Category Archives: Disruptive Technology

Has U.S. Healthcare reached its Tipping Point?

Posted on by • Posted in Affordability, Cost Management, Dept of Justice (DOJ), Disruption, Disruptive Technology, Federal Trade Commission, Federal Trade Commission (FTC), Health Insurance Industry, Health Policy, Health System, Healthcare Industry, Healthcare Reform, High Drug Prices, Inflation, Innovation, Innovative Care Models, Integrated Delivery System, Meaningful, Price Transparency, Private Equity, Tipping Point, Transformation, Transformational Change • Leave a comment
Has U.S. Healthcare reached its Tipping Point?

Last week was significant for healthcare:

  • Tuesday, the, FTC, and DOJ announced creation of a task force focused on tackling “unfair and illegal pricing” in healthcare. The same day, HHS joined FTC and DOJ regulators in launching an investigation with the DOJ and FTC probing private equity’ investments in healthcare expressing concern these deals may generate profits for corporate investors at the expense of patients’ health, workers’ safety and affordable care.
  • Thursday’s State of the Union address by President Biden (SOTU) and the Republican response by Alabama Senator Katey Britt put the spotlight on women’s reproductive health, drug prices and healthcare affordability.
  • Friday, the Senate passed a $468 billion spending bill (75-22) that had passed in the House Wednesday (339-85) averting a government shutdown. The bill postpones an $8 billion reduction in Medicaid disproportionate share hospital payments for a year, allocates $4.27 billion to federally qualified health centers through the end of the year and rolls back a significant portion of a Medicare physician pay cut that kicked in on Jan. 1. Next, Congress must pass appropriations for HHS and other agencies before the March 22 shutdown.
  • And all week, the cyberattack on Optum’s Change Healthcare discovered February 21 hovered as hospitals, clinics, pharmacies and others scrambled to manage gaps in transaction processing. Notably, the American Hospital Association and others have amplified criticism of UnitedHealth Group’s handling of the disruption, having, bought Change for $13 billion in October, 2022 after a lengthy Department of Justice anti-trust review. This week, UHG indicates partial service of CH support will be restored. Stay tuned.

Just another week for healthcare: Congressional infighting about healthcare spending. Regulator announcements of new rules to stimulate competition and protect consumers in the healthcare market.  Lobbying by leading trade groups to protect funding and disable threats from rivals. And so on.

At the macro level, it’s understandable: healthcare is an attractive market, especially in its services sectors. Since the pandemic, prices for services (i.e. physicians, hospitals et al) have steadily increased and remain elevated despite the pressures of transparency mandates and insurer pushback. By contrast, prices for most products (drugs, disposables, technologies et al) have followed the broader market pricing trends where prices for some escalated fast and then dipped.

While some branded prescription medicines are exceptions, it is health services that have driven the majority of health cost inflation since the pandemic.

UnitedHealth Group’s financial success is illustrative: 

it’s big, high profile and vertically integrated across all major services sectors. In its year end 2023 financial report (January 12, 2024) it reported revenues of $371.6 Billion (up 15% Year-Over-Year), earnings from operations up 14%, cash flows from operations of $29.1 Billion (1.3x Net Income), medical care ratio at 83.2% up from 82% last year, net earnings of $23.86/share and adjusted net earnings of $25.12/share and guidance its 2024 revenues of $400-403 billion. They buy products using their scale and scope leverage to  pay less for services they don’t own less and products needed to support them. It’s a big business in a buyer’s market and that’s unsettling to many.

Big business is not new to healthcare:

it’s been dominant in every sector but of late more a focus of unflattering regulator and media attention. Coupled with growing public discontent about the system’s effectiveness and affordability, it seems it’s near a tipping point.

David Johnson, one of the most thoughtful analysts of the health industry, reminded his readers last week that the current state of affairs in U.S. healthcare is not new citing the January 1970 Fortune cover story “Our Ailing Medical System”

 “American medicine, the pride of the nation for many years, stands now on the brink of chaos. To be sure, our medical practitioners have their great moments of drama and triumph. But much of U.S. medical care, particularly the everyday business of preventing and treating routine illnesses, is inferior in quality, wastefully dispensed, and inequitably financed…

Whether poor or not, most Americans are badly served by the obsolete, overstrained medical system that has grown up around them helter-skelter. … The time has come for radical change.”

Johnson added: “The healthcare industry, however, cannot fight gravity forever. Consumerism, technological advances and pro-market regulatory reforms are so powerful and coming so fast that status-quo healthcare cannot forestall their ascendance. Properly harnessed, these disruptive forces have the collective power necessary for U.S. healthcare to finally achieve the 1970 Fortune magazine goal of delivering “good care to every American with little increase in cost.”

He’s right.

I believe the U.S. health system as we know it has reached its tipping point. The big-name organizations in every sector see it and have nominal contingency plans in place; the smaller players are buying time until the shoe drops. But I am worried.

I am worried the system’s future is in the hands of hyper-partisanship by both parties seeking political advantage in election cycles over meaningful creation of a health system that functions for the greater good.

I am worried that the industry’s aversion to price transparency, meaningful discussion about affordability and consistency in defining quality, safety and value will precipitate short-term gamesmanship for reputational advantage and nullify systemness and interoperability requisite to its transformation.

I am worried that understandably frustrated employers will drop employee health benefits to force the system to needed accountability.

I am worried that the growing armies of under-served and dissatisfied populations will revolt.

I am worried that its workforce is ill-prepared for a future that’s technology-enabled and consumer centric.

I am worried that the industry’s most prominent trade groups are concentrating more on “warfare” against their rivals and less about the long-term future of the system.

I am worried that transformational change is all talk.

It’s time to start an adult conversation about the future of the system. The starting point: acknowledging that it’s not about bad people; it’s about systemic flaws in its design and functioning. Fixing it requires balancing lag indicators about its use, costs and demand with assumptions about innovations that hold promise to shift its trajectory long-term. It requires employers to actively participate: in 2009-2010, Big Business mistakenly chose to sit out deliberations about the Affordable Care Act. And it requires independent, visionary facilitation free from bias and input beyond the DC talking heads that have dominated reform thought leadership for 6 decades.

