AI in Medicine and Healthcare Blog

Wilmington Trust Interview - The AI Investment Lanscape

Tue, 21 Apr 2026 22:20:00 GMT

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My Latest Article for Inside Precision Medicine

Wed, 25 Mar 2026 21:27:33 GMT

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AI in Health #1 Best Selling Book at HIMSS 2026

Sun, 22 Mar 2026 19:07:03 GMT

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Looking Forward to Keynoting DHAI Summit

Tue, 03 Mar 2026 20:22:37 GMT

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The Hidden Leadership Skill that Makes AI Innovation Scale

Tue, 24 Feb 2026 20:01:30 GMT

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AI eBook Just Published - Free Download

Fri, 20 Feb 2026 22:00:48 GMT

Excited to share FINN Partners’ new eBook: Human-First Health Information: How AI, Data, and Innovation Are Rewriting the Future of Care.

As healthcare enters a new era of AI-enabled decision-making and data-driven transformation, one principle remains essential: human-first health information. Trusted, accessible, actionable insights that improve outcomes and strengthen patient experience.

I contributed a chapter focused on mastering your AI learning journey.

Click on this link to download a free copy.

In Celebration of Medical Misfits

Wed, 11 Feb 2026 14:57:34 GMT

Had bumper stickers existed in the 1850s, Dr. John Snow might have had one on the back of his carriage that later became popular in the 1960s with the counterculture crowd that read:

Subvert the Dominant Paradigm

It was 1854, and a deadly cholera outbreak was tearing through London. At the time, the medical establishment believed cholera spread through miasma—a poisonous cloud of bad air.

John Snow, an unknown physician who lived in the affected neighborhood, saw something different. As he watched neighbors die, he became convinced the disease wasn’t airborne—it was waterborne.

When Snow presented his theory to London’s medical leaders, he was dismissed. But he persisted. Through interviews, careful observation, data tables, and his now-famous map, Snow traced the outbreak to a contaminated water pump. His work helped stop the epidemic—and gave rise to what we now call epidemiology.

Healthcare has been here before.

Fast-forward to the 1970s. Even with mounting evidence, endoscopic surgery faced strong resistance. Leading surgeons believed “large problems required large incisions.” Minimally invasive “keyhole” surgery was dismissed.

Today, endoscopy is recognized as one of the most important breakthroughs in modern medicine.

Change is hard—especially in healthcare.

Since medicine emerged as a data-driven scientific discipline, progress has depended on leaders willing to challenge prevailing assumptions. Vaccines. Antibiotics. Sanitation. Clean water. Preventive care. None of these advances came from doing more of the same.

Standing behind every major leap forward were leaders who shared two traits:

They saw problems through a different lens.
They were willing to challenge the status quo to make healthcare better.

To be clear: thinking differently does not mean ignoring evidence or freestyling in the operating room. Medicine depends on rigor, standards, and proven best practices. But progress happens when we apply that science in new ways—more inclusive, more efficient, and more effective ways.

The art and science of thinking differently

Steve Jobs famously made “Think Different” a rallying cry, reminding us that the people who change the world are often the ones who see it differently.

True innovators connect the unconnected. They combine ideas across disciplines. They don’t just play the game better—they change the game.

Yet not all leaders are equal when it comes to innovation. Research shows that successful innovators spend significantly more time deliberately trying to think differently. For many people, this doesn’t come naturally—and it can feel uncomfortable or exhausting.

The good news? Thinking differently is a skill, not a gift. Most of our innovation capacity is shaped by environment and practice, not genetics. With repetition, what once felt uncomfortable becomes energizing—and that’s when the best ideas emerge.

History is full of reminders that even breakthrough ideas take time to find their true purpose. Early visions for the telephone included using it merely to notify people that a telegraph message had arrived.

And now, here we are—with AI.

AI has exploded into healthcare and society, driving change at a pace few organizations are prepared for. What works today will feel outdated tomorrow. Leaders who are complacent with the current state of healthcare will be eclipsed by those who think differently, plan creatively, and act with intent.

While many health leaders talk about innovating with AI, I’m looking for the misfits—the ones whose ideas make traditionalists uneasy, but who ultimately move health and medicine forward.

They’re the ones who’ve always changed the world. Could that be you?

The Future of Africa is Intelligent

Tue, 03 Feb 2026 17:03:00 GMT

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AMLD Africa brought together at the University of the Witwatersrand students and emerging tech entrepreneurs from across Africa for four days of learning, networking, and serious thinking about what’s possible. From delivering digital services to some of the world’s most remote, low-resource communities to upskilling Africans at scale and building sustainable solutions with global relevance, the ambition on display was extraordinary.

What impressed me most wasn’t just the depth of technical knowledge in the room—it was the hunger. The passion. And the clear sense of responsibility these young Africans feel to use AI and digital tools to improve Africa and, in doing so, improve the world.

If this generation is any indication, Africa’s future is not just promising—it’s already being built.

To the students and entrepreneurs, I met: ��’�� . �� .

#AMLDAfrica #ArtificialIntelligence #Africa #Innovation #Leadership #FutureOfWork #AIForGood #AfricaRising

Mastering Your AI Learning Journey

Tue, 20 Jan 2026 20:24:35 GMT

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The Real Disruption in Healthcare Isn’t AI. It’s the Rise of the Intelligent Health Consumer.

Tue, 13 Jan 2026 17:50:12 GMT

There’s a quiet but consequential misunderstanding happening in healthcare right now.

Across boardrooms and conference stages, leaders talk about artificial intelligence as if it’s the disruption to manage—the next great differentiator between healthcare organizations. Strategies are framed around AI adoption, governance, and maturity, as though intelligence itself is the “holy grail.”

