The Elizabeth Holmes Trial Is an Indictment of US Health Care

What might have happened if taxpayers—rather than investors—had directly funded Theranos’s blood-prick research?

This piece originally appeared in The Nation on December 22, 2021 and has since been updated to reflect developments in the case.

It’s understandable why millions of people would like to see Elizabeth Holmes’s head on a pike.

She has become, conveniently if involuntarily, the poster child for a wide variety of sins: the excesses of Silicon Valley, commonplace corporate lies, a thorough lack of executive accountability. The jury just found the Theranos founder guilty on four of the 11 charges, including multiple counts of wire fraud (that quaintly named crime, suggesting that American statutes have not caught up to the 21st century). Holmes, at one point the world’s youngest self-made female billionaire, could go to prison for 20 years or more, having defrauded the investors who put a billion dollars or so into her company.

The trial and the Theranos saga have been an object lesson on what is wrong with health care and American capitalism.

It’s impossible to fault Holmes or Theranos for trying to produce a quick, pinprick blood test that would make so much of the world’s health care delivery easier, faster, and putatively cheaper. True, some or perhaps most of Theranos’s champions may have had less-than-pure motivations; John Carreyou’s vital book Bad Blood depicts Walgreens executives, for example, as conspicuously incurious observers of Theranos’s technology, lest there be any obstacle on the path to the cash register. In 2010, the Walgreens CFO visited Theranos’s Palo Alto headquarters and was, according to Carreyou, unfazed by lack of access to the laboratory, happy instead to accept an autographed American flag that Holmes said had flown over an Afghanistan battlefield.

Still, we want entrepreneurs to swing for the fences, don’t we? If venture capital and other investors are going to pump their billions into start-ups, it’s better that they support health care innovation than, say, Juicero, the VC-backed $400 kitchen device for squeezing fruit that quickly went the way of all peels and rinds.

Virtue of purpose is, of course, no excuse for fraud. Theranos, depending on your perspective, committed fraud for many years, almost immediately from its 2003 launch. Holmes’s intensity and gender-pioneer status bamboozled not only investors but a small army of journalists. I was among them: As the editor of Inc. magazine, I put Holmes on our October 2015 cover. (I’ll still defend the story, but regret calling Holmes “the next Steve Jobs” on the cover, not that Jobs was a CEO without flaws.)

More surprising and disturbing than the seduction of journalists is that Theranos’s top-tier investors didn’t smell something unpleasant years ago. This has been an essential discovery during Holmes’ trial; Bloomberg reported: “Theranos forecast revenue of $140 million in 2014, and almost $1 billion for 2015. Holmes’s top financial officer testified that Theranos posted just $150,000 in revenue in 2014. Evidence at trial shows it was even less in 2015.” This kind of shortfall should have triggered nuclear alerts, from major investors and board members; the lack of public flares vividly illustrates the cynical corruption of America’s financial leadership.

But the broader indictment should be of the for-profit health care system that made Theranos attractive in the first place. One of the trial’s most telling threads involved Theranos not disclosing basic information to Walgreens because it was trying to protect trade secrets.

Whether it’s quick blood tests or mRNA Covid vaccines, health care technology is an obvious public good, and the Theranos debacle—regardless if Holmes is convicted or acquitted—shows the predictable perils of entrusting those technologies to a patent-enabled private sector. The public sector is hardly immune to missteps or corruption, but a blood-test technology under the supervision of the government would not have needed to fake revenue results, and would likely not have produced fraud on a Holmesian scale.

That juxtaposition is especially ironic because, as the flag-over-Afghanistan anecdote reminds us, Theranos was in a critical sense a creature of the military-industrial complex. The US military was highly interested in Theranos’s technology, because it believed that this technology could be supremely useful in a battlefield setting. One of Theranos’s board members was former secretary of state George Shultz (in a wonderfully Oedipal twist, his grandson Tyler, briefly a Theranos employee, was a major source for the Wall Street Journal series that destroyed Theranos and ushered in the federal indictment).

I can’t help wondering: If Theranos had been indirectly working on behalf of a taxpayer-funded military, what would have happened if taxpayers had directly funded the blood-prick research? Might we have achieved the science without the fraud? It seems like a useful experiment.

James Ledbetter is the publisher of FIN and chief content officer of Clarim Media.

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Navigating Platforms and Technologies for a New Healthcare Era

Here’s what payers and providers should look for as they update their core platform strategies for the new normal in healthcare.

Here’s what payers and providers should look for as they update their core platform strategies for the new normal in healthcare.

As discussed in our previous article, many healthcare organizations we work with have set their sights on delivering holistic, frictionless customer journeys that span the boundaries between payers and providers and seamlessly blend physical and digital experiences. This vision stands in stark contrast to the disjointed, fragmented and inefficient processes that characterize today’s healthcare industry.

Before they can seize that grail, however, many healthcare organizations must first modernize, rationalize and reimagine their current core platforms and technologies. Historically, healthcare technology platforms have been optimized for an ecosystem formed in an era of proprietary data silos and adversarial market segments. Closed architectures required extensive custom code and manual workarounds to interact with external systems and devices.

These technology foundations can’t support many of the healthcare industry’s emerging attributes, including interoperable data sets across payer and provider settings, price transparency for medical services, on-demand and healthcare-anywhere care delivery models, and real-time transaction processing – to name just a few.

Put bluntly, the last-gen technology that many providers and payers currently rely on simply won’t support the demands of the new healthcare industry, and will be unable to provide a competitive advantage in the new normal.