Or, collectively, we can watch events like last week’s roll by and witness the emergence of a large public utility serving most and a smaller private option for those that afford it. Or something worse.

P.S. Today, thousands will make the pilgrimage to Orlando for HIMSS24 kicking off with a keynote by Robert Garrett, CEO of Hackensack Meridian Health tomorrow about ‘transformational change’ and closing Friday with a keynote by Nick Saban, legendary Alabama football coach on leadership. In between, the meeting’s 24 premier supporters and hundreds of exhibitors will push their latest solutions to prospects and customers keenly aware healthcare’s future is not a repeat of its past primarily due to technology. Information-driven healthcare is dependent on technologies that enable cost-effective, customized evidence-based care that’s readily accessible to individuals where and when they want it and with whom.

And many will be anticipating HCA Mission Health’s (Asheville NC) Plan of Action response due to CMS this Wednesday addressing deficiencies in 6 areas including CMS Deficiency 482.12 “which ensures that hospitals have a responsible governing body overseeing critical aspects of patient care and medical staff appointments.” Interest is high outside the region as the nation’s largest investor-owned system was put in “immediate jeopardy” of losing its Medicare participation status last year at Mission. FYI: HCA reported operating income of $7.7 billion (11.8% operating margin) on revenues of $65 billion in 2023.

Cano Health files for bankruptcy

Posted on by • Posted in Bankruptcy, Disruption, Disruptive Technology, Financial Stewardship, Financial Viability, Financially Distressed, Innovation, Medicare Advantage, Primary Care, Primary Care Delivery Model, Primary Care Strategy, Private Equity • Leave a comment

https://mailchi.mp/1e28b32fc32e/gist-weekly-february-9-2024?e=d1e747d2d8

On Sunday, Miami, FL-based Cano Health, a Medicare Advantage (MA)-focused primary care clinic operator, filed for bankruptcy protection to reorganize and convert around $1B of secured debt into new debt.

The company, which went public in 2020 via a SPAC deal worth over $4B, has now been delisted from the New York Stock Exchange. After posting a $270M loss in Q2 of 2023, Cano began laying off employees, divesting assets, and seeking a buyer. As of Q3 2023, it managed the care of over 300K members, including nearly 200K in Medicare capitation arrangements, at its 126 medical centers. 

The Gist: 

Like Babylon Health before it, another “tech-enabled” member of the early-COVID healthcare SPAC wave is facing hard times. While the low interest rate-fueled trend of splashy public offerings was not limited to healthcare, several prominent primary care innovators and “insurtechs” from this wave have struggled, adding further evidence to the adages that healthcare is both hard and difficult to disrupt.

Given that Cano sold its senior-focused clinics in Texas and Nevada to Humana’s CenterWell last fall, Cano may draw interest from other organizations looking to expand their MA footprints.

General Catalyst announces intent to buy a health system

Posted on by • Posted in Disruption, Disruptive Technology, Health System, Mergers & Acquisitions, Private Equity, Transformation • Leave a comment

https://mailchi.mp/de5aeb581214/the-weekly-gist-october-13-2023?e=d1e747d2d8

On Sunday, venture capital (VC) firm General Catalyst unveiled the Health Assurance Transformation Corporation (HATCo), a new subsidiary company which aims to acquire a health system to serve as a blueprint for the VC firm’s vision of healthcare transformation. 

Sharing this news on the first day of the HLTH 2023 conference in Las Vegas, General Catalyst declined to comment on which health systems are targets, or how much it is willing to spend, but CEO Hemant Taneja suggested that investment returns would be evaluated on a longer timeline than the typical 10-year venture capital horizon. 

Dr. Marc Harrison, the former CEO of Intermountain Health who joined General Catalyst in 2022, has been tapped to lead HATCo. The new company will build on General Catalyst’s previously announced partnerships with health systems, including Intermountain, HCA Healthcare, and Universal Health Services, with the goal of connecting healthcare startups with health systems in order to test and scale their technologies.  

The Gist: While private equity firms have backed health systems before, a VC firm expressing interest in health system ownership is a surprising development. 

Even on a longer timeframe than most venture plays get, it’s difficult to imagine a health system ever delivering the outsized returns VC investors usually demand. It’s possible HATCo’s true value will come from scaling and selling the services of tech startups in General Catalyst’s portfolio after vetting them at their health system “proving ground”. 

HATCo’s more ambitious aim to align payers and providers in a pivot to value-based care is a familiar one, but the new venture will find itself up against skepticism from insurers and other entrenched stakeholders, which has been difficult for even the most motivated health systems to overcome.

The AI-empowered patient is coming. Are doctors ready?

Posted on by • Posted in Artificial Intelligence, Artificial Intelligence Generative, ChatGPT, ChatGPT-4, Disruption, Disruptive Technology, Google’s Med-PaLM 2, Innovation, Physician • Leave a comment

https://www.linkedin.com/pulse/ai-empowered-patient-coming-doctors-ready-robert-pearl-m-d-/

Artificial intelligence (AI) has long been heralded as an emerging force in medicine. Since the early 2000s, promises of a technological transformation in healthcare have echoed through the halls of hospitals and at medical meetings.

But despite 20-plus years of hype, AI’s impact on medical practice and America’s health remains negligible (with minor exceptions in areas like radiological imaging and predictive analytics).

As such, it’s understandable that physicians and healthcare administrators are skeptical about the benefits that generative AI tools like ChatGPT will provide.

They shouldn’t be. This next generation of AI is unlike any technology that has come before. 

The launch of ChatGPT in late 2022 marked the dawn of a new era. This “large language model” developed by OpenAI first gained notoriety by helping users write better emails and term papers. Within months, a host of generative AI products sprang up from Google, Microsoft and Amazon and others. These tools are quickly becoming more than mere writing assistants.