It isn’t.

The real disruption didn’t arrive as a technology roadmap or a vendor demo. It walked through the front door, pulled out a phone, and sighed in frustration.

Your competition isn’t the health system across town. It’s the experience someone had with Amazon the night before.

Healthcare is no longer evaluated against healthcare. It’s evaluated against the rest of a person’s life—and in 2026 that life is increasingly intelligent, mobile, personalized, and relentlessly convenient. That is the shift many healthcare organizations still haven’t fully internalized.

Welcome to the era of the Intelligent Health Consumer.

I first wrote about the rise of the Intelligent Health Consumer in my 2020 book, AI in Healthcare – The Rise of Intelligent Health Systems. At the time, the idea felt forward-looking. Today, it’s no longer a prediction. It’s simply reality.

Consumers don’t wake up thinking about AI. They wake up inside it.

Intelligence has become the background hum of daily life—so embedded that it’s almost invisible. A wearable quietly interprets sleep patterns and physiological signals overnight. A bank resolves fraud before anxiety ever has a chance to surface. A travel app predicts price changes with uncanny timing. A streaming service understands mood and preference like a close friend.

None of this feels magical anymore. It feels normal.

And that distinction matters.

Because consumers don’t care how these systems work. They care about how they feel. These experiences remove effort. They anticipate needs. They deliver clarity without demanding attention. They respect time.

This is the world people now inhabit—one where intelligence fades into the background and life simply works.

And then a consumer enters healthcare.

Suddenly, everything slows down.

Tasks that should take minutes stretch into days. Answers that should be clear are buried inside portals filled with PDFs, unexplained terminology, and fragmented information. Scheduling feels transactional. Billing feels adversarial. Navigation feels like guesswork rather than guidance.

Not because clinicians lack compassion or capability—but because the experience surrounding the extraordinary skills, talents, and hopes of doctors, nurses, and care teams has not kept pace with the intelligence shaping the rest of a consumer’s life.

This is where the real gap lives.

It’s tempting to say healthcare is falling behind. That framing misses the mark. Clinically, healthcare is advancing at an extraordinary pace. Scientific discovery, diagnostics, therapeutics, and medical expertise continue to accelerate.

The problem is that everything outside healthcare is advancing even faster in how it communicates, anticipates, and personalizes.

The reference point has moved.

Healthcare hasn’t moved with it—yet.

Consumers feel that dissonance immediately. They don’t need surveys to tell them something is wrong. They feel it in the friction, the repetition, and the lack of continuity. They feel it when every other industry seems to remember them, but healthcare still asks them to explain themselves from scratch.

When that happens, healthcare isn’t compared to another hospital or health plan. It’s compared—often subconsciously—to the best experience they had yesterday.

That’s why the Amazon comparison matters. Not because healthcare should behave like retail, but because consumers carry expectations forward. Seamless ordering, proactive communication, and effortless resolution become the baseline. When healthcare falls short of that baseline, it doesn’t feel “complex.” It feels outdated.

At this point, many leaders retreat to a familiar refrain: healthcare is different. More regulated. More complex. More consequential.

All of that is true—and also beside the point.

Consumers don’t experience regulation. They experience interaction.

They don’t see complexity. They feel confusion.

They don’t care why something is hard. They only know that it is.

Here’s the uncomfortable reality: regulation does not require opacity. Complexity does not demand friction. Clinical care may be uniquely serious, but the experience around it does not need to feel uniquely broken.

The world has already reset expectations for how organizations communicate, respond, and adapt. Healthcare didn’t opt out of that reset. It simply hasn’t fully acknowledged it.

What’s driving this change isn’t AI adoption curves or technology roadmaps. It’s something far more powerful: expectation inflation .

For decades, healthcare transformation was driven by reimbursement changes, regulatory pressure, or policy shifts. Today, it’s driven by comparison. Consumers no longer compare hospitals to other hospitals. They compare healthcare to the best experiences they have anywhere in their lives.

This is the real disruption.

Not AI as a tool—but AI as a trainer of expectations.

Once consumers are taught that systems can anticipate, explain, and adapt, anything that doesn’t feels outdated. Any friction feels unnecessary. Any opacity feels like indifference.

The Intelligent Health Consumer isn’t waiting for healthcare to catch up. They’re already here, carrying expectations shaped elsewhere. They expect clarity without chasing it. They expect personalization without paperwork. They expect systems that remember, connect, and anticipate. They expect digital experiences that don’t require training manuals or patience.

Most importantly, they don’t view healthcare as a special ecosystem with separate rules. They view it as part of life. And life, now, is intelligent.

This doesn’t mean healthcare needs to become Amazon or Netflix. It doesn’t mean care should be transactional or superficial. It means healthcare must operate in a world where consumers are trained—every single day—by organizations that remove friction by default.

That is the shift.

The organizations that succeed over the next decade won’t be defined by the size of their campuses, the number of beds they operate, or even how much technology they deploy. They’ll be defined by how well they use intelligence to make care feel coherent, humane, and responsive.

They’ll understand something essential:

AI isn’t the story.
The consumer is.

The Intelligent Health Consumer has arrived. The only remaining question is whether healthcare is willing to meet them where they already are.

AI in 2026 – Boom, Bust or Backlash in Healthcare?

Tue, 06 Jan 2026 22:56:48 GMT

It was the fall of 2022 when Large Language Models and Generative AI burst out of research labs and onto Main Street. Since then, every day seems to bring another AI breakthrough that challenges how work gets done.

In my role advising organizations on AI strategy and deployments, I see a consistent pattern among healthcare leaders: excitement about what AI could unlock, paired with exhaustion from the volume of noise, pressure, and competing claims.

Welcome to 2026.

