Tag: Data

Health Innovation & Data: Five Common Missteps (and How to Interrupt Them)

Nov 29, 2023

By MARIE COPOULOS

I’ve had the great fortune of spending much of my career at the intersection of health care innovation and the underlying data that drives new models.

For those of us who’ve worked in this space for a long time, there’s a certain pattern recognition that comes with this work that is often immediate and obvious – both in terms of really cool developments but also gotchas. “Ah, you’re stumbling here. Everyone does that.”

The challenge, I’ve found, is that these ‘gotchas’ that can be so visible to the folx who’ve worked in health tech for the past few decades can be counterintuitive in the business and even met with resistance. Why?

I’m going to focus here on pattern recognition, with the goal of highlighting common stumbling blocks and, critically, ways you can interrupt them if you see them.

Pattern #1: Lacking a Clear-Eyed View of Market Data Gaps
Key Question: Do you understand how the market you’re in informs your ability to measure your work and use data to drive insight?

For those of you building models that change the status quo – this is for you. By nature these innovations break from existing care and financial models with the goal to improve them. We need this in health care. However, it’s common to overlook the fact that breaking with the status quo also breaks with the ways that we capture and serve up health data.

To this end, don’t assume you will be able to measure and show success, and that the data you need must be out there. The true differentiator is for both to align. Design with intention.

If you’re at the stage of thinking about a productized solution to a health care problem, then it is also the right time to look at the market with a lens toward data availability. In your problem space, what’s the data set you’re likely to lean on? Is it sufficient?

If the answer is that the data is not available or notoriously problematic in your market space for the problem you’re solving, this merits a pause. Can you find a way to survive in this reality? Can you create the data set you need? Can you adjust what you’re doing in some way to align with what is available? Is qualitative feedback ok?

Pattern #2: Accumulating Non-Technical Roadblocks Key Question: Do you have a good handle on the non-technical challenges impacting your data business?

A decade ago I would have approached this question differently. Technical challenges were often paramount as we tried to figure out how to solve the basics. Today, however, it’s often the opposite, in that business challenges are more likely to slow down technical progress than the other way around.

Healthcare Data: The Disruption Opportunity + Why This Time Is Different

May 19, 2023• 1

By SHUBHRA JAIN & JAY SANTORO

Knowledge is power. If this adage is true, then the currency of power in the modern world is data. If you look at the evolution of the consumer economy over the past 100 years, you will see a story of data infrastructure adoption, data generation, and then subsequent data monetization. This history is well told by Professors Minna Lami and Mika Pantzar in their paper on ‘The Data Economy’: “Current ‘data citizenship’ is a product of the Internet, social media, and digital devices and the data created in the digitalized life of consumers has become the prime source of economic value formation. The database is the factory of the future.” If we look no further than the so-called big tech companies and distill their business models down in a (likely overly) reductionist fashion: Apple and Microsoft provide infrastructure to get you online, and Facebook (Meta) and Google collect your data, while providing a service you like, and use that data to sell you stuff. Likely none of this is surprising to this audience, but what is surprising is that this playbook has taken so long to run its course in one of the world’s largest and most important sectors: healthcare.

Given the potential impact data access and enablement could have on transforming such a large piece of the economy, the magnitude of the opportunity here is — at face value — fascinating. That said, healthcare is a different beast from many other verticals. Serious questions arise as to whether target venture returns can be extracted in this burgeoning market with the scaled incumbents (both within and outside healthcare) circling the perimeter. Additionally, this is a fragmented ecosystem that has existed (in its infancy) for a few years now with well-funded players now solving for different use cases. Thus, another question emerges as to which areas are best suited for upstarts to capitalize. A key theme in our assessment of the space is that regulation is driving the move towards democratized data access in healthcare, but unlike in regulatory shake-ups of the past, this time start-ups will benefit more than scaled incumbents. Furthermore, we have identified some areas within each approach to this new ecosystem that particularly excite us for net new investment. Let’s dive in.

Why This Time is Different: Regulatory + Market Dynamics

The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 brought about an explosion of digital healthcare data by expanding adoption of electronic medical records from ~12% to 96%.

DNA Storage in a Yottabyte Era

Dec 7, 2021

By KIM BELLARD

Did you know we are living in the Zettabyte Era? Honestly, did you even know what a zettabyte is? Kilobytes, gigabytes, maybe even terabytes, sure, but zettabytes? Well, if you ran data centers you’d know, and you’d care because demand for data storage is skyrocketing (all those TikTok videos and Netflix shows add up). Believe it or not, pretty much all of that data is still stored on magnetic tapes, which have served us well for the past sixty some years but at some point, there won’t be enough tapes or enough places to store them to keep up with the data storage needs.

That’s why people are so keen on DNA storage – including me.

A zettabyte, for the record, is one sextillion bytes. A kilobyte is 1000 bytes; a zettabyte is 1000⁷. Between gigabytes and zettabytes, by powers of 1000, come terabytes, petabytes, and exabytes; after zettabyte comes yottabytes. Back in 2016, Cisco announced we were in the Zettabyte Era, with global internet traffic reaching 1.2 zettabytes. We’ll be in the Yottabyte Era before the decade is out.