In time, they will radically change healthcare, empower patients and redefine the doctor-patient relationship. To make sense of this bold vision for the future, this two-part article explores:

  1. The massive differences between generative AI and prior artificial intelligences
  2. How, for the first time in history, a technological innovation will democratize not just knowledge, but also clinical expertise, making medical prowess no longer the sole domain of healthcare professionals.

To understand why this time is different, it’s helpful to compare the limited power of the two earliest generations of AI against the near-limitless potential of the latest version.

Generation 1: Rules-Based Systems And The Dawn Of AI In Healthcare

The latter half of the 20th century ushered in the first generation of artificial intelligence, known as rule-based AI.

Programmed by computer engineers, this type of AI relies on a series of human-generated instructions (rules), enabling the technology to solve basic problems.

In many ways, the rule-based approach resembles a traditional medical-school pedagogy where medical students are taught hundreds of “algorithms” that help them translate a patient’s symptoms into a diagnosis.

These decision-making algorithms resemble a tree, beginning with a trunk (the patient’s chief complaint) and branching out from there. For example, if a patient complains of a severe cough, the doctor first assesses whether fever is present. If yes, the doctor moves to one set of questions and, if not, to a different set. Assuming the patient has been febrile (with fever), the next question is whether the patient’s sputum is normal or discolored. And once again, this leads to the next subdivision. Ultimately each end branch contains only a single diagnosis, which can range from bacterial, fungal or viral pneumonia to cancer, heart failure or a dozen other pulmonary diseases.

This first generation of AI could rapidly process data, sorting quickly through the entire branching tree. And in circumstances where the algorithm could accurately account for all possible outcomes, rule-based AI proved more efficient than doctors.

But patient problems are rarely so easy to analyze and categorize. Often, it’s difficult to separate one set of diseases from another at each branch point. As a result, this earliest form of AI wasn’t as accurate as doctors who combined medical science with their own intuition and experience. And because of its limitations, rule-based AI was rarely used in clinical practice.

Generation 2: Narrow AI And The Rise Of Specialized Systems

As the 21st century dawned, the second era of AI began. The introduction of neural networks, mimicking the human brain’s structure, paved the way for deep learning.

Narrow AI functioned very differently than its predecessors. Rather than researchers providing pre-defined rules, the second-gen system feasted on massive data sets, using them to discern patterns that the human mind, alone, could not.

In one example, researchers gave a narrow AI system thousands of mammograms, half showing malignant cancer and half benign. The model was able to quickly identify dozens of differences in the shape, density and shade of the radiological images, assigning impact factors to each that reflected the probability of malignancy. Importantly, this kind of AI wasn’t relying on heuristics (a few rules of thumb) the way humans do, but instead subtle variations between the malignant and normal exams that neither the radiologists nor software designers knew existed.

In contrast to rule-based AI, these narrow AI tools proved superior to the doctor’s intuition in terms of diagnostic accuracy. Still, narrow AI showed serious limitations. For one, each application is task specific. Meaning, a system trained to read mammograms can’t interpret brain scans or chest X-rays.

But the biggest limitation of narrow AI is that the system is only as good as the data it’s trained on. A glaring example of that weakness emerged when United Healthcare relied on narrow AI to identify its sickest patients and give them additional healthcare services.

In filtering through the data, researchers later discovered the AI had made a fatal assumption. Patients who received less medical care were categorized as healthier than patients who received more. In doing so, the AI failed to recognize that less treatment is not always the result of better health. This can also be the result of implicit human bias.

Indeed, when researchers went back and reviewed the outcomes, they found Black patients were being significantly undertreated and were, therefore, underrepresented in the group selected for additional medical services.

Media headlines proclaimed, “Healthcare algorithm has racial bias,” but it wasn’t the algorithm that had discriminated against Black patients. It was the result of physicians providing Black patients with insufficient and inequitable treatment. In other words, the problem was the humans, not narrow AI.

Generation 3: The Future Is Generative

Throughout history, humankind has produced a few innovations (printing press, internet, iPhone) that transformed society by democratizing knowledge—making information easier to access for everyone, not just the wealthy elite.

Now, generative AI is poised to go one step further, giving every individual access to not only knowledge but, more importantly, expertise as well.

Already, the latest AI tools allow users to create a stunning work of art in the style of Rembrandt without ever having taken a painting class. With large language models, people can record a hit song, even if they’ve never played a musical instrument. Individuals can write computer code, producing sophisticated websites and apps, despite never having enrolled in an IT course.

Future generations of generative AI will do the same in medicine, allowing people who never attended medical school to diagnose diseases and create a treatment plan as well as any clinician.

Already, one generative AI tool (Google’s Med-PaLM 2) passed the physician licensing exam with an expert level score. Another generative AI toolset responded to patient questions with advice that bested doctors in both accuracy and empathy. These tools can now write medical notes that are indistinguishable from the entries that physicians create and match residents’ ability to make complex diagnoses on difficult cases.

Granted, current versions require physician oversight and are nowhere close to replacing doctors. But at their present rate of exponential growth, these applications are expected to become at least 30 times more powerful in the next five years. As a result, they will soon empower patients in ways that were unimaginable even a year ago.

Unlike their predecessors, these models are pre-trained on datasets that encompass the near-totality of publicly available information—pulling from medical textbooks, journal articles, open-source platforms and the internet. In the not-distant future, these tools will be securely connected to electronic health records in hospitals, as well as to patient monitoring devices in the home. As generative AI feeds on this wealth of data, its clinical acumen will skyrocket.

Within the next five to 10 years, medical expertise will no longer be the sole domain of trained clinicians. Future generations of ChatGPT and its peers will put medical expertise in the hands of all Americans, radically altering the relationship between doctors and patients.