As predictions flood inboxes and social feeds, focused on what AI might do next, I want to ground the conversation in something more useful. Rather than forecasting outcomes, let’s focus on three forces already at work—forces that will determine whether AI delivers real value in healthcare or quietly stalls.

Will 2026 be a year of boom, bust, or backlash?

The honest answer is yes.

Boom: Early Wins—and an AI Arms Race

Let’s start with what’s working.

Healthcare is seeing real, if narrow, gains from AI:

Ambient documentation reducing administrative burden
Imaging and pathology tools improving speed and consistency
Operational and revenue cycle applications driving incremental efficiency

These are not moonshots. They are targeted solutions addressing specific pain points. And they matter.

At the same time, healthcare is now firmly in an AI arms race.

Every EHR vendor, medical device company, life sciences firm, and digital health startup is racing to declare itself “AI-native.” Roadmaps are packed with copilots, assistants, agents, and automation claims. No vendor wants to be perceived as falling behind.

That pressure is accelerating innovation—but it’s also compressing timelines, encouraging over-promising, and pushing organizations to adopt faster than they can realistically absorb.

Boom energy is real.

But it is also uneven and fragile.

Prediction: Within two years, most AI used in provider organizations will arrive embedded inside core systems and devices already in use. Intelligence will not be something teams “add on”; it will be something they inherit.

Recommendation: Understand where AI is already embedded across your vendor ecosystem and what’s coming next. Engage early through advisory councils or pilots. Engage and prepare clinicians before these capabilities are introduced into workflows. AI should never arrive as a surprise.

Bust: When Pilots Multiply, but Value Doesn’ t

Generative AI has dominated innovation agendas, yet only a fraction of pilots ever reach sustained production. A survey cited by MIT reports that roughly 95% of business AI pilots fail to generate measurable returns.

This is not evidence that AI lacks value.

It is evidence that many organizations lack discipline.

High failure rates are normal in early markets. Technology matures. Tools improve. But value only materializes when leaders focus on fundamentals: design, data readiness, workflow integration, and ownership.

Most AI initiatives fail not because the technology doesn’t work, but because success is never clearly defined. Projects are launched out of curiosity, vendor pressure, or fear of being left behind. Clinical impact, operational accountability, and economic value are clarified too late—if at all.

Equally damaging is the underestimation of the human systems AI enters. Healthcare work is relational, regulated, and trust-dependent. When AI is introduced without redesigning workflows, preparing staff, or clarifying responsibility, it creates friction—not relief. Adoption then stalls quietly.

Prediction: In 2026, organizations will run fewer AI pilots—but with much higher expectations. Boards and executives will require clearer evidence of clinical, workforce, or financial value before approving new initiatives.

Recommendation: Move from “fail fast” to “fail before you scale.” Define success upfront, assign ownership early, and redesign workflows alongside technology. AI initiatives without a credible path to value should stop quickly .

Backlash: Fear, Workforce Anxiety, and the Trust Gap

The most underestimated force shaping AI’s trajectory in 2026 isn’t technical or financial.

It’s human.

History offers context. When automobiles first appeared, they were seen as dangerous and socially disruptive. Red Flag laws required people to walk ahead of vehicles waving flags and capped speeds at just a few miles per hour. These laws weren’t about innovation—they were about fear, control, and adjustment.

Healthcare AI is entering a similar phase.

Workforce research shows healthcare workers are among the most cautious about AI adoption, citing concerns about trust, transparency, and job impact. This caution is not irrational. Healthcare has a long history of technology being imposed rather than co-designed.

As a result, scrutiny is increasing—particularly from labor organizations and state legislators. Recent bills, including those limiting AI’s role in clinical decision-making and licensed practice, reflect not anti-innovation sentiment, but unresolved trust and knowledge gaps.

Innovation does not scale without trust.

In 2026, AI scrutiny will intensify, especially with labor organizations and at the state legislative level.

As I write this, the Chair of the New York State Senate Committee on Internet and Technology just introduced a bill (S7263) to “protect patients and front-line care workers from the adverse effects of AI tools in risky or untested settings.” The bill prohibits chatbots from performing the duties of licensed nurses and puts strong guardrails around the use of AI in healthcare settings.”

I often write about the need for a balanced approach to defining both the “gas and guardrails” that guide AI’s use in health and medicine. Incentives and safeguards are equally important.

Prediction : Expect increased legislative activity and labor engagement around AI in healthcare throughout 2026. Such actions should not be dismissed simply as anti-innovation. They reflect something deeper: a trust and knowledge gap that needs to be closed.

Recommendation: Create durable AI value by investing in workforce and consumer education. Clinicians need clarity—not just on how AI works, but on how it supports professional judgment rather than replaces it.

From Awe to Analytical

The year ahead will test leadership resolve. Transformation in healthcare is rarely linear—and never clean.

Vendors will continue to showcase breakthroughs. The hype will continue. But 2026 is not the year for cheerleading.

It is the year for realism.

The most effective leaders are moving from awe to analysis—recognizing that AI value does not come from the technology itself, but from the opportunity it creates to rethink how work gets done.

In that sense, AI value is—and always will be—a uniquely human process.

Hidden Data Errors Delay Healthcare for Millions of Americans

Tue, 18 Nov 2025 17:40:48 GMT

Network inaccuracy isn’t an inconvenience — it’s a public health crisis.

Four out of five provider directory listings in major health plans are wrong.
That bad data drives higher costs, delayed care, and fear for millions of Americans already worried about getting sick.

This isn’t a complex problem to fix.
It’s a neglected one.

Thi s article is worth reading.

Is AI Part of Your HR Plan?