An industry in motion

Recognizing this, some large healthcare industry players are reevaluating their technology strategies. We’re noticing an increase in market noise and hype as multiple industry stakeholders position themselves to create market value in the emerging interoperable, price-transparent healthcare economy. Some of the moves we’re seeing include:

  • Leading electronic medical record (EMR) vendors (most notably Epic but also others to varying degrees) are looking to expand beyond health system and hospital boundaries by actively diversifying into the health plan space. These vendors are investing in platforms and products that support traditional payer functionality (claims, membership, premium billing, etc.). Their belief is that an integrated, monolithic, end-to-end platform that spans payer and provider functions will drive value in a converging marketplace.

  • Many large national health plans have been moving into the platform and tech space for a while now, including UnitedHealth Group/Optum, CVS/Aetna, Anthem and others. These diversification strategies have historically included acquiring or monetizing and commercializing proprietary health plan assets (including platforms) and selling them to other health plans. 

    We expect that several of these companies will look to build out and commercialize next-generation healthcare core technology themselves, often in partnership with EMR vendors, to drive value by enabling seamless end-to-end experiences powered by shared data assets.

  • New entrants and Big Tech such as Walmart HealthAmazon Care, Microsoft and Google are investing billions of dollars into introducing new business, operating and technology models to the industry. All of these efforts will have a potentially significant impact on the evolution of core platforms in healthcare and the viability of legacy strategies.

Choosing a technology platform

We’re helping clients separate the hype from the substance of these emerging strategies by working through these key questions:

  • Will you be locked in? We’re hearing from healthcare C-suites who are initially enamored by the idea of buying a single, integrated, end-to-end solution from one vendor. While we understand the apparent appeal of this approach, in reality it can be a rigid and expensive option. The “monolithic” approach puts your company at the mercy of one vendor’s ability to deliver all required capabilities, and makes it more difficult to assemble best-of-breed solutions on open platforms.
  • How fast can you innovate? Organizations locked into a single vendor’s solution will be only as responsive to market and regulatory change as their vendor is. By contrast, those powered with open core technology will be able to vet and integrate new apps, devices and solutions as fast as the marketplace develops them.
  • How comfortable are you with a competitor powering your business? The large national health insurance carriers that have launched platform and technology operations still maintain their core insurance businesses. Our clients express concern about ensuring the companies/vendors they rely on to provide new platform and technology services are separate from the companies they compete with on their core businesses of health insurance and care delivery.

Evaluating open core technology

Many of our clients want to modernize while still getting value from their existing technology investments, data stores and experience and knowledge. That flexibility is possible with core technology that has an intelligence layer that can absorb, integrate, orchestrate and act upon data across the ecosystem. By using core environments with open, standards-based APIs, business logic and workflows, organizations can assemble best-of-breed applications and tools to create experiences specific to their member and population health needs.

Other key qualities to look for in next-gen core technology include:

  • Real-time functionality. Core technology must have real-time change capabilities fed by insights and recommendations from inside and outside the system. Both internal audiences and members/patients should have access to insights for decision-making, from comparing prices to assessing quality ratings of providers for a specific procedure.

  • Support for next-generation payment models. Core technology must enable outcomes-based benefit and contract designs, bundled services, reference pricing, provider incentives and real-time adjudication and payment. As data barriers fall, systems increasingly will need to fully integrate claims and medical data with specialty, pharmacy and non-medical health services.

  • Event-driven insights and automation. When core systems incorporate engines that publish data generated from EMR, claims and other processes in real time, that data can be made available throughout the organization’s application ecosystem. Using artificial intelligence, organizations can then make key processes predictive and automated, such as a machine learning-based review of rejected claims that then approves claims that meet a specific threshold.

Healthcare organizations’ core technology strategies go beyond one company’s balance sheet. They will influence how effectively the industry shifts to value-based models that promise improved outcomes and frictionless experiences at lower costs. Today’s interoperability regulations enable industry players to converge their data sets and use analytics to identify care gaps and social determinants of health. But friction points and outright obstacles among payers and providers with obsolete core systems still inhibit realization of these benefits.

Those that embrace open core technologies will be well positioned to tap the power of the emerging health ecosystem and its fluid data flows to deliver the end-to-end health experience consumers want. Organizations that lock in with one vendor may perpetuate these barriers, ultimately hurting their ability to compete.

William “Bill” Shea is a Vice-President within Cognizant Consulting’s Healthcare Practice. Patricia (Trish) Birch is Senior Vice-President & Global Practice Leader, Healthcare Consulting, at Cognizant.

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As Medical Science Accelerates, Remote Clinical Trials Will Triumph

Clinical trials continue to evolve as new technologies allow researchers to manage them without participants coming to a physical location. Despite hurdles, remote trials are likely to become standard practice.

Clinical trials, a crucial phase of drug development, continue to evolve as new technologies allow researchers to manage them without participants coming to a physical location. Historically, they had to go somewhere to get medications and report results. Now reporting is done online and drugs are delivered by mail, in what are called decentralized trials (DCTs). The trend began before the Covid-19 pandemic, but it has significantly increased drug companies’ need to use this approach.

The very first DCT was done by Pfizer in 2011. It was known as the REMOTE (Research on Electronic Monitoring of Overactive Bladder Treatment Experience) trial, part of a so-called Investigational New Drug Application with the FDA.

“The scientists managing the study recruited participants on the Internet, relied on online questionnaires and electronic diaries, and delivered the drug under investigation directly to participants’ homes,” says Rob Goodwin, vice president and head of operations for global product development at Pfizer. Recruiting participants was a challenge. “It wasn’t easy to bring patients in through the Web,” continues Goodwin. “Not having a central study site presented a logistical challenge. But we learned a lot. It was a springboard for several other trials, and it set us up well for the pandemic.”