Whether physicians embrace this development or resist is uncertain. What is clear is the opportunity for improvement in American medicine. Today, an estimated 400,000 people die annually from misdiagnoses, 250,000 from medical errors, and 1.7 million from mostly preventable chronic diseases and their complications.

In the next article, I’ll offer a blueprint for Americans as they grapple to redefine the doctor-patient relationship in the context of generative AI. To reverse the healthcare failures of today, the future of medicine will have to belong to the empowered patient and the tech-savvy physician. The combination will prove vastly superior to either alone.

Health “insurtechs” struggling to stay relevant

Posted on by • Posted in Accountable Care Organization (ACO), Disruption, Disruptive Technology, Financial Viability, Financially Distressed, Health Insurance Industry, Initial Public Offering (IPO), Innovation, Insurtechs, Medical Loss Ratio (MLR), Medicare Advantage, Operating Expenses, Operating Income, Operating Margin, Operating Performance • Leave a comment

https://mailchi.mp/9fd97f114e7a/the-weekly-gist-october-6-2023?e=d1e747d2d8

“Insurtechs” Clover Health, Oscar Health, and Bright Health all went public in the midst of the hot equity market of 2021. Investors were excited by the fast growth of these health insurer startups, and their potential to revolutionize an industry dominated by a few large players.

However, the hype has dissipated as financial performance has deteriorated. After growing at all costs during a period of low interest rates, changing market conditions directed investors to demand a pivot to profitability, which the companies have struggled to deliver—two years later, none of the three has turned a profit. 

Oscar and Bright have cut back their market presence significantly, while Clover has mostly carried on while sustaining high losses. In the last two years, only Oscar has posted a medical loss ratio in line with other major payers, who meanwhile are reporting expectation-beating profits. While Oscar has shown signs of righting the ship since the appointment of former Aetna CEO Mark Bertolini, 

the future of these small insurers remains uncertain. As their losses mount and they exit markets, they may become less desirable as acquisition targets for large payers.

Cain Bros House Calls Kickstarting Innovation (Part 2)

Posted on by • Posted in Differentiation, Disruption, Disruptive Technology, Health System, Hospital, Hospital Industry, Innovation, Innovative Care Models, Payvider, Private Equity, Restructure, Return on Investment, Strategic Advantage, Strategic Alignment, Strategic Change, Strategic Leadership, Strategic Resource Allocation, Strategy and Transformation, Strategy Sustainable Long Term • Leave a comment
Cain Bros House Calls Kickstarting Innovation (Part 2)

This is Part 2 of a series by Cain Brothers about the first-ever collaboration conference between health systems and private equity (PE) investment firms. Part 1 of this series addressed the conference’s who, what and where. This commentary will focus on the why. We will explore the underlying forces uniting health systems with private equity during this period of unprecedented industry disruption.

Why Health Systems and PE Need Each Other

On June 13 and 14, 2023, Cain Brothers hosted the first-ever collaboration conference between health systems and private equity (PE) investment firms. Timing, market dynamics and opportunity aligned. The conference was an over-the-moon success. Along with its sponsors, Cain Brothers will seek to expand the conference and align initiatives through the coming years.

Why Now? Healthcare is Stuck and Needs Solutions

As a society, the U.S. is spending ever-higher amounts of money while its population is getting sicker. A maldistribution of facilities and practitioners creates inequitable access to healthcare services in lower-income communities with the highest levels of chronic disease.

New competitors and business models along with unfavorable macro forces, including high inflation, aging demographics and deteriorating payer mixes, are fundamentally challenging health systems’ status quo business practices.

Over the last 50 years, healthcare funding has shifted dramatically away from individuals and toward commercial and governmental payers. In 1970, individual out-of-pocket spending represented 36.5% of total healthcare spending. Today, it is just over 10%.

Governments, particularly the federal government, have become healthcare’s largest payers, funding over 40% of healthcare’s projected $4.7 trillion expenditure in 2023. Individual patients often get lost in the massive payment shuffle between payers and providers.

Meanwhile, governments’ pockets are emptying. As a percentage of GDP, U.S. government debt obligations have grown from 55% in 2001 to 124% currently. With rising interest rates and the commensurate increase in debt service costs, as well as an aging population, there is little to suggest that new funding sources will emerge to fund expansive healthcare expenditures. Scarcity reigns where resources for healthcare providers were once plentiful.

As a consequence, the healthcare industry is entering a period of more fundamental economic limitations. Delaying transformation and expecting society to fund ongoing excess expenditure is not a sustainable long-term strategy. Current economic realities are forcing a dramatic reallocation of resources within the healthcare industry.

The healthcare industry will need to do more with less. Pleading poverty will fall on deaf ears. There will be winners and losers. The nation’s acute care footprint will shrink. For these reasons, health systems are experiencing unprecedented levels of financial distress. Indeed, parts of the system appear on the verge of collapse, particularly in medically underserved rural and urban communities.

More of the same approaches will yield more of the same dismal results. Waking up to this existential challenge, enlightened health systems have become more open to new business models and collaborative partnerships.

Necessity Stimulates Innovation

Two disruptive and value-based business models are on the verge of achieving critical mass. They are risk-bearing “payvider” companies (e.g. Kaiser, Oak Street Health and others) and consumer-friendly, digital-savvy delivery platforms (e.g. OneMedical and innumerable point-solution companies).

Value-based care providers and their investors have the scars and bruises to show for challenging entrenched business practices reliant on fee-for-service (FFS) business models and administrative services only (ASO) contracting. Incumbents have protected their privileged market position well through market leverage and outsized political influence.

Despite market resistance, “payvider” and digital platform companies are emerging from the proverbial “innovators’ chasm.” More early adopters, including those health systems attending the Nashville conference, are embracing value-creating business models. The chart below illustrates the well-trodden path innovation takes to achieve market penetration.