Tue, 11 Nov 2025 20:00:48 GMT

In my keynote presentations to healthcare leaders, one of the questions I always pose is this: Is AI part of your organization’s HR plan?

When it comes to AI, healthcare leaders often overestimate the challenges of technology and underestimate the challenges of people.

Employee resistance and lack of understanding are among the top reasons AI initiatives fail to deliver on their promise. This isn’t a criticism. It’s an acknowledgement that the single greatest question anyone in the healthcare workforce has is this: What does AI mean to me and my career?

That’s why upskilling the healthcare workforce on AI basics isn’t optional—it’s mission-critical.

Here are a few essentials every healthcare leader should consider when building AI fluency across their organization:

✅ Start with awareness, not algorithms. Help staff understand what AI is—and isn’t.

✅ Link learning to purpose. Tie AI education to improving care, safety, and patient outcomes.

✅ Tailor training to roles. A nurse, clinician, and administrator each need different levels of literacy.

✅ Make it continuous. AI learning shouldn’t be a one-off workshop—it’s a journey.

✅ Foster psychological safety. Encourage curiosity and open dialogue about change.

✅ Teach responsible AI. Build fluency in bias, privacy, and ethical use.

AI readiness is strategic—not optional.

And so, is AI part of your HR plan today?

How is your organization preparing its workforce for the age of intelligent care?

What steps are you taking to turn AI fear into AI fluency?

Responsible AI Guidance From the Joint Commission

Fri, 07 Nov 2025 15:38:27 GMT

The Joint Commission and Coalition for Health AI (CHAI) just released the first national guidance (US) on the Responsible Use of AI in Healthcare.

This is a practical, flexible framework designed to help health systems of all sizes govern, validate, and monitor AI responsibly—while ensuring patient safety and trust.

Coming next: AI governance playbooks and a voluntary AI certification program for more than 22,000 accredited organizations nationwide.

This is a significant step forward for provider organizations in the United States seeking a standard, well-vetted approach to responsibly deploying AI.

Go here for more information.

Improving the Patient Experience with AI

Mon, 03 Nov 2025 16:11:22 GMT

I recently did the opening keynote for the annual gathering of the Forum for Healthcare Strategists to discuss the almost unlimited opportunities that forward-thinking marketing and patient experience leaders have to move us from "one-size-fits-all" to a highly personalized and effective experience for every patient and health consumer.

Thank you, Chris Boyer, for interviewing me and allowing me to share my thoughts on AI and strategic marketing in healthcare.

The interview may be found here .

AI Upskilling in Africa - January 2026

Fri, 31 Oct 2025 17:52:18 GMT

I’m excited to be heading to Johannesburg in January to keynote and serve on the faculty for AMLD Africa. Love that this is an event driven by students from Africa and around the world who are dedicated to democratizing Artificial Intelligence across the continent through knowledge-sharing, ethical development, and inclusive innovation for an equitable digital future.

The event is happening on the campus of Wits University January 26-29, and is geared towards students, researchers, startups, industry professionals, policymakers who are interested in shaping an intelligent future for Africa. Go here for more information:

https://mlafrica.org/event/amld-africa-2026/

HIMSS AI Forum Keynote - Review by Medika Life

Mon, 14 Jul 2025 16:47:43 GMT

I was in New York last week to do the opening Keynote for the HIMSS 2025 AI Forum. It was a great international gathering to review and discuss the state of AI in health and medicine.

My keynote for this event focused on how AI is driving fundamental changes in the provision of health and medical services as a backdrop to what I call the "AI Leadership Imperative." Done right, AI is not about technology. It's about EMPOWERMENT. 2025 is the year health and medical leaders must move away from Fear of Missing Out as a motive and put in place the people and processes necessary to use AI to drive value at scale across health enterprises.

For a deeper look at what I covered in my HIMSS talk, GO HERE for a thoughtful review of my session by Gil Bashe of Medika Life.

Commemorating Juneteenth

Thu, 19 Jun 2025 19:33:40 GMT

As we commemorate Juneteenth, let us recognize that, despite decades of progress, systemic disparities persist in who gets care, when, and how. These gaps are rooted in the embedded policies, norms, and practices that advantage some and disadvantage others.

Health care is a noble cause, and it needs our help. I hope you will take a few minutes to reflect on the information I’ve excerpted from my new book, Health Care Nation.

Each of us has the power to make a difference. Health equity isn’t just a moral imperative—it’s a path toward a more just and prosperous future for all of us.

T.

On the Air in NYC to Talk About My New Book

Tue, 10 Jun 2025 20:53:05 GMT

This week, I hit the airwaves on Shake It Off—a talk radio show reaching listeners across the greater New York City area—to share the story behind my new book Health Care Nation.

We didn’t just talk health care. We talked movement building . I believe it’s time for citizens and clinicians alike to raise their voices—not just in frustration, but in reimagining what American health care could be .

If you're ready to challenge the status quo and be part of a smarter, more humane system, give this a listen .

Responsible AI - Free Download for Healthcare Leaders

Wed, 21 May 2025 14:54:28 GMT

Everyone’s talking about Responsible AI. But when it comes to actually putting principles into practice, the follow-through is often inconsistent.

That’s why I’ve adapted a leadership module I use in my advisory work and made it available as a free download. It’s designed to help clinical and operational leaders ask—and answer—three key questions that reveal how well their organization is developing, implementing, and managing AI in ways that truly serve all patients and consumers.

If you're serious about making Responsible AI real, not just rhetorical, this tool is a great place to start.

Go here to download this guide.

MedPage Today Op-Ed

Fri, 16 May 2025 15:16:49 GMT

I have just published an op-ed piece in MedPage Today, which is an excerpt from a chapter in my book, Health Care Nation. In many ways, health care has become America’s largest escape room.

