  • What’s Next?

We are aware of at least 5 proposed Congressional bills and 16 Privacy Frameworks/Principles. These are listed in the Appendix below; please feel free to update these lists in your comments.  In this post we’ll focus on providing background and describing issues. In a future post we will compare and contrast specific legislative proposals.

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Obsessive Measurement Disorder: Etiology of an Epidemic

By KIP SULLIVAN JD Kip Sullivan

Review of The Tyranny of Metrics by Jerry Z. Muller, Princeton University Press, 2018

In the introduction to The Tyranny of Metrics, Jerry Muller urges readers to type “metrics” into Google’s Ngram, a program that searches through books and other material published over the last five centuries. He tells us we will find that the use of “metrics” soared after approximately 1985. I followed his instructions and confirmed his conclusion (see graph below). We see the same pattern for two other buzzwords that activate Muller’s BS antennae – “benchmarks,” and “performance indicators.” [1]

Muller’s purpose in asking us to perform this little exercise is to set the stage for his sweeping review of the history of “metric fixation,” which he defines as an irresistible “aspiration to replace judgment based on personal experience with standardized measurement.” (p. 6) His book takes a long view – he takes us back to the turn of the last century – and a wide view – he examines the destructive impact of the measurement craze on the medical profession, schools and colleges, police departments, the armed forces, banks, businesses, charities, and foreign aid offices.

Foreign aid? Yes, even that profession. According to a long-time expert in that field, employees of government foreign aid agencies have “become infected with a very bad case of Obsessive Measurement Disorder, an intellectual dysfunction rooted in the notion that counting everything in government programs will produce better policy choices and improved management.” (p. 155)

Muller, a professor of history at the Catholic University of America in Washington, DC, makes it clear at the outset that measurement itself is not the problem. Measurement is helpful in developing hypotheses for further investigation, and it is essential in improving anything that is complex or requires discipline. The object of Muller’s criticism is the rampant use of crude measures of efficiency (cost and quality) to dish out rewards and punishment – bonuses and financial penalties, promotion or demotion, or greater or less market share. Measurement can be crude because it fails to adjust scores for factors outside the subject’s control, and because it measures only actions that are relatively easy to measure and ignores valuable but less visible behaviors (such as creative thinking and mentoring). The use of inaccurate measurement is not just a waste of money; it invites undesirable behavior in both the measurers and the “measurees.” The measurers receive misleading information and therefore make less effective decisions (for example, “body count” totals tell them the war in Viet Nam is going well), and the subjects of measurement game the measurements (teachers “teach to the test” and surgeons refuse to perform surgery on sicker patients who would have benefited from surgery).

What puzzles Muller, and what motivated him to write this book, is why faith in the inappropriate use of measurement persists in the face of overwhelming evidence that it doesn’t work and has toxic consequences to boot. This mulish persistence in promoting measurement that doesn’t work and often causes harm (including driving good teachers and doctors out of their professions) justifies Muller’s harsh characterization of measurement mavens with phrases like “obsession,” “fixation,” and “cult.” “[A]lthough there is a large body of scholarship in the fields of psychology and economics that call into question the premises and effectiveness of pay for measured performance, that literature seems to have done little to halt the spread of metric fixation,” he writes. “That is why I wrote this book.” (p. 13)

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Innovation Amidst the Crisis: Health IT and the Opioid Abuse Epidemic | Part 3 – Clinical Decision Support

By COLIN KONSCHAK, FACHE and DAVE LEVIN, MD

Dave Levin

Colin Konschak

The opioid crisis in the United States is having a devastating impact on individuals, their families, and the health care industry. This multi-part series will focus on the role technology can play in addressing this crisis. Part one of the series proposed a strategic framework for evaluating and pursuing technical solutions.

A Framework for Innovation

As noted in part one of our series, we believe the opioid crisis is an “All Hands-On Deck” moment and health IT (HIT) has a lot to offer. Given the many different possibilities, having a method for organizing and prioritizing potential IT innovations is an important starting point. We have proposed a framework that groups opportunities based on an abstract view of five types of functionality. In this article we will explore the role of technologies that provide clinical decision support.

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