Ironically, during this period of industry disruption, health systems understand they need to deliver greater value to customers to maintain market relevance. It will require great execution and overcoming legacy practices to develop business platforms that incorporate the following value-creating capabilities:

  • Decentralized care delivery (to make care more accessible and lower cost).
  • Root-cause treatment of chronic conditions.
  • Integrated physical and mental healthcare services.
  • Consistent, high-quality consumer experience.
  • Coordinated service delivery.
  • Standardized protocols that improve care quality and outcomes.
  • A truly patient/customer-centric operating orientation.

It’s not what to do, it’s how to get it done that creates the vexing conundrum. Solutions require collaboration. Platform business models replete with strategic partnerships are emerging. Paraphrasing an African proverb, it’s going to take a village to fix healthcare. That’s why the moment for health systems and PE firms to collaborate is now.

PE to the Rescue?

Private equity has become the dominant investment channel for business growth across industries and nations. According to a recent McKinsey report, PE has more than $11.7 trillion in assets under management globally. This is a massive number that has grown steadily. PE changes markets. It turbocharges productivity. It is a relentless force for value creation.

By investing in a wide spectrum of asset classes, private equity has become a vital source of investment returns for pensions, endowments, sovereign wealth funds and insurance companies. Healthcare, given its size and inefficiencies, is a target-rich environment for PE investment and returns. This explains the PE’s growing interest in working with health systems to develop mutually beneficial, value-creating healthcare enterprises.

Despite reports to the contrary, PE firms must invest for the long term. Unlike the stock market, where investors can buy and sell a stock within a matter of seconds, PE firms do not have that luxury. To generate a return, they must acquire and grow businesses over a period of years to create suitable exit strategies.

Money talks. By definition, all buyers of new companies value their purchase more than the capital required for the acquisition. In making purchase decisions, buyers evaluate businesses’ past performance. They also assess how the new business will perform under their stewardship. PE or PE-backed acquirers also consider which future buyers will be most likely acquire the company after a five-plus year development period.

PE’s investment approach can align well with health systems looking to create sustainable long-term businesses tied to their brands and market positioning. PE firms buy and build companies that attract customers, employees and capital over the long term, far beyond their typical five- to seven-year ownership period. Health systems that partner with PE firms to develop companies are the logical acquirers of those companies if they succeed in the marketplace. In this way, a rising valuation creates value for both health systems and their PE partners.

It is important to note that not all PE are created the same. Like health systems, PE firms differ in size, market orientation, investment theses, experience and partner expectations. Given this inherent diversity, it takes time, effort and a shared commitment to value creation for health systems and PE firms to determine whether to become strategic partners. Not all of these partnerships will succeed, but some will succeed spectacularly.

For health system-PE partnerships to work, the principals must align on strategic objectives, governance, performance targets and reporting guidelines. Trust, honest communication and clear expectations are the key ingredients that enable these partnerships to overcome short-term hurdles on the road to long-term success.

Conclusion: Time to Slay Healthcare’s Dragons

Market corrections are hard. As a nation, the U.S. has invested too heavily in hospital-centric, disease-centric, volume-centric healthcare delivery. The result is a fragmented, high-cost system that fails both consumers and caregivers. The marketplace is working to reallocate resources away from failing business practices and into value-creating enterprises that deliver better care outcomes at lower costs with much less friction.

Progressive health systems and PE firms share the goal of creating better healthcare for more Americans. Cain Brothers is committed to advancing collaboration between health systems and PE-backed companies. In addition to the Nashville conference, the firm has combined its historically separate corporate and non-profit coverage groups to foster idea exchange, expand sector understanding and deliver higher value to clients.

The ability to connect and collaborate effectively with private equity to advance business models will differentiate winning health systems. In a consolidating industry, this differentiation is a prerequisite for sustaining competitiveness. It’s adapt or die time. Health systems that proactively embrace transformation will control their future destiny. Those that fail to do so will lose market relevance.

The future of healthcare is not a zero-sum equation. Markets evolve by creating more complex win-win arrangements that create value for customers. No industry requires restructuring more than healthcare. As a nation and an industry, we have the capacity to fix America’s broken healthcare system. The real question is whether we have the collective will, creativity and resourcefulness to power the transformation. We believe the answer to that question is yes.

Paraphrasing Rev. Theodore Parker, the economic arc of the marketplace is long but it bends toward value. Together, health systems and PE firms can power value-creation and transformation more effectively than either sector can do independently. Each needs the other to succeed. Slaying healthcare’s dragons will not be easy but it is doable. It’s going to take a village to fix healthcare.

Retail giants vs. health systems: Fight will come down to ‘system-ness’

Posted on by • Posted in Capitation, Chronic Care Management, Continuous Care, Disease Management, Disruption, Disruptive Technology, Health System, Hospital, Hospital Industry, Innovation, Innovative Care Models, Retail Healthcare, Specialized Medicine, Systemness, Value-Based Contracting, Value-Based Healthcare • Leave a comment

https://www.linkedin.com/pulse/retail-giants-vs-health-systems-fight-come-down-robert-pearl-m-d-/?trackingId=163%2Bb4FP3L%2B%2BO9I24fNl0Q%3D%3D

Value-based healthcare, the holy grail of American medicine, has three parts: excellent clinical quality, convenient access and affordability for all.

And as with the holy grail of medieval legend, the quest for value-based care has been filled with failure.

In the 20th century, U.S. medical groups and hospital systems could—at best—achieve two elements of value-based care, but always at the sacrifice of the third. Until recently, American medicine lacked the clinical knowhow, technology and operational excellence to accomplish all three, simultaneously. We now have the tools. The only thing missing is “system-ness.”

What Is System-ness?

System-ness is the effective and efficient coordination of healthcare’s many parts: outpatient and inpatient, primary and specialty care, financing and care delivery, prevention and treatment.

By bringing these disparate pieces together within a well-functioning system, healthcare providers have the opportunity to maximize clinical outcomes, weed out waste, lower overall costs and provide greater levels of convenience and access.

Who Are The Search Parties? 