We’ve locked our most talented health care experts and consumers in with a staggering $4.7 trillion of our own money. The problem is that we haven’t figured out how to escape the maze of convoluted policies, skewed financial incentives, and entrenched traditions that are steering amazing people and 17.3% of our Gross Domestic Product (GDP) in the wrong direction.

Go here to learn more.

Las Vegas Talk Show Interview

Tue, 13 May 2025 20:52:15 GMT

Maria Ngo hosts a talk show in Las Vegas called THE STRIP LIVE. She typically interviews celebrities like Tony Bennett, Kevin Costner, and Sir Richard Branson. Needless to say, I was surprised to have a text from Maria wanting to talk when I landed in Las Vegas to speak at HIMSS and a launch event for my new book, Health Care Nation.

Go here to watch this fun interview . Maria brings an energy level to her work that is contagious. We covered everything from the new book, the future of AI, to mentoring advice.

South China Morning Post - Exploring How AI is Changing Healthcare

Wed, 09 Apr 2025 15:52:52 GMT

The South China Morning Post is Hong Kong's largest daily newspaper. This article appeared in the April 9th edition where I discuss how AI is already reshaping healthcare and look ahead to envision how it will improve health on a global scale.

Interview by Health Populi About My New Book Health Care Nation

Thu, 03 Apr 2025 16:54:52 GMT

I had the opportunity to sit down with Jane Sarasohn-Kahn to talk about my new book, Health Care Nation - The Future is Calling and It's Better Than You Think . From defining why the American Health System is going in the wrong direction, to discussing the power of a citizen-driven movement, this review gets at the heart of why I wrote this book. Go here f or our discussion. Go here to bookmark this highly-rated blog reporting on transformation issues and opportunities in health and medicine.

Health Care Nation Launches - Amazon Names as #1 New Release

Mon, 31 Mar 2025 18:50:25 GMT

Friday, March 28th was the official launch date for Health Care Nation-The Future is Calling and It's Better Than You Think . It is now available through all major booksellers. Amazon named it the #1 (Audible Version) and #2 (Paperback Version) New Release in the Health Care Management Category and the #1 New Release in Health Policy. If you are curious, go here to listen to the Preface and Chapter 1.

Special thanks to those who pre-ordered or purchased the book early.

Politics Done Right Podcast - Talking about my new book - Health Care Nation

Mon, 24 Mar 2025 17:17:17 GMT

Egberto Willies is a podcast host and commentator who always tries to tease out the "real story" happening behind the scenes of news today. I had the opportunity to sit with Egberto and talk about why America spends more on health care than any other country, and yet, we as citizens are the least healthy in the developed world and most likely to die early. I covered some of the key issues found in my new book, Health Care Nation.

Go here to listen to our wide-ranging conversation on health care and our ability to reimagine a better use of our talented health professionals and resources.

Dinner with the Real Jerry Macguire

Sat, 15 Mar 2025 16:55:57 GMT

Remember the movie, Jerry Maguire? (Show me the money!). I had dinner last week with Leigh Steinberg…the real Jerry Maguire who was personified in the movie by Tom Cruise. Leigh is a legend in the sports world.

Leigh has been one of the greatest advocates in calling attention to the devastating effects of concussions and brain injuries in sports. From the NFL to pee wee sports, Leigh is the guy who drove visibility and protections for athletes everywhere.

I had the privilege of being on stage at HIMSS25 with Leigh to talk about his great work and what's ahead for the treatment and prevention of concussions and brain injuries, neuroplasticity, and the future of brain health.

T.

Health Care Nation Debuts at Las Vegas Launch Event

Sat, 15 Mar 2025 16:41:43 GMT

Special thanks to my publisher, Taylor and Francis, for organizing a "soft launch" event in Las Vegas last week for my new book Health Care Nation - The Future is Calling and It's Better Than You Think. While the official launch happens on March 28th with all major booksellers, we had advance copies available for sale. It was great fun to do my first book signings. Already getting good feedback from early readers.

A big thank you to early buyers and readers.

For more information on the new book, go to www.healthcarenation.us

The Conversation Americans Should Be Having as the United States Pulls Out of the World Health Organization

Fri, 07 Feb 2025 04:06:27 GMT

Two weeks ago President Donald Trump made waves in the global health community by issuing an Executive Order to pull America out of the World Health Organization (WHO).

Founded in 1948, WHO is an agency of the United Nations whose charter is to plan and coordinate the international response to health emergencies as well as help countries monitor, prepare, and recover from disease threats. While not without controversy, WHO is the most recognized global forum for predicting and planning for events affecting the health of humans across the planet.

Media coverage of the US withdrawal has focused on political rancor (Trump believes WHO mishandled the pandemic) and funding (While the US is one of 194 participating countries, it funds almost 20% of the agency’s $6.8 billion budget). [i]

As the new Administration gives up America’s seat at the table for global health planning, it's important to shine a light on very real issues impacting the health and well-being of Americans. They are worth public scrutiny and debate starting with this statement:

America is a First-World Nation Battling its Own Third-World Health Crises

America’s health care system is the most expensive in the world. It’s staffed with some of the world’s best health and medical talent. Despite this, we are at the bottom of the list in overall health compared to all developed nations. This includes access to care, administrative efficiency, equity, and health care outcomes. [ii]

Americans are among the least healthy people in the rich world and among the most likely to die early.