A few years later the FDA officially called for “new strategies to modernize clinical trials to advance precision medicine, patient protections, and more efficient product development.” In a 2019 statement, then-FDA chairman Scott Gottlieb said that critical medical innovations could be delayed or completely lost because the cost of testing had gotten so high. He said the U.S. needed  “a more agile clinical research enterprise capable of testing more therapies or combinations of therapies against an expanding array of targets more efficiently and at a lower total cost..”

Traditionally, drug trials have been performed by clinicians or researchers affiliated with an academic medical center or hospital. Participants come to the facility, where drugs are dispensed, vital signs measured, and tests carried out. Such trials remain the gold standard, says Yosef Khan, principal for clinical trials and real-world evidence at Premier, a healthcare improvement company, and remain necessary for products such as surgical and medical devices. But in many cases they drain sponsor resources and impose a burden on participants, many of whom might not live nearby and/or face transportation and time challenges.

Three factors, says Khan, have led DCTs to evolve during the past 20 years. The first is frustration on the part of clinical researchers about the length of trials and the resulting attrition among participants. Then there is the rapid growth of technologies that allow researchers to conduct remote trials or access clinical registries, which are vast databases containing real-world data about medical conditions and how doctors are treating them. Finally, the government has given a push. The federal 21st Century Cures Act was passed in 2016 to accelerate the “discovery, development and delivery” of medical therapies. It encouraged biomedical research investment and facilitated more rapid innovation in review and approval processes, among other things. Khan says additional regulation remains necessary to ensure that the data collected in DCTs going forward is accurate and reliable.

Decentralized trials offer a range of benefits, including reducing the needed size of research teams and lowering costs for drug companies. More participants may be attracted to trials that eliminate worries about travel and time demands. And perhaps most importantly, because physical boundaries disappear online, researchers can broaden their participant pool to more accurately include people of diverse ethnicities, genders, and ages.

This addresses real problems with how medical science has proceeded until now. “Studies show persistent minority underrepresentation in clinical trials, even for conditions that affect them disproportionately,” reports the Journal of the American Medical Association. “Black people accounted for only four percent of 300,000 participants in trials of cardiovascular and diabetes medications approved by the FDA from 2008 to 2017, and Hispanic individuals accounted for 11 percent.” (Black Americans represent about 12.8% of the population, and Latinos 18%.) Recruiting minority participants for Covid-19 vaccine efforts in the past two years has been a challenge, according to some researchers. Improving the diversity of trials is critical, says Khan: “If I have only white men in the trial, can I really say the drug will work for all demographics?”

“There is great hope that DCTs will increase diversity, bring in unmet populations, and increase retention,” says Pfizer’s Goodwin. “I would say it’s too early to determine whether these efforts are panning out…You’re trying to create the best experience for the patient, but some populations have concerns and simply won’t join a trial. The challenges aren’t simply related to technology. We must continually focus on making patients comfortable.”

Despite the clear benefits DCTs offer—including, says Khan, the ability for small biotech startups to more easily carry out clinical trials—they come with challenges. Sending drugs to individuals by mail can be complex and even pose a risk if shipments are lost or compromised. Wearable biometric devices, often required for modern trials, are still relatively finicky, and troubleshooting them remotely can be difficult. There are also privacy concerns about online reporting, though blockchain technology offers some ways to protect personal healthcare data.

“When the pandemic hit, we weren’t new to DCTs, which gave us the ability to move quickly,” says Goodwin. “To develop the coronavirus vaccine, we were able to take advantage of existing technology such as telemedicine, and work with local labs, so patients didn’t have to travel. We used e-diaries and a range of apps that people could download to their mobile devices, though some people chose to use physical diaries to record signs and symptoms. We taught people to swab themselves, and had the swabs picked up at their homes.”

Pfizer doesn’t rely on in-house technology for its DCTs—it partners with third-party companies that handle many aspects of remote trials. Medable, umotif, and snapIoT are among the companies operating in this industry.

Ultimately, says Goodwin, “a hybrid approach is the way of the future.” In such cases, participants might show up in person at the beginning of the study for necessary lab tests and paperwork, and return only if the study required it or if they experience an adverse event.

Despite hurdles, remote trials are likely to become standard practice. “Change is difficult,” says Khan. “But we have to continue accelerating the use of DCTs.”

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The Forces Driving Healthcare to Rethink Its Platform Strategies

Senior healthcare leaders need to understand the drivers of industry change, as well as the technology underpinnings needed to support new value propositions.

The healthcare industry is rapidly being recontoured by the forces of digital innovation, new industry regulations and growing consumer expectations for better healthcare experiences. From our observations, healthcare payers and providers increasingly have both the technology tools and the regulatory incentives to overcome the industry’s traditionally adversarial silos and barriers.

The goal: delivering consumer experiences that seamlessly unify payer and provider functions and physical and digital channels. Soon, care, payment, follow-up, referrals and ancillary services will all be blended into a single, frictionless process that makes traditional boundaries between payers and providers transparent to consumers.

Already, payer-provider convergence is accelerating as interoperability, price transparency and aggressive new entrants with deep pockets erode the industry’s traditional barriers and business models. We’re seeing health plans executing diversification strategies designed to increase alignment and collaboration with providers. Some payers, including United Health Group/Optum and Blue Shield of California, have even bought provider practices.

On the provider side, some — including UPMC and Intermountain Health — have stood up their own health plans, taking on both insurance risk and the financial risk of shifting to more value-based contracts based on improving health outcomes. The race is on to deliver a seamless healthcare experience, and long-term incumbent players and new entrants alike are placing their bets.