In the future, system-ness will be the variable that determines whether healthcare transformation is led by (a) incumbent health systems like Kaiser Permanente and Geisinger Health or (b) the retail giants like Amazon, CVS and Walmart. The latter group has become an ever-growing threat in the healthcare arms race, quickly amassing their own (though still modest) systems of care through billion-dollar acquisitions.

Although both the incumbents and new entrants will struggle to implement value-based care on a national scale, the victor stands to earn hundreds of billions of dollars in added revenue and tens of billions in profits.

To better understand the power of system-ness, and the challenges all organizations will face in providing it, here are three examples of value-based-care solutions implemented successfully by Kaiser Permanente.

1. Preventing Problems, Managing Disease

Research demonstrates that preventive medicine and early intervention reduce heart attacks, strokes and cancer. Yet our nation falls far short in these areas when compared to its global peers.

One example is hypertension, the leading cause of strokes and a major contributor to heart attacks. With help from doctors, nearly all patients can keep high blood pressure under control. Yet, nationally, hypertension is controlled only 60% of the time.

We see similarly poor rates of performance when it comes to prevention and screening for cancers of the colon, breast and lung.

Undoing these troubling trends requires system-ness. In Kaiser Permanente, 90% of patients had their blood pressure controlled and were screened for cancer. Getting there required a comprehensive electronic health record, a willingness for every doctor (regardless of specialty) to focus on prevention, leadership that communicated the value of prevention and a salary structure that rewarded group excellence.

2. Continuous Care, Without Interruption  

Most doctors’ offices are open Monday to Friday during normal business hours—only one-fourth of the time that a medical problem might occur.

At night and on weekends, patients have no choice but to visit ERs. There, they often wait hours for care, surrounded by people with communicable diseases. Their non-emergent problems generate bills 12-times higher than if they’d waited to be seen in a doctor’s office.

There’s a better way. In large-enough medical groups, hundreds of clinicians can provide round-the-clock care on a rotating, virtual basis—using video to assess patients and make evidence-based recommendations.

This approach, pioneered by physicians in the Mid-Atlantic Permanente Medical group, solved the patient’s problem immediately 70% of the time without a trip to the ER and, for the other 30%, enabled coordination of medical care with the ER staff.

3. Specialized Medicine, Immediate Attention

When a primary care physician needs added expertise (from a dermatologist, urologist or orthopedist), it’s usually the responsibility of the patient to make their own specialty appointments, check with insurance for coverage and provide their medical records.

This takes hours or days to coordinate and can delay care by weeks, resulting in avoidable complications.

But in a well-structured system, there’s no need to wait. Using telehealth tools at Kaiser Permanente, primary care doctors can connect instantly with dozens of different specialists—often while the patient is still in the exam room. Once connected, the specialist evaluates the patient and provides immediate expertise.

This way, care is not only faster and less expensive, but also better coordinated. Data from within Kaiser Permanente show that these virtual consultations resolve the patient’s problem 40% of the time without having to schedule another appointment. For the other 60%, the diagnostic process can begin immediately.

The Foundations For System-ness

Few organizations in the U.S. can or do offer these system-based improvements. Doing so requires skilled physician leadership, a shift in the financial model and a willingness to accept risk.

In fact, most organizations across the U.S. that claim to operate “value-based” systems actually rely on doctors who are scattered across the community, disconnected from each other and paid on the basis of volume (fee-for-service) rather than value (capitation).

As a result, patient care is fragmented and uncoordinated, leading to repeated tests and ineffective treatments, thus increasing medical costs and compromising medical outcomes.

Value-based care (superior quality, access and affordability) requires teams of clinicians working together as one—all paid on a capitated basis.

Without capitation, dermatologists will insist on seeing every patient in their office where they can bill insurance five-times more than with a tele-dermatology visit. And gastroenterology specialists will insist that all patients have colonoscopy rather than recommending low-risk patients do a safe, convenient, at-home colon cancer screening (called a fecal immunochemical test or “FIT”) at 5% of the cost.

In these cases, individual doctors don’t consciously make care inconvenient for patients. Rather, it is the only choice they have when working in a fee-for-service payment model. Ultimately, system-ness is best achieved when health systems are integrated, prepaid, tech-enabled and physician-led. 

Amazon, CVS, Walmart Know About Systems

These three companies are global leaders in “system-ness,” at least in retail. Combined, they have a market cap of $1.88 trillion, employ 3.4 million Americans and are looking to take a slice of U.S. healthcare’s $4.3 trillion annual expenditures.

Already, they manage complex order-entry and fulfillment systems. They use technology to streamline everything from customer service to supply-chain management. They are led through a clear and effective reporting structure.

In terms of competing for healthcare’s holy grail, these are huge competitive advantages compared to today’s uncoordinated, individualized, leaderless healthcare industry.

As retailers vie to bring their system knowhow to American medicine, they are acquiring the pieces needed to compete with the healthcare incumbents. They’ve spent tens of billions of dollars on medical groups that are committed to value-based care (One Medical, Oak Street Health, etc.). They’ve also spent massive sums on home-health companies (Signify) and on pharmacies (PillPak), along with expanding their in-store, at-home and online care options. Many of these care-delivery subsidiaries are focused on Medicare Advantage, the capitated half of Medicare where financial success is dependent on high quality medical care provided at lower cost.

What’s more, all these retailers have a national presence with brick-and mortar facilities in nearly every community in the country—a leg up on nearly every existing health system.

Who Will Win—And Why?

Trying to pick the victor in the battle to transform American medicine at this point is like selecting the winner of a heavy-weight championship boxing match after three evenly matched rounds. Intangibles like stamina, courage and willingness to absorb pain have yet to be tested.  

In The Innovator’s Dilemma, the late Clayton Christensen examined historical battles between incumbent organizations and new entrants. After analyzing dozens of industries, he concluded new entrants routinely become the victors because the incumbents move too slowly and fail to embrace the need for major change.

And from that perspective, if I had to wager, I’d put my money on the retail giants.