The richest men in America live longer than the average man in any country. The poorest have life expectancies comparable to men in Sudan and Pakistan . [i]

If you are a citizen of Mississippi, you probably won’t live as long as someone from Bangladesh . [ii] [ iii] [iv]

Maternal mortality rates for American women are worse than in most third-world countries. Even more unexplainable is that Black women are three times more likely to die of childbirth than White women. This gap is worse today than it was when we began keeping records in the early 1900’s. [i]

America is a global leader in avoidable amputations. This is mainly due to the improper management of diabetes, which impacts 38.4 million Americans. [ii]

30 million Americans die prematurely each year from preventable diseases. Twenty-seven percent of US health-care spending goes to managing health conditions that are preventable. [iii]

As the World Health Organization focuses on increasing its investments in global Public Health, it’s important to note that America’s investment in similar Public Health services is declining.

Winston Churchill once said, “Healthy citizens are the greatest asset any country can have.” And so, as we discuss and debate America’s role in creating a healthier world through organizations like WHO, let us actively debate and decide what priorities we will invest in to improve the health of the 330 million people who call America home.

[i] Achievements in Public Health, 1900-1999: Healthier Mothers and Babies, Centers for Disease Control (CDC), Achievements in Public Health, 1900-1999: Healthier Mothers and Babies (cdc.gov)

[ii] NICHOLAS KRISTOF, How Do We Fix the Scandal That Is American Health Care? New York Times, https://www.nytimes.com/2023/08/16/opinion/health-care-life-expectancy-poverty.html?smid=em-share

[iii] Sandro Galea, Nason Maani, The Cost of Preventable Disease in the US, The Lancet, October, 2020, https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(20)30204-8/fulltext
[i] Raj Chetty, Michael Stepner, Sarah Abraham, Shelby Lin, Benjamin Scuderi, Nicholas Turner, Augustin Bergeron, and David Cutler, Income and Life Expectancy in the United States: Executive Summary, The Health Inequality Project, April 2016, https://www.healthinequality.org/documents/paper/healthineq_summary.pdf

[ii] NICHOLAS KRISTOF, How Do We Fix the Scandal That Is American Health Care? New York Times, https://www.nytimes.com/2023/08/16/opinion/health-care-life-expectancy-poverty.html?smid=em-share

[iii] Life Expectancy at Birth by State, National Center for Health Statistics, https://www.cdc.gov/nchs/pressroom/sosmap/life_expectancy/life_expectancy.htm (cdc.gov)

[iv] Life Expectancy at Birth – Bangladesh, World Bank Group https://data.worldbank.org/indicator/SP.DYN.LE00.IN?locations=BD
[i] https://www.msn.com/en-us/politics/government/what-is-the-world-health-organization-and-why-does-trump-want-to-leave-it/ar-AA1xFf0l?ocid=BingNewsSerp

[ii] Mirror, Mirror 2024: A Portrait of the Failing U.S. Health System, Commonwealth Fund, September, 2023, https://www.commonwealthfund.org/publications/fund-reports/2024/sep/mirror-mirror-2024

Australian Talk Tour February 12-21

Wed, 05 Feb 2025 00:29:32 GMT

Excited to be heading to Australia this week as part of a five-city talk tour organized by UBS Australia. They’ve assembled a great lineup of speakers who will be exploring the evolving global landscape in business and health tech. I'm keynoting on what's next for AI.

The cities and dates for the tour include:

Brisbane: February 12

Adelaide: February 13

Melbourne: February 17

Sydney: February 18

Perth: February 20

Along the way I'll also be catching up with some of my favorite AI and digital health experts who are doing great things "Down Under."

Oh yeah… It’s summertime in Australia. Not so much in Seattle.

DeepSeek and the Changing AI Landscape

Tue, 28 Jan 2025 16:20:30 GMT

I’ve been pondering how many journalists and podcasters I’ve ticked off when answering this question: Where will AI be in a year?

My answer has always been simple and honest: No one knows.

This week the Chinese start-up DeepSeek is the latest shift in AI’s tectonic plates. Seemingly out of nowhere, it became the top-rated AI app in the United States.

Deepseek’s new, open-source AI model rivals the abilities of OpenAI's most recent model—with far less investment and using reduced-capacity chips. Training costs for ChatGPT-4 were over $100 million. Deepseek’s investment was supposedly $6 million. Deepseek’s model improves energy efficiency making AI more accessible to more people and industries and could be welcomed news when it comes to AI’s environmental impact.

There’s a lot to be learned about Deepseek’s capabilities. For now, it certainly ups the ante in the AI “space race” for global tech titans and governments.

I can hear the hype machines starting to churn as I write this. Here’s a solid piece from Scientific American that outlines what is known.

And so: Where will AI be in a year? No one knows.

New Book -Health Care Nation

Thu, 23 Jan 2025 20:49:02 GMT

I am pleased to announce that I have a new book coming in April: Health Care Nation - The Future is Calling and It's Better Than You Think.

Whether a patient, health consumer, physician, nurse, health executive, or elected official, somewhere deep in our brains is this simple truth: the American health system isn’t working, and it will only get worse if we don’t do something about it.

Despite spending more money per capita on healthcare than any other country in the world, the U.S. struggles to match other nations in life expectancy, health outcomes and general well-being. Meanwhile, the system spends more on unnecessary, ineffective, and wasteful services than what we collectively invest in K-12 education in America.

All the while, our health status is declining. For the first time, kids born today may not live as long as their older siblings. Health Care Nation shines a light on the deep interconnectedness between the health of people and the health of a nation. It’s about the opportunity and responsibility each of us has to reimagine and reengineer a system that focuses on keeping all citizens healthy and caring for them when they are not.

Health Care Nation takes readers on a journey to understand the fundamental issues driving the system in the wrong direction. It focuses on helping each reader find or sharpen their voice in what should change based on their views, values and experiences.

Health Care Nation awakens readers to the possibilities that exist today that are right in front of us if only we choose to see them. It creates an understanding of the forces at work in healthcare today that are driving us in the wrong direction, instilling readers with a sense of activism that mobilizes them to take action.