To succeed in the emerging healthcare landscape, senior healthcare leaders need to first understand the forces reshaping healthcare and the experiences payers and providers deliver, as well as the impact of these forces on core healthcare technology.

In this article, we’ll look at the drivers of change and what they entail for technology selections, and in an upcoming essay we’ll evaluate emerging core technology strategies and explain the capabilities healthcare organizations need from next-gen technology.

A radical industry makeover

New market forces are driving out longstanding healthcare complexities and costs that historically have stymied innovation by preventing efficient data sharing and market-driven economics. These new developments include:

  • Consumer-empowering regulations. The federal data interoperability rule breaks open data silos and sets standards to enable data flows among entities both inside and outside of healthcare. Similarly, price transparency regulations that reveal contract data and negotiated rates are already influencing payer-provider negotiations. This is inching the industry closer to a market-driven model for pricing medical services.

    Together, these regulations are rendering legacy business models based on proprietary data ownership and opaque pricing strategies obsolete. Consumers stand to gain real control over their health information and the ability to easily comparison-shop on quality and value.

  • Mass “API-ification” of core payer and provider functions. With new advancements in technology — combined with interoperability regulations mandating standards-based application programming interfaces (APIs) — an ecosystem-powered approach is emerging to drive value from platform and technology investments. Standards-based APIs will help providers and payers overcome process gaps and inefficiencies by enabling real-time automated transactions.

    For example, an API could enable a best-of-breed quality management system to exchange data with a core administrative system, resulting in the ability to streamline quality reports and identify care gaps more quickly. APIs also will democratize data and functionality, enabling innovation marketplaces for third-party apps and developers. Imagine an App Store or Play Store specific to healthcare. Apps could range from FDA-vetted clinical functions to medical appointment reminders.

  • New value-based care and payment models. The adoption of new payment models is aligning payer and provider incentives and inspiring new business and care delivery models that are breaking down traditional adversarial silos. This is accelerating payer/provider convergence.

A new platform for a reshaped industry

These forces — and the new industry topology they are creating — are testing the limits of traditional health industry technology platforms and surrounding applications. Traditional technology infrastructures are ill-equipped to support new value propositions based on interoperable data flows, transparent pricing and open ecosystems. 

Consider the friction points that exist at the historically adversarial payer/provider boundary: authorizations, referrals management, claims adjudication, denials management, appeals and grievances, etc. Both sides are heavily invested in a parallel revenue cycle management (RCM) arms race plagued by redundancy, inefficiency and costs.

Converting these friction points into value for consumers and healthcare organizations will require open platforms and an ecosystem approach to technology and automation. These must be built on an intelligence layer that draws on data and insights from combined consumer, payer and provider data sets — and increasingly, from combined payer/provider business models.

An evolution ahead

To support new business models based on payer/provider collaboration and even co-ownership of health systems, the industry’s technology platforms and strategies need to evolve. Yet we see many organizations trying to drive these alignments with outdated platform strategies that are technologically incapable of supporting the data fluidity and consumer-centricity these new business models require. Today’s profound business and operating model shifts require fundamental changes in how business and enabling technologies are architected.

At the same time, healthcare organizations need to resist the market noise and focus on making sensible investments that build on, and drive value from, their existing platform investments and leverage their incumbent advantages. Organizations must take time to understand the next-generation technology capabilities they’ll need.

In Part 2, we’ll dissect emerging solutions for delivering frictionless end-to-end consumer experiences and the characteristics healthcare organizations need from next-gen tech to generate opportunities in a reshaped consumer-focused industry.

 

William “Bill” Shea is a Vice-President within Cognizant Consulting’s Healthcare Practice. Patricia (Trish) Birch is Senior Vice-President & Global Practice Leader, Healthcare Consulting, at Cognizant.

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American Interdependence, Democracy, and Innovation

Will American democracy survive? It’s a sad question many of us are asking these days. It’s also the title of the opening session at our Health+Wealth of America conference on Thursday Dec. 16 in midtown Manhattan.

Will American democracy survive? It’s a sad question many of us are asking these days. It’s also the title of the opening session at our Health+Wealth of America conference on Thursday Dec. 16 in midtown Manhattan. Addressing it will be Don Guttenplan, recently-appointed editor of The Nation. We are duly excited that this will be our return to in-person conferences. Here’s our great program.

It’s not an optimistic time in our country. But we are determined to seek signs of progress and arguments for it. And our speakers are eloquent. Not to mention diverse. We are probing where our country and the world are going, and you have to look at that diamond from many angles. We hope it’s not really a lump of coal. The conference is co-hosted by Techonomy, our CDX digital transformation subsidiary, and Worth Magazine, our corporate cousin inside Clarim Holdings.

Worth has shifted towards a broader definition of “worthiness,” and is launching a new list called the Worthy 100—entrepreneurs changing the world for the better. Jacqueline Novogratz, founder and CEO of Acumen, is one of the world’s most visionary change-agents, and she is on the new list. She will also be on our stage as the closing speaker. Her view is that Americans take too narrow a view of who and where they are, and that needs to change, particularly in a world beset by climate change, global pandemic, and potentially uncontrollable immigration. Her session is entitled “Declaring American Interdependence.”

The morning ends with the very Anthony Scaramucci, on “Why Bitcoin Is Headed to Half a Million.” He’ll surely give us, too, his latest assessment of Trump. Then we’ll have breakouts, lunch, and return to hear activist, author, and politician Zephyr Teachout, who recently announced her candidacy for attorney general of New York State. She’ll be interviewed by brilliant Financial Times columnist Rana Foroohar, about, among other things, why we need to break up big tech.