But there’s an even more worrisome potential outcome: neither those inside nor outside of healthcare will make the necessary investments or accept the risk of leading systemic change. As a result, the movement toward value-based healthcare will stall and die.

In that context, purchasers of healthcare (businesses, the government and patients) will encounter a difficult reality: over the next eight years, medical costs will nearly double, creating an unaffordable and unsustainable scenario. As a result, our nation will likely experience reduced medical coverage, increased rationing, ever-longer delays for care and a growth in health disparities.

If that day arrives, our country will regret its inaction.

Opinion:  The AI revolution in health care is already here

Posted on by • Posted in Artificial Intelligence, Artificial Intelligence Generative, Artificial Intelligence Predictive, Clinical Decision Making Software, Clinical Decision Support Systems, Disruption, Disruptive Technology, Innovation, Innovative Care Models, Patient Centered Care, Quality of Care • Leave a comment
https://www.washingtonpost.com/opinions/2023/07/11/ai-health-care-revolution/?utm_source=Sailthru&utm_medium=email&utm_campaign=Issue:%202023-07-12%20Healthcare%20Dive%20%5Bissue:52339%5D

Pay attention to the media coverage around artificial intelligence, and it’s easy to get the sense that technologies such as chatbots pose an “existential crisis” to everything from the economy to democracy.

These threats are real, and proactive regulation is crucial. But it’s also important to highlight AI’s many positive applications, especially in health care.

Consider the Mayo Clinic, the largest integrated, nonprofit medical practice in the world, which has created more than 160 AI algorithms in cardiology, neurology, radiology and other specialties. Forty of those have already been deployed in patient care.

To better understand how AI is used in medicine, I spoke with John Halamka, a physician trained in medical informatics who is president of Mayo Clinic Platform. As he explained to me, “AI is just the simulation of human intelligence via machines.”

Halamka distinguished between predictive and generative AI. The former involves mathematical models that use patterns from the past to predict the future; the latter uses text or images to generate a sort of human-like interaction.

It’s that first type that’s most valuable to medicine today. As Halamka described, predictive AI can look at the experiences of millions of patients and their illnesses to help answer a simple question: “What can we do to ensure that you have the best journey possible with the fewest potholes along the way?”

For instance, let’s say someone is diagnosed with Type 2 diabetes. Instead of giving generic recommendations for anyone with the condition, an algorithm can predict the best care plan for that patient using their age, geography, racial and ethnic background, existing medical conditions and nutritional habits.

This kind of patient-centered treatment isn’t new; physicians have long been individualizing recommendations. So in this sense, predictive AI is just one more tool to aid in clinical decision-making.

The quality of the algorithm depends on the quantity and diversity of data. I was astounded to learn that the Mayo Clinic team has signed data-partnering agreements with clinical systems across the United States and globally, including in Canada, Brazil and Israel. By the end of 2023, Halamka expects the network of organizations to encompass more than 100 million patients whose medical records, with identifying information removed, will be used to improve care for others.

Predictive AI can also augment diagnoses. For example, to detect colon cancer, standard practice is for gastroenterologists to perform a colonoscopy and manually identify and remove precancerous polyps. But some studies estimate that 1 in 4 cancerous lesions are missed during screening colonoscopies.

Predictive AI can dramatically improve detection. The software has been “trained” to identify polyps by looking at many pictures of them, and when it detects one during the colonoscopy, it alerts the physician to take a closer look. One randomized controlled trial at eight centers in the United States, Britain and Italy found that using such AI reduced the miss rate of potentially cancerous lesions by more than half, from 32.4 percent to 15.5 percent.

Halamka made a provocative statement that within the next five years, it could be considered malpractice not to use AI in colorectal cancer screening.

But he was also careful to point out that “it’s not AI replacing a doctor, but AI augmenting a doctor to provide additional insight.” There is so much unmet need that technology won’t reduce the need for health-care providers; instead, he argued, “we’ll be able to see more patients and across more geographies.”

Generative AI, on the other hand, is a “completely different kind of animal,” Halamka said. Some tools, such as ChatGPT, are trained on un-curated materials found on the internet. Because the inputs themselves contain inaccurate information, the models can produce inappropriate and misleading text. Moreover, whereas the quality of predictive AI can be measured, generative AI models produce different answers to the same question each time, making validation more challenging.

At the moment, there are too many concerns over quality and accuracy for generative AI to direct clinical care. Still, it holds tremendous potential as a method to reduce administrative burden. Some clinics are already using apps that automatically transcribe a patient’s visit. Instead of creating the medical record from scratch, physicians would edit the transcript, saving them valuable time.

Though Halamka is clearly a proponent of AI’s use in medicine, he urges federal oversight. Just as the Food and Drug Administration vets new medications, there should be a process to independently validate algorithms and share results publicly. Moreover, Halamka is championing efforts to prevent the perpetuation of existing biases in health care in AI applications.

This is a cautious and thoughtful approach. Just like any tool, AI must be studied rigorously and deployed carefully, while heeding the warning to “first, do no harm.”

Nevertheless, AI holds incredible promise to make health care safer, more accessible and more equitable.

Entering the next “golden age” of medical innovation

Posted on by • Posted in Cancer Treatment, Clinical Innovation, CRISPR Gene Therapy, CRISPRs, Disruptive Technology, Health System, Hospital, Hospital Industry, Innovation, Innovative Care Models, Medical Innovation, mRNA-based Vaccines, Strategic Change, Strategy, Strategy Clinical, Strategy Demand-Driven, Strategy Development, Weight Loss Drugs • Leave a comment

https://mailchi.mp/7f59f737680b/the-weekly-gist-june-30-2023?e=d1e747d2d8

The New York Times Magazine published an encouraging piece about the impressive series of recent medical breakthroughs, many of which have been in the works for decades. 

Challenging the conventional wisdom that disruptive scientific breakthroughs have slowed over time, the article points out that the last five years of medicine have featured the rollout of mRNA vaccines, the first instance of a person receiving CRISPR gene therapy, and development of next-generation cancer treatment and weight-loss drugs. 