The ultimate goal of this book is to help everyone find and use their voice to drive positive change. Health Care Nation is designed to help readers understand the role they can play and actions they can take to determine the health and economic well-being for generations to come.

My publisher is doing an early book launch at the HIMSS conference in Las Vegas March 3-6. Would love to see you if attending. Look for me at the HIMSS bookstore near the exhibit hall. I'll be signing advance copies. Health Care Nation is also available for preorder on Amazon.

For more information about the book go to www.healthcarenation.us .

AI in 2025 - Three Things to Know

Mon, 06 Jan 2025 23:24:23 GMT

With January comes a sea of predictions for 2025. Many are insightful, but if you're a health leader tracking AI developments, here are three emerging themes to pay attention to.

The Great AI Pivot: From FOMO to Value

Since the Fall of 2022, AI hasn’t been just a technological shift—it’s been a cultural phenomenon. Conversations about AI spread from the conference room to the dinner table. Organizations adopted it at breakneck speed, and the fear of missing out (FOMO) drove up to 60% of AI’s recent adoption. One study found that 63% of leaders feared their organizations would fall behind if they didn’t join the AI gold rush.

In the coming year, forward-thinking leaders will pivot from pursuing limited-value AI applications to investing in ecosystems of people and processes that generate scalable, repeatable value (think innovation flywheel). This is a different mindset compared to the approach taken by many leaders in the last two years. It’s a recognition that AI is here to stay and that creating “value-at-scale” requires the adoption of a growth mindset for what’s ahead.

Large Language Models (LLMs) and Gen AI are so 2024

Don’t get me wrong, LLMs and Gen AI will continue generating strong value through a growing array of new use cases that benefit health and medicine. Look for additional upside potential in the next coming years as major AI vendors continue to evolve these models and capabilities.

But here’s the rub, the challenge with these is that they require massive resources, deal primarily with text, and are meant to augment human intelligence rather than take on and execute discrete tasks.

2025’s innovators are already looking beyond them. Smaller, more nimble solutions are stepping into the spotlight. Three in particular deserve attention:

Small Language Models (SLMs):

These models are the sprinters of AI—compact, faster, and built for specific tasks. They don’t require sprawling datasets or extensive computational power. In healthcare, they’re being fine-tuned for specific applications, from analyzing patient feedback to streamlining billing processes.

Multimodal Models:
These AI systems think in symphonies rather than solos. Text, images, and audio weave together into richer insights. They are especially relevant when performing tasks that require understanding across additional modalities.

Agentic AI:
This type of AI exhibits autonomous decision-making, planning, and adaptability, capable of performing finite tasks with minimal human intervention. These models plan, adapt, and operate with minimal human oversight. In healthcare, they can manage discrete tasks and workflows, freeing staff for more nuanced, human-centric activities.

The Intelligence Race: AI in Every Corner of Your Organization

AI is the new “space race” for selling products and solutions in healthcare. Since 2022, healthcare vendors have been scrambling to differentiate their brands and solutions with AI.

As a result, every device and tool, from electronic medical records (EMRs) to the hand sanitizer dispenser at the nurse’s station, is becoming “smart.”

When it comes to generating value the challenge for healthcare leaders is deciphering aspiration from execution.

In 2025, leaders will ask sharper questions. They’ll look for demonstrations that are real and deployable, not sales pitches. Can this AI tool scale across my organization? Does it solve a strategic clinical or operational problem I care about, or is it just a “nice-to-have” add-on? How will I measure the Return on Value (RoV)?

Another layer of complexity AI is driving is in procurement processes.

We will reach a point soon where the majority of AI used in healthcare organizations will be embedded in the major systems purchased or licensed rather than AI solutions that are home-grown or from small niche vendors.

As this occurs, it’s important to adapt your organization’s purchasing, licensing, and auditing processes to reflect this change. A simple question I ask my clients is whether AI is part of their RFI and RFP processes.

Purchasing processes must assess and address how AI is used in any product to ensure patient safety, regulatory compliance, and operational efficiency. AI technologies can introduce risks related to data security, bias, and reliability, which could directly impact patient outcomes. Clear policies help healthcare organizations set expectations for transparency, requiring vendors to disclose how their AI models are trained, validated, and monitored.

Additionally, such policies protect healthcare organizations from potential liability and ensure alignment with ethical standards and emerging regulations. Integrating guidelines such as a board-adopted Responsible AI framework into purchasing and licensing processes reduces liabilities, fosters trust, drives better patient care, and mitigates unforeseen risks associated with AI adoption.

In the coming year, the AI market will continue to change and evolve at a rapid pace. As I’ve written before, this velocity of change requires leaders to think and act differently to help their teams and organizations navigate a choppy sea of change.

May 2025 be a year where foresight, not FOMO, charts your course forward.

Welcome to 2025

Sun, 29 Dec 2024 16:39:02 GMT

Welcome to 2025! I'm hopeful it's the year that we'll move from AI FOMO (fear of missing out) to focusing on driving value at scale in support of our missions and enterprises.

To get started, Deloitte’s 16th annual Tech Trends report is a great quick read. AI is the common thread of nearly every trend. Moving forward, it will be part of the substructure of everything we do.

The report is available here .

Here's to an intelligent new year!

Keynoting APAC's Largest MedTech Conference

Fri, 30 Aug 2024 19:31:18 GMT

Looking forward to being back in Singapore next week to speak at/attend APACMed 2024. Healthcare across Asia Pacific is changing. Consumers are increasingly gravitating towards health organizations that provide greater convenience. This includes the use of digital and AI solutions that allow them to be more involved in managing their health.