Markets may be mostly up, but it’s often hard to see progress underway on the big systemic things that matter—equality, global warming, education, health care, and especially the pandemic. One of our speakers who can find that progress is Amanda Leland, the recently appointed executive director of the Environmental Defense Fund. She’ll talk about EDF’s war on methane, its upcoming satellite to find and monitor it, and why even as we fight determinedly against global warming, we must work to help those most vulnerable to it. Then two other top leaders of EDF, Heather McTeer Toney and Dr. Margot Brown, will (in a breakout) explain why EDF is so focused on environmental justice–ensuring disadvantaged communities get a voice in environmental policy and that climate action doesn’t only benefit the rich. Separately, two top leaders in impact investing, one from UBS and one from Toniic, will explain how the way we direct our money can be critical to tackling climate change and social problems generally.

Is the Democratic Party “sleepwalking to catastrophe” asked columnist Ezra Klein recently in a profile of the uncannily-accurate pollster and political analyst David Shor. This expert will tell us why he is deeply worried about the direction of the Democrats. We blend politics with economics, because it’s all connected.

Business leaders will also be there in force. Betterment CEO Sarah Kirshbaum Levy joins Kevin Pleiter, head of the capital markets group at global technology consulting firm Cognizant, to discuss the direction of fintech. How could the dizzying range of entrepreneurial financial innovations work better together?

It’s a time of health care crisis, confusion, and, too often, suffering. Veteran investor, author and pundit Esther Dyson has turned her life towards philanthropy with a big long-term project called Wellville. She’s working to help five less-affluent counties around the U.S. better build systems to keep people healthy, as she’ll tell us. Alberto Casellas, EVP and CEO of Synchrony Health and Wellness, describes how Americans can more affordably pay for health care. Top business strategist Rita McGrath joins healthcare communications veteran Ritesh Patel to examine how innovation is changing the pandemic-era patient experience. Jim McCann, founder and Chairman of 1-800-FLOWERS.com, delves into the emotional lives of Americans in this painful pandemic era, which his company uniquely engages with. He’ll be joined by PTSD expert and psychiatrist Dr. Charles Marmar of NYU Langone.

Health care is a crisis especially for mothers in many parts of America, so Simmone Taitt, CEO of Poppyseed Health, a company focused directly on maternal health, helps us understand how that has to change.

This diamond has multiple facets. Google’s Jesse Haines explains how the search giant is working to enhance job creation and entrepreneurship with its Grow With Google initiative. Valarie McCall, chief of staff for the mayor of Cleveland, joins three other women leaders to dissect why women still have so much difficulty breaking through in male-dominated industries like government, real estate, and insurance. Immediately afterwards, we’ll hear from Anoop Gupta, CEO of startup SeekOut, which a group of Microsoft executives recently started to bring more fairness to hiring and diversity to organizations, using algorithms and better software design.

New School Professor Natalia Petrzela, a historian of American culture, talks about both her upcoming book FIT NATION: How America Embraced Exercise As The Government Abandoned It, as well as her extremely-relevant previous one, entitled Classroom Wars: Language, Sex, and the Making of Modern Political Culture.

There is, of course, much more, especially on climate and innovation. Full list of speakers is here and the agenda is here. And the all-important registration page is here. Vaccinated only, of course. But while the in-person experience will be incredible, you can also join us for free online if necessary.

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The Evolution and Death of the Electronic Medical Record

The EMR we have come to know does a very important thing, but it’s absolutely nothing compared to what they could, should, and maybe will do in the very near future.

This may sound odd coming from someone like me who has long worked in healthcare technology, and especially as the literal co-founder of an EMR company, but in the same way that we saw paper patient records heading toward extinction decades back, the EMR as we know it is beginning to wobble. It’s like an aging boxer in round 13 taking on a younger, faster opponent.

The word EMR is a noun, a static thing. In truth, when we use the term, we far more often have an active idea in our minds, making it more like a verb. And in fact, many paragraphs and entire books are dedicated to describing and understanding what an EMR actually is. The U.S. Government has gotten in on the act, with a corpus of literature, revisions, artifacts, checklists, commentary, and guides – all to define this one thing. 

So I ask you: What is an EMR?

It’s easy to hearken back to the pre-digital era and remember the patient chart, stored in a filing cabinet in our doctor’s office. Its simplicity and the simplicity of that analog era may seem quaint, but it was easy then to define a medical record.  It was one individual doctor’s record of what had been seen and done with their own eyes and hands for a given patient.

The promise of the electronic era was romantic and ambitious – to break down the silos of a world before computers and build a composite, complete picture of the core clinical information about a patient. It would encompass the work of many hands and eyes of all the doctors who touch a patient – untethered from geographical boundaries.

But that’s not what’s happened.  Instead (and unsurprisingly) form has followed function.  EMRs became mechanical turks for the original myopic recordkeeping of the doctors of yesteryear.  Only this time, to pay for their added time and expense, they were way “more so.”  EMRs enabled documentation far more than a doctor’s hand would ever bother to capture (thus making the billing codes a little higher). Anything the hands and eyes of a doctor did to that original paper chart was fully captured in highly compliant and extremely legal bloat-script. And to do that, EMRs included lots of other things we somehow added to their original definition. Like a deranged and perhaps half-blind baker, we threw together a recipe – a pinch of front-end workflow, a dash of software processing, and of course a handful of storage capabilities. We mixed it together haphazardly, and then we required it universally.

