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The New Rules of Healthcare Platforms: APIs Enable the Platforming of Healthcare

BY VINCE KURATIS, BRENDAN KEELER, and JODY RANCK

Recent regulations have mandated the use of HL7 FHIR APIs (application programming interfaces) to share health data. The regs apply to healthcare providers, payers, and technology developers who participate in federal programs. Many incumbent healthcare organizations are viewing these mandates as a compliance burden. That’s short-sighted. We recommend a more opportunistic POV.

APIs facilitate the sharing of health data across different devices and platforms. By adopting APIs, healthcare organizations can transform themselves from traditional service providers into powerful platforms that can connect patients, providers, and other stakeholders in new and innovative ways.

This blog post is the fourth in the series on The New Rules of Healthcare Platforms. In this essay, we explore the many benefits of API adoption for healthcare organizations and the key considerations that must be taken into account when implementing APIs:

  • Healthcare’s Data Inflection Point
  • APIs Enable Platform Business Models
  • Barriers, Challenges, Reality Check

Healthcare’s Data Inflection Point

Compared to other industries, healthcare generates a disproportionately large amount of data. According to RBC Capital Markets, “30% of the world’s data volume is being generated by the healthcare industry. By 2025, the compound annual growth rate of data for healthcare will reach 36%. That’s 6% faster than manufacturing, 10% faster than financial services, and 11% faster than media & entertainment.”

Over the past 15 years, new regulations have driven digitization, data interoperability, and data sharing. The goal of regulations has been to liberate patient data that has previously been unstructured and trapped in patient silos. Venture capitalist Kahini Shah summarized these regulatory efforts in her article entitled Healthcare Data APIs – An Upcoming Multi-Billion Dollar Market?:

Recent regulation is forcing digitization, aggregation and transmission of medical records. Congress passed the HITECH Act in 2009, prompting the adoption of electronic health records. Before that medical records were paper based. Healthcare data is incredibly siloed, every American sees an average of 19 providers in their lifetime. Connecting these disparate electronic systems and having them exchange information is called interoperability. In 2020, the HHS and CMS implemented two rules that mandate patient access to their medical records and interoperability. These transformative rules give patients the right to access their data when they need and make it available via APIs. The interoperability rules state that there is no blocking – EHRs must allow data to be shared easily across different systems owned by different vendors.

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Can AI Part The Red Sea?

BY MIKE MAGEE

A few weeks ago New York Times columnist Tom Friedman wrote, “We Are Opening The Lid On Two Giant Pandoras Boxes.” He was referring to 1) artificial Intelligence (AI) which most agree has the potential to go horribly wrong unless carefully regulated, and 2) global warming leading to water mediated flooding, drought, and vast human and planetary destruction.

Friedman argues that we must accept the risk of pursuing one (rapid fire progress in AI) to potentially uncover a solution to the other. But positioning science as savior quite misses the point that it is human behavior (a combination of greed and willful ignorance), rather than lack of scientific acumen, that has placed our planet and her inhabitants at risk.

The short and long term effects of fossil fuels and carbonization of our environment were well understood before Al Gore took “An Inconvenient Truth” on the road in 2006. So were the confounding factors including population growth, urbanization, and surface water degradation. 

When I first published “Healthy Waters,” the global population was 6.5 billion with 49% urban, mostly situated on coastal plains. It is now 8 billion with 57% urban and slated to reach 8.5 billion by 2030 with 63% urban. 552 cities around the globe now contain populations exceeding 1 million citizens.

Under ideal circumstances, this urban migration could serve our human populations with jobs, clean air and water, transportation, housing and education, health care, safety and security. Without investment however, this could be a death trap. 

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What Can We Learn from the Envision Bankruptcy?

By JEFF GOLDSMITH

Envision, a $10 billion physician and ambulatory surgery firm owned by private equity giant Kohlberg Kravis Roberts, filed Chapter 11 bankruptcy on May 15.  It was the largest healthcare bankruptcy in US history.   Envision claimed to employ 25 thousand clinicians- emergency physicians, anesthesiologists, hospitalists, intensivists, and advanced practice nurses and contracted with 780 hospitals.  Envision’s ER physicians delivered 12 million visits in 2021, not quite 10% of the US total hospital ED visits.