The Gist: The expanding innovation pipeline not only brings excitement and optimism for patients and physicians, but also has the potential to dramatically impact long-established care delivery pathways. 

Case in point: used at scale, new weight loss drugs could curb obesity-related chronic diseases and joint replacements—while possibly increasing the incidence of Alzheimer’s disease and cancer as more people live longer lives. 

Providers planning for facility and other long-term investments must think through scenarios about how these early, but very promising, innovations could alter demand and shift care delivery needs over coming decades.

Solving Baumol’s Cost Disease, in Healthcare

Posted on by • Posted in Artificial Intelligence, Baumol's Cost Disease, Cost Disease, Cost Reduction, Disruptive Technology, Innovation • Leave a comment

Why does the cost of education and healthcare services continue to rise rapidly, while the cost of goods rise much more slowly? According to economics theory, wages rise when there’s greater productivity; but a rise without an increase in productivity is referred to as “Baumol’s Cost Disease” . In an original study first published in 1966, economist William J. Baumol used the example of a string quartet to illustrate this idea: While the productivity of a given quartet has not increased over time over the last two hundred years, the salary (in nominal and real terms) has increased dramatically. 

One way out of this trap is to turn services into goods. Employing a cobbler to make a pair of custom shoes, for instance, is expensive, so we buy factory made shoes: shoes as a good instead of as a service. In doing so, we accept some limitations: a finite set of styles and sizes to choose from; perhaps a less-than-perfect fit for each individual foot; limited styles and customizations — but with the positive trade off in favor of greatly decreased cost. In much the same way, we consume the “good” of the string quartet in the form of a digital recording of a musical piece, instead of the “service” of a live performance. In short, turning services into goods industrializes the process, increasing efficiency and reducing cost. 

But is this seemingly alchemical transformation possible in healthcare?

Until today, it’s essentially been accepted as a given that this cost “disease” is incurable where there’s the need for professional, highly trained people performing services — industries like healthcare, education — and therefore drives some of the biggest cost crises of our day, that affect many people in countless ways. 

To cure Baumol’s cost disease, we would have to transform the industry’s professional human labor into something that can be manufactured, commoditized, industrialized, and automated. While this has long been an issue in healthcare, for many good and bad reasons, the cure involves bringing more artificial intelligence (AI) to the industry. AI creates a new opportunity: to transform services into goods.

In healthcare, unlike in other industries—like social media content analysis, or self-driving cars—the kind of data labelling needed is actually already an intrinsic part of the healthcare system.

It’s no magic bullet for sure; even our own a16z partners Martin Casado and Matt Bornstein have argued that in enterprise companies, this won’t work, and that AI in this case effectively just replaces human services with different human services with few gains, given all the data cleanup and edge cases involved. But in healthcare, unlike in other industries — like social media content analysis, or self-driving cars — the kind of data labelling needed is actually already an intrinsic part of the healthcare system. In much the same way it is an intrinsic part of Google search — where people choose the most relevant link in the search results, and Google’s AI learns from this, improving with each search — whenever a doctor diagnoses a condition, prescribes a mediation, or interprets an x-ray, that information is then encoded into the electronic health record (EHR). Or, it’s in revenue cycle management —  how all bills are paid in healthcare — where people currently perform the manual tasks of identifying what is billable, and to whom. Using AI to learn from these coders (the way, for example, Alpha Health does) means  the human work — human labeling — is “free”, since it’s part of what we’re doing anyway. 

What’s more, the data is high quality, because when all the doctors in the system are labellers, AI ensures every doctor has the very best teachers in the world — no single doctor alone could ever have that roster of mentors. Training is done on all patients, AI learns from everything, and everybody… and then outputs the results back out to everyone.  

AI learns from everything, and everybody… and then outputs the results back out to everyone.

Of course, it’s not a total walk in the park; work needs to be done to integrate this data into the system. One you solve data labelling, you have to train with those labels. Data labelling is just one of the reasons AI based businesses are perceived to have low margins (often requiring an enormous amount of GPU or CPU time, and at great expense. But human training is also expensive: training must often be customized to individuals, and often needs to be redone as employees churn. Because computers are identical, training AI has no such challenges. If you compare the cost of AI training to the cost of executing a simple algorithm, AI training is expensive. If you compare the cost of AI training to the cost of human training, AI is cheap. And, AI training gets exponentially cheaper over time, because of Moore’s Law’s profoundly powerful compounding effects. So even if using AI is at cost parity with a service solution now, the eventual win is obvious. And to some degree, we can commoditize the AI itself as well, for more efficiency, by keeping customization low and training rare with AI.

Another complaint about AI’s ability to transform services into goods is what’s referred to as the “long tail of tasks.” This is the idea that AI won’t be useful if it can only perform a small fraction of what humans can. But in healthcare, even a small fraction of that long tail can have enormous impact. With the right, highly efficient training and labeling, AI can transform perhaps 5% of the human labor of analyzing bills and claims to automate from services to goods. By using AI to learn from medical billing — even just by triaging the “easy” and mundane cases (and escalating the “long tail” of more complex tasks to people as needed) — can bring a dramatic cost savings. Not to mention allowing people to focus on the more higher order aspects of the job, allowing them to deliver better results and service.

We’ve been waiting decades — maybe even centuries — for the ability to reverse Baumol’s Cost Disease in our most service-heavy, yet most critical, industries, such as healthcare.

The  transformation of services into goods won’t occur overnight. But Baumol himself couldn’t have foreseen the revolution that AI is creating, any more than someone in the Renaissance anticipating a shoe factory and Moore’s Law since. If applied in the right places, with the right conditions, taking into account the hard realities of the healthcare system, AI can be a vastly powerful lever to pull. We may not cure Baumol’s Cost Disease overnight, but even a small gain in cost and time savings would have huge impacts in healthcare.