I think of today’s EMR as a three-layer cake.  

Layer one: The Workflow. You know the drill: Check-in (“insurance card please”), intake (“Smoker?”, “How many packs?”, “Can you step onto this scale?”), exam (“Cough please”), orders (drugs, labs), check-out (“that’ll be $95 and please take a card to schedule your radiology from the stack in the sliding window”). These are the step-by-step tasks that the EMR software walks staff and providers through in order to produce a consistently-documented and compliant encounter, one that does not lend itself to lawsuits but is as billable as possible. 

Layer two: The Compute. The data captured through those workflows in the first layer is then used to gonkulate new info.  CPT codes are calculated and defended by ICD codes, interview data, and time logs. “Meaningful Use” metrics are calculated and attested to, for quality, of course, and of course also for other payments. Quality scores are gonkulated again as referral forms and automated “consult letters”. Tremendous amounts of compute are funneled single-mindedly to turn the clinical experience into financial outcomes, whether fee-for-service or “value-based” care.

Finally, layer three: The Storage.  Unfortunately, this is not the storage we might want, a longitudinal profile of the patient with relevant aspects updated frequently. Instead, it is the storage of all of the above metrics generated by the compute, geared simply to be ready for audits and questions.  Armed with this storage, providers hope desperately not to be embarrassed when patients come back expecting to be remembered. This has led to many EMR cartoons that feature blind men and elephants, as even the most wizened experts struggle to adequately identify what EMR they are looking at. 

All this has contributed to an enormous explosion of healthcare vertical monopolies (and related price increases) across the country. Many have rationalized that if an  EMR is only to be a “core sample” of the Workflow, Compute, and Storage of one physician’s experience, then the logical thing to do is to move all the physicians a patient sees under the same EMR roof. Such consolidation has created a mirage of “continuity of care”. 

As EMRs have matured and regulators have blanched at the silos created by their original mandates and incentive programs a decade ago, the ecosystem has slowly nudged itself towards sharing. Record sharing (originally mandated by HIPAA) is becoming a norm, with common sharing services like Commonwell yielding a 20% match rate for Epic record queries and a 70% match rate for Athenahealth (the company I founded). It’s increasingly common now, as a doctor looks at their patients, for them to find externally-generated data in a patient’s EMR. Such a record is not machine-readable, allows no alerts to fire on that data, and leads to few algorithmically derived insights.  But it’s a helluva lot more than nothing, even as it’s a helluva a lot less than we deserve.  

My summary is that EMRs are OK as they are today, but absolutely nothing compared to what they could, should, and maybe will be in the very near future.

So what should EMR mean? Let’s go back to those three aspects: Workflow, Compute, and Storage. 

First, we need to liberate that Workflow layer which today means a thousand things.  Most of the workflows are unrelated to moving people through old-school office visits. In old EMR speak, we called this concept “the encounter,” and it was tied tightly and rigidly to care delivered over an exam table or hospital bed. 

The new workflows are different. They are the always-on, often nearly free, constant contacts of the digital health age. Think of such workflows as the “edge computing of care”. K Health and Buoy Health will give you free bot-doctoring that is getting better and better. And a dozen more digital health players will give you weirdly-affordable super-fast online team-based care.

The new explosion of health communication means text threads, care plan alerts, and group messaging, which offer ongoing relationships and community with providers and with patients like you.  These workflows will be more important than office visit workflows going forward. The original workflow engines, so a long part of traditional EMRs, should also be able to write to our records. But so should thousands of additional applications and sources.

All of this demands a totally different workflow engine. What about passive monitoring of exercise, or steps, or glucose levels? There are whole companies yet to be built that are centered on new care modalities that have nothing to do with exam rooms. 

Now let’s relook at Compute.  Sure, we should be able to compute codes and bill them. Why, though, are we stuck with EMR’s Compute being entirely geared towards claims? New age providers are increasingly creating products that don’t fit neatly within the world of the CPT code. Many are asking for a monthly subscription fee from employers and payers.  Then those organizations purchase pieces of their care product that they don’t provide with their own staff, not unlike a general contractor with subcontractors.

New age providers will need to buy care as often as they bill for it. Where is the Compute to direct that spend? Where are the ledgers?  Back in the third party administrator days in California, there were a few rudimentary capitation management apps, but they are ancient and not connected to anything.  Firefly Health, the company where I serve as executive chairman, bills employers for its care but also pays specialists for jumping in on sticky cases, which eliminates the need for a full-on referral.

There is also a whole category of marvelous Compute that will come as we more routinely ingest social-determinants-of-health data, which is super important.  The dominant providers and their fee-for-service (FFS) agreements are technically interested in such things, but cannot make such things core to their systems and processes. There is not enough return to FFS-dependent providers to incentivize their radically reducing fees generated by patients. 

Other Compute could surveil populations for what’s working and what’s not, for the purposes of making real-time trade outs. Again that’s not a thing traditional FFS business models can afford to care about, but will be a major win for all new age, value-based players. As more and more healthcare players are born digitally native, there will be more and more APIs to call to calculate care coordination. For example, can you schedule across all the siloed electronic calendars in medicine today? Looking outside healthcare, Kayak has no problem interacting with all the calendars of airlines worldwide. Such discrepancies point to a dramatic misappropriation of where we currently spend our industry’s Compute.

Finally, Storage.  What should we store? Core samples? Blind man soundings? Of course not. The term EMR should refer to the record and only the record – a complete  operational data store for every American. Meanwhile, digital health companies today are intentionally narrow. Ria Health, for example, makes no bones doing anything other than alcohol treatment. They have no plans to do a middling job at X-rays and colonoscopies and all the other things traditional IDNs seek to cobble together. They plan to do alcohol treatment well and, to do so, they need to get a really complete, comprehensive and continuous view of their subjects.