Announcing The COVID-19 Symptom Data Challenge

Sep 1, 2020

By FARZAD MOSTASHARI

In Partnership with the Duke-Margolis Center for Health Policy, Resolve to Save Lives, Carnegie Mellon University, and University of Maryland, Catalyst @ Health 2.0 is excited to announce the launch of The COVID-19 Symptom Data Challenge. The COVID-19 Symptom Data Challenge is looking for novel analytic approaches that use COVID-19 Symptom Survey data to enable earlier detection and improved situational awareness of the outbreak by public health and the public.

How the Challenge Works:

In Phase I, innovators submit a white paper (“digital poster”) summarizing the approach, methods, analysis, findings, relevant figures and graphs of their analytic approach using Symptom Survey public data (see challenge submission criteria for more). Judges will evaluate the entries based on Validity, Scientific Rigor, Impact, and User Experience and award five semi-finalists $5,000 each. Semi-finalists will present their analytic approaches to a judging panel and three semi-finalists will be selected to advance to Phase II. The semi-finalists will develop a prototype (simulation or visualization) using their analytic approach and present their prototype at a virtual unveiling event. Judges will select a grand prize winner and the runner up (2nd place). The grand prize winner will be awarded $50,000 and the runner up will be awarded $25,000.The winning analytic design will be featured on the Facebook Data For Good website and the winning team will have the opportunity to participate in a discussion forum with representatives from public health agencies.

Phase I applications for the challenge are due Tuesday, September 29th, 2020 11:59:59 PM ET.

Learn more about the COVID-19 Symptom Data Challenge HERE.

Challenge participants will leverage aggregated data from the COVID-19 symptom surveys conducted by Carnegie Mellon University and the University of Maryland, in partnership with Facebook Data for Good. Approaches can integrate publicly available anonymized datasets to validate and extend predictive utility of symptom data and should assess the impact of the integration of symptom data on identifying inflection points in state, local, or regional COVID outbreaks as well guiding individual and policy decision-making.

These are the largest and most detailed surveys ever conducted during a public health emergency, with over 25M responses recorded to date, across 200+ countries and territories and 55+ languages. Challenge partners look forward to seeing participant’s proposed approaches leveraging this data, as well as welcome feedback on the data’s usefulness in modeling efforts.

Indu Subaiya, co-founder of Catalyst @ Health 2.0 (“Catalyst”) met with Farzad Mostashari, Challenge Chair, to discuss the launch of the COVID-19 Symptom Data Challenge. Indu and Farzad walked through the movement around open data as it relates to the COVID-19 pandemic, as well as the challenge goals, partners, evaluation criteria, and prizes.

Healthcare in the National Privacy Law Debate

Feb 10, 2020• 3

This article originally appeared in the American Bar Association’s Health eSource here.

By KIRK NAHRA

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.

Congress is debating whether to enact a national privacy law. Such a law would upend the approach that has been taken so far in connection with privacy law in the United States, which has either been sector specific (healthcare, financial services, education) or has addressed specific practices (telemarketing, email marketing, data gathering from children). The United States does not, today, have a national privacy law. Pressure from the European Union’s General Data Protection Regulation (GDPR)¹ and from California, through the California Consumer Privacy Act (CCPA),² are driving some of this national debate.

The conventional wisdom is that, while the United States is moving towards this legislation, there is still a long way to go. Part of this debate is a significant disagreement about many of the core provisions of what would go into this law, including (but clearly not limited to) how to treat healthcare — either as a category of data or as an industry.

So far, healthcare data may not be getting enough attention in the debate, driven (in part) by the sense of many that healthcare privacy already has been addressed. Due to the odd legislative history of the Health Insurance Portability and Accountability Act of 1996 (HIPAA),³ however, we are seeing the implications of a law that (1) was driven by considerations not involving privacy and security, and (2) reflected a concept of an industry that no longer reflects how the healthcare system works today. Accordingly, there is a growing volume of “non-HIPAA health data,” across enormous segments of the economy, and the challenge of figuring out how to address concerns about this data in a system where there is no specific regulation of this data today.

Pressed to Demonstrate Utility, Digital Health Struggles — Just Like Traditional Medicine

Dec 1, 2019

By DAVID SHAYWITZ, MD

After absorbing several years of increasingly extravagant promises about the remarkable potential of digital health, investors, physicians, and other stakeholders are now unabashedly demanding: “Show me the data.”

By now, most everyone appreciates the promise of digital health, and understands how, in principle, emerging, patient-focused technologies could help improve care and reduce costs.

The question is whether digital health can actually deliver.

A recent NIH workshop, convened to systematically review the data on digital health, acknowledged, “evidence is sparse for the efficacy of mHealth.”

As Scripps cardiologist Eric Topol and colleagues summarized in JAMA late last year,

“Most critically needed is real-world clinical trial evidence to provide a roadmap for implementation that confirms its benefits to consumers, clinicians, and payers alike.”

What everyone’s asking for now is evidence – robust data, not like the vast majority of wellness studies that experts like Al Lewis and others have definitively shredded.