The Envision bankruptcy eclipsed by nearly four-fold in current dollars the Allegheny Health Education and Research Foundation (AHERF) bankruptcy in the late 1990’s.   KKR has written off $3.5 billion in equity in Envision.   Envision’s most valuable asset, AmSurg and its 257 ambulatory surgical facilities, was separated from the company with a sustainable debt structure.  And at least $5.6 billion of the remaining Envision debt will be converted to equity at the barrel of a gun, at dimes on the dollar of face value. 

KKR took Envision private in 2018 when Envision generated $1 billion in profit, in luminous retrospect the peak of the company’s good fortune.   Envision’s core business was physician staffing of hospital emergency departments and operating suites.    In 2016, then publicly traded, Envision merged with then publicly traded ambulatory surgical operator AmSurg.  This merger seemed at the time to be a sensible diversification of Envision’s “hospital contractor” business risk.   

Indeed, Envision’s bonus acquisition of anesthesia staffing provider Sheridan, acquired by AMSURG in 2014,  helped broaden its portfolio away from the Medicaid intensive core emergency room staffing business (EmCare), which required extensive cost-shifting (and out of network billing) to cover losses from treating Medicaid and uninsured patients.   It is clear from hindsight that where you start, e.g. your core business, limits your capacity to spread or effectively manage your business risk, an issue to which we will return.

The COVID hospital cataclysm can certainly be seen as a proximate cause of Envision’s demise.

The interruptions of elective care and the flooding of emergency departments with elderly COVID patients, which kept non-COVID emergencies away, damaged Envision’s core business as well as nuking ambulatory surgery. By the spring of 2020, Envision was exploring a bankruptcy filing.  An estimated $275 million in CARES Act relief and draining a $300 million emergency credit line from troubled European banker Credit Suisse temporarily staunched the bleeding.  But the pan-healthcare post-COVID labor cost surge also raised nursing expenses and led to selective further shutdowns in elective care and further cash flow challenges.  

While one cannot fault KKR’s due diligence team for missing a global infectious disease pandemic, with hindsight’s radiant clarity, there were other issues simmering on the back burner by the time of the 2018 deal that should have raised concerns.  Two large struggling investor owned hospital chains,  Tenet and Community Health Systems, began divesting marginal properties in earnest in 2018, placing a lot of Envision’s contracts in the pivotal states of Florida and Texas at risk.

More importantly,  there were escalating contract issues with  UnitedHealth, one of Envision’s biggest payers,  as well as increasing political agitation about out-of-network billing, which provided Envision vital incremental cash flow.  These problems culminated in a United decision in January 2021 to terminate insurance coverage with Envision, making its entire vast physician group “out of network”. 

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AI is Bright, But Can Also Be Dark

BY KIM BELLARD

If you’ve been following artificial intelligence (AI) lately – and you should be – then you may have started thinking about how it’s going to change the world. In terms of its potential impact on society, it’s been compared to the introduction of the Internet, the invention of the printing press, even the first use of the wheel. Maybe you’ve played with it, maybe you know enough to worry about what it might mean for your job, but one thing you shouldn’t ignore: like any technology, it can be used for both good and bad.  

If you thought cyberattacks/cybercrimes were bad when done by humans or simple bots, just wait to see what AI can do.  And, as Ryan Health wrote in Axios, “AI can also weaponize modern medicine against the same people it sets out to cure.”

We may need DarkBERT, and the Dark Web, to help protect us.

A new study showed how AI can create much more effective, cheaper spear phishing campaigns, and the author notes that the campaigns can also use “convincing voice clones of individuals.”  He notes: “By engaging in natural language dialog with targets, AI agents can lull victims into a false sense of trust and familiarity prior to launching attacks.”  

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SPM-Creative Learning Exchange, Portland, OR (& virtual), July 16

As you may know I am on the board of the Society for Participatory Medicine (SPM) which is trying to promote a new partnership between patients and the health care system.