We should all have an EMR, and it should operate like our LinkedIn profile – when we make a change to it, everyone following us should be able to know right away.  There can be no “Save as PDF” and re-sending to friends and prospects. This is what digital-native companies must have. Such companies have no interest in guarding their evidence of care on a patient. In fact, they know they do a much better job when their understanding of members is complete. In that way, they are natively sharers, for both selfish and inherently good reasons.

In my old EMR life, we talked about the scalability of technology. Today, “extensibility” is just as important. Can a tech-native provider build its own workflows and have them seamlessly co-exist with “rented” ones? Can they do the same with their compute? And of course, as with Spotify, can they dispense with keeping an out-of-date, memory-hogging copy of just their own songs alone and instead get a database of all the songs in the world? We know how to do this shit. In fact, in parts of our lives that we care about much less deeply, we do it all the time. 

Simply put, the EMR we have come to know does a very important thing. But god willing, we will need it less and less. EMRs grew up to do a certain job, at a certain time, in a certain place. They are not wrong or bad, but they are closely related to the rapidly-diminishing office-based, fee-for-service world. As digital health companies move from being cool parlor tricks and gadgetry to the mainstream, let’s hope that “place” moves into the rearview mirror.

 

With upstart EMR provider athenahealth, Jonathan Bush was one of the pioneers of the digital health movement enveloping healthcare today.  He is currently an active investor in numerous young healthcare companies, is CEO of Zus Health and Executive Chairman of Firefly Health.

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Where Will COVID Passports Take Flight?

The vision of a global system with standards for the sharing, storage, and verification of vaccination data has not materialized. But success in places like Singapore could help the world move towards a digitized healthcare future.

Preparing for a recent trip from the United States to my home base in Singapore, I had to document and organize records of my COVID vaccination status and required test results. I spent hours preparing numerous forms stored in separate websites or apps. I also struggled to verify if my pre-departure PCR test at San Francisco airport, issued on a piece of paper that could have easily gotten lost, met the stringent entry requirements of the Singapore government. It wasn’t exactly a nightmare, but it certainly wasn’t fun. It would have been easier if I had been able to use a universal globally-accepted digital Covid “passport.”

As the world emerged from pandemic lockdowns this year, such passports have gained attention as a potential tool for safely reopening economies and borders. The apps, which allow individuals to store their test results or vaccine records on a phone and display them to third parties, showed early promise and sparked buoyant enthusiasm in many tech circles.

But the story of COVID passports is one of only fitful progress.

Early in the pandemic, many of the most high-profile COVID passport projects were designed to help facilitate international travel. Within months of the first major lockdowns, a vibrant and global community of technologists came together to build transnational systems to allow test results and vaccine records to be recognized across borders, enabling a more seamless road to international travel recovery.

NGOs and private sector players soon rose to the challenge. Multilateral partnerships were forged; international forums were held; and pilot programs were launched along key international air travel routes. But to date, the vision of a global system with common standards for the sharing, storage, and verification of health data has not materialized. As my experience underscored, international travel in the COVID era remains cumbersome.

Given the thorny technological, political, and operational challenges to making international COVID passport apps work, one can be forgiven for questioning their feasibility. But with pressure mounting on governments around the world to reopen economies, we are seeing many COVID passport solutions focused on national-level needs. This is certainly true in the Asia Pacific region, where “zero COVID” strategies and the risk-averse pandemic management policies of many governments have led to sustained lockdowns and created an urgent need for safe reopening.

Some countries have done well developing and deploying COVID passports. In Singapore, for example, proof of vaccination has been strictly required for entry to restaurants and other venues for many months. Most Singaporeans can easily demonstrate their vaccine status with a digital health pass embedded in TraceTogether, the national contact tracing app. Having lived here through most of the pandemic, I can personally attest that rollout of the system was practically seamless—vaccine records were automatically imported directly into the app, which was intuitive to use and taken up by most of the population.

Singapore’s success with its domestic COVID passport solution can be attributed, in part, to its digitally-savvy and technocratic governance. The country is also small, making it relatively easy to operate a centrally administered database of vaccine results and test records that can easily be queried by COVID apps. This is one of the reasons that a vibrant ecosystem of COVID passport providers emerged quickly in the country. Few other countries have these same ingredients for success.

Singapore is also a place where strict regulations are the norm, people tend to follow the rules, and trust in government services is relatively high. In many other countries, however, public apathy or antipathy towards COVID passports has been a key obstacle to uptake of COVID passports. In the United States, for example, the MIT Technology Review found in August that seven states had rolled out vaccine certification apps, while 22 states have banned such systems to some degree. On my recent trip to the United States, it was downright trippy to visit cities like Tucson, Arizona where people could barely be convinced to wear masks in crowded indoor settings, much less download an app. Vaccine mandates were nonexistent anyway.

But despite social and political resistance, COVID passport apps are becoming increasingly common around the world. Compared to those designed for international travel, these local systems require less technology to implement and don’t face the interoperability challenges of global solutions. National-level systems are also less likely to be beset by fraud and misuse, since it is easier to query and verify test results or vaccine status within a single nation’s borders than across disparate systems for vaccine approval and lab accreditation.

Still, some countries have seen COVID management hampered by stop-and-go implementation of domestic solutions. Denmark was one of the first to introduce a COVID passport, in April. After 80% of its citizens had been fully vaccinated, it phased out the pass in September, but after a subsequent surge in cases, health experts called for its return. Israel, another early adopter, followed a similar pattern, dropping its Green Pass in June before reinstating it after record infections, a decision that was credited for helping to reduce the spread of COVID once again.