The goal is to find solid evidence that a proposed innovation actually leads to measurably improved outcomes, or to a material reduction in cost. Not that it could or should, but that it does.
Continue reading…

Who Owns Patient Data?

Nov 1, 2018

By Fred Trotter

Who owns a patient’s health information?

The patient to whom it refers?
The health provider that created it?
The IT specialist who has the greatest control over it?

The notion of ownership is inadequate for health information. For instance, no one has an absolute right to destroy health information. But we all understand what it means to own an automobile: You can drive the car you own into a tree or into the ocean if you want to. No one has the legal right to do things like that to a “master copy” of health information.

All of the groups above have a complex series of rights and responsibilities relating to health information that should never be trivialized into ownership.

Raising the question of ownership at all is a hash argument. What is a hash argument? Here’s how Julian Sanchez describes it:

“Come to think of it, there’s a certain class of rhetoric I’m going to call the ‘one-way hash‘ argument. Most modern cryptographic systems in wide use are based on a certain mathematical asymmetry: You can multiply a couple of large prime numbers much (much, much, much, much) more quickly than you can factor the product back into primes. A one-way hash is a kind of ‘fingerprint’ for messages based on the same mathematical idea: It’s really easy to run the algorithm in one direction, but much harder and more time consuming to undo. Certain bad arguments work the same way — skim online debates between biologists and earnest ID (Intelligent Design) aficionados armed with talking points if you want a few examples: The talking point on one side is just complex enough that it’s both intelligible — even somewhat intuitive — to the layman and sounds as though it might qualify as some kind of insight … The rebuttal, by contrast, may require explaining a whole series of preliminary concepts before it’s really possible to explain why the talking point is wrong.”

Life-Saving Data That Is Nowhere To Be Found: Hospitals’ C-section Rates

Oct 31, 2018• 10

By DANI BRADLEY MS, MPH

The United States is the only developed nation in the world with a steadily increasing maternal mortality rate — and C-sections are to blame. Nearly 32% of babies are born via C-section in the United States, a rate of double or almost triple what the World Health Organization recommends. While C-sections are an incredibly important life-saving intervention when vaginal delivery is too dangerous, they are not devoid of risks for mom or for baby. Hospitals and doctors alike are aware, as it’s been widely reported that unnecessary C-sections are dangerous — and hospitals and doctors agree that the number one way to reduce this risk is to choose a delivery hospital with low a C-section rate. However, information on hospitals’ C-section rates is incredibly hard to find, which leaves women in the dark as they try to make this important choice.

In an effort to help women make informed decisions about where to deliver their babies, we set out to collect a comprehensive, nationwide database of hospitals’ C-section rates. Knowing that the federal government mandates surveillance and reporting of vital statistics through the National Vital Statistics System, we contacted all 50 states’ (+Washington D.C.) Departments of Public Health (DPH) asking for access to de-identified birth data from all of their hospitals. What we learned might not surprise you — the lack of transparency in the United States healthcare system extends to quality information, and specifically C-section data.
Continue reading…

It’s The Platform, Stupid: Capturing the Value of Data in Campaigns — and Healthcare

Oct 1, 2018

By David Shaywitz, MD

If you’ve yet not discovered Alexis Madrigal’s fascinating Atlantic article (#longread), describing “how a dream team of engineers from Facebook, Twitter, and Google built the software that drove Barack Obama’s re-election,” stop right now and read it.

In essence, a team of technologists developed for the Obama campaign a robust, in-house platform that integrated a range of capabilities that seamlessly connected analytics, outreach, recruitment, and fundraising. While difficult to construct, the platform ultimately delivered, enabling a degree of logistical support that Romney’s campaign reportedly was never able to achieve.

It’s an incredible story, and arguably one with significant implications for digital health.

(1) To Leverage The Power of Data, Interoperability Is Essential

Data are useful only to the extent you can access, analyze, and share them. It increasingly appears that the genius of the Obama campaign’s technology effort wasn’t just the specific data tools that permitted microtargeting of constituents, or evaluated voter solicitation messages, or enabled the cost-effective purchasing of advertising time. Rather, success flowed from the design attributes of the platform itself, a platform built around the need for inoperability, and guided by an integrated strategic vision.

Grassley Criticizes Removal of Doctor Discipline Data

Sep 1, 2018

By PIA CHRISTENSEN

U.S. Sen. Charles Grassley (R-Iowa) sent a letter today to the Health Resources and Services Administration, criticizing its decision to remove a public version of the National Practitioner Data Bank, which has helped reporters and researchers to expose serious gaps in the oversight of physicians.

“Shutting down public access to the data bank undermines the critical mission of identifying inefficiencies within our health care system – particularly at the expense of Medicare and Medicaid beneficiaries,” Grassley wrote to HRSA Administrator Mary Wakefield. “More transparency serves the public interest.”

Grassley, ranking Republican on the Senate Judiciary Committee, continued: “Generally speaking, except in cases of national security, the public’s business ought to be public. Providers receive billions of dollars in state and federal tax dollars to serve Medicare and Medicaid beneficiaries. Accountability requires tracking how the money is spent.”