On June 16 at 8am-1pm PST SPM is hosting a Creative Learning Exchange in Portland, OR at OHSU. The topic is Advancing Health Equity Through Participatory Medicine and there’ll be patients, clinicians and other leading crucial discussions about how to move health equity forward.

If you are in Portland please come join the meeting and if you can’t get there, it will be broadcast online. (There’s a nominal cost for tickets but no one will be turned away if they can’t afford it) Click here to find out more.–Matthew Holt

Asking Bard And ChatGPT To Find The Best Medical Care, I Got Truth And Truthiness

BY MICHAEL MILLENSON

If you ask ChatGPT how many procedures a certain surgeon does or a specific hospital’s infection rate, the OpenAI and Microsoft chatbot inevitably replies with some version of, “I don’t do that.”

But depending upon how you ask, Google’s Bard provides a very different response, even recommending a “consultation” with particular clinicians.

Bard told me how many knee replacement surgeries were performed by major Chicago hospitals in 2021, their infection rates and the national average. It even told me which Chicago surgeon does the most knee surgeries and his infection rate. When I asked about heart bypass surgery, Bard provided both the mortality rate for some local hospitals and the national average for comparison. While sometimes Bard cited itself as the information source, beginning its response with, “According to my knowledge,” other times it referenced well-known and respected organizations.

There was just one problem. As Google itself warns, “Bard is experimental…so double-check information in Bard’s responses.” When I followed that advice, truth began to blend indistinguishably with “truthiness” – comedian Stephen Colbert’s memorable term to describe information that’s seen as true not because of supporting facts, but because it “feels” true.

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

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%.

Screenshot of Epic EMR (Demo)
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The Disease Killing Healthcare and Causing Physician Burnout

BY SCOTT MACDIARMID

We have a healthcare crisis . . . and the crisis is now. Costs are soaring out of control, threatening the financial health of individuals and our nation. Quality of care is deteriorating, in spite of “world class care” signs seemingly on every corner. And physicians are checking out and burning out. I believe it’s one of the greatest societal issues of our day.

So, you may be wondering: How in the heck did we get ourselves into such a mess? In the greatest country in the world who spends the most on healthcare and is regularly bragging on how great it is, what happened? 

Experts and pundits alike tout a litany of reasons. Increasing life expectancy, our reliance on sophisticated and expensive diagnostic tests and treatments, the costs of big pharma, duplication of care, fraud and abuse—the list goes on. Although these are all important contributors, none of them points to the underlying disease that’s killing healthcare.

The healthcare system in some respects is like the human body. It has seven systems, and the health and survival of each is largely dependent on the health of the others, much like the inter-dependent relationship of the organs of the human body. For example, if your liver or kidneys fail, your body’s health is severely impacted, even if your heart and lungs are functioning normally. 

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Healthcare: Make Better Mistakes

BY KIM BELLARD

I saw an expression the other day that I quite liked. I’m not sure who first said it, and there are several versions of it, but it goes something like this: let’s make better mistakes tomorrow.

Boy howdy, if that’s not the perfect motto for healthcare, I don’t know what is.

Health is a tricky business.  It’s a delicate balancing act between – to name a few — your genes, your environment, your habits, your nutrition, your stress, the health and composition of your microbiome, the impact of whatever new microbes are floating around, and, yes, the health care you happen to receive. 

Health care is also a tricky business. We’ve made much progress in medicine, developed deeper insights into how our bodies work (or fail), and have a multitude of treatment options for a multitude of health problems. But there’s a lot we still don’t know, there’s a lot we know but aren’t actually using, and there’s an awful lot we still don’t know. 

It’s very much a human activity. Different people experience and/or report the same condition differently, and respond to the same treatments differently. Everyone has unique comorbidities, the impact of which upon treatments is still little understood. And, of course, until/unless AI takes over, the people responsible for diagnosing, treating, and caring for patients are very much human, each with their own backgrounds, training, preferences, intelligence, and memory – any of which can impact their actions. 

All of which is to say: mistakes are made. Every day. By everyone. 

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