So clearly, in some contexts, COVID passport apps are feasible and helpful for managing the pandemic. But many solutions will almost certainly fail. And what will happen when the pandemic wanes?

The good news is that all such efforts may ultimately have lasting and positive impact. They helped raise awareness and drive investment in the underlying technologies that power COVID passports, which could be useful in other settings where vaccine records or test results are mandatory for accessing facilities, such as the requirement in some countries for surgeons to be vaccinated against hepatitis B virus. They are helping the world move towards an urgently-needed more digitized healthcare future. And they may also come in handy for the next pandemic. It could be right around the corner.

Will Greene is a Singapore-based healthcare writer and strategy professional. He currently serves as Healthcare Engagement Manager for Roche Diagnostics Asia Pacific, where he drives thought leadership for Lab Insights, a data hub and educational content platform for the clinical lab community. All views are his own.

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Join Techonomy, CDX and Worth for Health+Wealth of America NYC

THURSDAY, DECEMBER 16 | AN ALL DAY HYBRID EVENT Techonomy, CDX and Worth host our first full-fledged, fully-vaccinated in-person event! We invite you to join us in midtown Manhattan (or virtually) for the latest installment […]

THURSDAY, DECEMBER 16 | AN ALL DAY HYBRID EVENT

Techonomy, CDX and Worth host our first full-fledged, fully-vaccinated in-person event! We invite you to join us in midtown Manhattan (or virtually) for the latest installment in our Health+Wealth of America series, where we’ll bring together experts on our national mood and politics, the future of business, the pandemic, the state of tech and transformation, the push for equity, healthcare, education, climate responsibility, and more.

At this all-day event near Grand Central Station, we’ll bring together speakers like: EDF’s Amanda Leland, Anthony Scaramucci, health care activist Esther Dyson and Don Guttenplan of The Nation to discuss what is happening with the health and wealth of America, defined broadly.

We are really excited to return to face-to-face – our collective conversation has only grown greater during the past year and a half. We look forward to seeing you there.

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Blood Test Shows Promise for Detecting Cancer Far Earlier

Scientists in Ontario used machine learning techniques to find telltale signs of cancer in blood samples that were collected up to seven years prior to conventional diagnosis.

For people with cancer, early detection can mean the difference between life and death. Detecting cancer in its earliest stages — before it has grown aggressively or spread to lymph nodes or other parts of the body — gives people the best chance of survival. The more advanced the cancer when it’s diagnosed, the lower the odds it can be conquered with surgery or therapies.

While scientists are constantly seeking better treatments for cancer, the real holy grail among oncology researchers has been developing an early-warning system. Routine screenings such as colonoscopies, Pap smears, or mammograms have been highly effective in detecting certain cancers earlier than if people waited until they had noticeable symptoms. But even these tools can’t spot the earliest signs of cancer. Also, they’re not available for every type of cancer.

In the genomics field, scientists have begun focusing on telltale cancer markers found in the blood. For example, tiny DNA fragments known as ctDNA are shed by tumors and circulate in the bloodstream. Many companies and research institutions have now developed tests to detect these fragments from a simple blood draw. They are used primarily to monitor existing cancers — offering important signals about how a tumor is responding to treatment or whether tumors have specific genetic variants that make them good targets for certain therapies — but they can also pick up the presence of cancer in people who have not yet been diagnosed.

Unfortunately, ctDNA fragments generally cannot be used to locate the source of the cancer; since they travel in the bloodstream, they could have originated almost anywhere. But now scientists are exploring another layer of information carried by these DNA fragments. Results from a new study indicate this may be the missing puzzle piece that finally allows for early cancer detection with the ability to map its origin.

In our bodies, DNA is the blueprint that guides everything — from building our organs to sending out a key hormone at a critical moment. But our DNA carries a second layer of code on top of it, known as methylation. This code regulates which parts of our DNA get turned into active marching orders by RNA and proteins at any given time, ensuring that our complex systems get only the information they need when they need it.

At the recent annual meeting of the American Society of Human Genetics, Nicholas Cheng from the Ontario Institute for Cancer Research presented data from a study that aimed to detect cancer by mining methylation data from DNA fragments found in blood samples. He and his team used more than 300 blood samples collected between 2009 and 2017 as part of Canadian Partnership for Tomorrow’s Health Project, a large-scale health project that follows hundreds of thousands of participants over several years.

The team focused on people who were healthy at enrollment but were later diagnosed with breast, prostate, or pancreatic cancer at some point during the study. They used blood samples collected prior to diagnosis — in some cases, many years prior — and applied machine learning tools to look for methylation patterns indicative of cancer. They also analyzed control samples from study participants who never had cancer to ensure that any findings were specific to the development of cancer.

Cheng and his colleagues found that their approach not only identified the presence of cancer, but also pinpointed its source using key methylation signatures. Best of all, the researchers found this worked up to seven years prior to diagnosis by conventional techniques. “Across cancer genomes there [tend] to be genome-wide disruptions in methylation patterns,” Cheng said in his conference presentation. “We’re able to identify discriminatory signatures indicative of cancers.”

Cheng believes that eventually this kind of tool could be validated sufficiently to be used alongside standard screening protocols in clinical practice; it could be useful with cancers for which there are good screening methods as well as cancers for which no screening exists, such as pancreatic cancer. While further study is needed, it’s a remarkably promising step toward earlier detection of cancer.

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