Intelligent Aging is Healthcare’s Moonshot

Thu, 28 Mar 2024 01:06:33 GMT

“It's not how old you are, it's how you are old.”

- Jules Renard

It was the summer of 1965 when Medicare was signed into law, guaranteeing that the federal government would manage the provision and cost of medical care for all seniors. In doing so, President Lyndon Johnson proudly declared, “No longer will older Americans be denied the healing miracle of modern medicine. No longer will illness crush and destroy the savings that they have so carefully put away over a lifetime.” ^[1]

As the country’s then nineteen million seniors celebrated, little note was taken of the seventy-six million children who were part of a generation that would come to be known as the “baby boomers.” ^[2] ^[3]

A nation of people once very young is today growing older by the minute. Every 15 seconds, a baby boomer turns 65. Medicare covers 62 million beneficiaries today. This will swell to over 80 million beneficiaries by 2030. ^[4] ^[5] As this tectonic demographic shift happens, there is another essential fact to consider: On average, those 65 and older consume five times more health resources than those under 65. ^[6]

Caring for aging boomers will stress the economic well-being of the working-age population. The number of taxpaying workers per Medicare beneficiary has declined from 4.6 during the program’s early years to 2.9 today. By 2030, this number is projected to be 2.3 ^[7]

The hypergrowth of Medicare beneficiaries multiplied by a 5X consumption factor is problematic. Add medical inflation, an expected staffing shortfall, and a decreasing number of workers to pay for it, and you grasp the magnitude of the problem.

Changing Outcomes by Changing the Model

A paradigm shift is needed to better manage older citizens’ needs and curb rising costs. Leveraging the use of AI, digital tools and other smart technologies across the spectrum of care settings will help address the following:

Reactive to proactive: Today the delivery and payment for health and medical services are based on a “break-fix” model. The introduction and use of intelligent technologies will allow us to proactively focus more on prevention and the overall holistic health of populations rather than episodic and transaction-based treatments.

When it comes to the health and well-being of older people, a big part of what needs to be done is preventing and better managing chronic conditions that can be proactively monitored and better managed with intelligent lifestyle and community-based services.

Intelligent Aging Opportunities

Over the next fifteen years, the number of people 65 and older in the United States will grow by over 50%. ^[8]

This generational shift will be accompanied by a change in technology acceptance among older people. Someone who is seventy today may have first experienced some form of personalized IT in middle age or later, while a fifty-year-old today is far more technology-friendly and savvy. As a result, there will be a growing interest and market for already available and maturing intelligent technologies to support physical, emotional, social, and mental health as we age.

For example, telehealth visits among Medicare beneficiaries increased 63-fold during the pandemic. Equally important, 95% of Medicare beneficiaries were satisfied with their telehealth experience. [9]

Here are other examples of how intelligent technologies will support older consumers:

Ambient Intelligence will become commonplace. Continuous “anywhere” monitoring will provide new and ongoing opportunities to assess and manage the health and wellness of older citizens. Whether through wearables, sensing devices in the home, or embedded in things we have regular contact with like car seats and mattresses, smart devices will gather data that is analyzed by healthcare professionals and/or presented back to the consumer.

Intelligent virtual assistants will be used between human visits to keep people healthy. They will assess and provide individuals with ongoing and real-time intelligent advice. Manually managing and recording daily activities such as nutrition and fitness has always been tedious and difficult. AI virtual assistants will automate the acquisition of deep knowledge of an individual’s diet, exercise, medications, and emotional state.

AI will reduce social isolation for many older Americans and create new healthy connections between friends, family members, and the community. AI chatbots at home will keep people on top of things like taking medications, reminding them of doctors’ appointments, and even scheduling transportation.

New intelligent medical devices and applications will focus on improving the daily living needs of older citizens. AI-powered hearing aids and visual assistive devices will mitigate the effects of hearing and vision loss, enhancing safety and social connection.

As we consider the health, medical and economic challenges of serving this important population, let’s start first by acknowledging and celebrating our successes. Things like public health and medical breakthroughs are allowing more people to live longer than at any point in history. As we celebrate this accomplishment, let us recognize that this success creates new challenges that the existing healthcare system was never designed to address.

Creating a new approach starts with moving away from our traditional views and beliefs regarding aging. Nowhere will this be more important than how we leverage technology to improve the provision of services to manage the health and wellbeing of older citizens.

[1] What Did Medicare Do (And Was It Worth It)?. Amy Finkelstein , Robin McKnight . NBER Working Paper No. 11609. April 2006 http://www.nber.org/papers/w11609

[2] Older Americans 2016: Key Indicators of Well-Being http://www.seniorcare.com/featured/aging-america/

[3] U.S. Census Bureau, Current Population Reports . https://www.childstats.gov/AMERICASCHILDREN/tables/pop1.asp

[4] The Next Generation of Medicare Beneficiaries, MedPac Report to the Congress: Medicare and the Health Care Delivery System. 2015 http://www.medpac.gov/docs/default-source/reports/chapter-2-the-next-generation-of-medicare-beneficiaries-june-2015-report-.pdf#:~:text=The%20number%20of%20taxpaying%20workers%20per%20Medicare%20beneficiary,projected%20by%20the%20Medicare%20Trustees%20to%20be%202.3.

[5] 2021 Medicare Beneficiaries at a Glance, CMS. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Beneficiary-Snapshot/Bene_Snapshot

[6] Lubitz J, Greenberg LG, Gorina Y et al. Three decades of health care use by the elderly, 1965–1998. Health Aff (Millwood) 2001;20:19–32.

[7] Medicare 2021 Trustee Report, CMS, https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/ReportsTrustFunds

[8] Jennifer M. Ortman, Victoria A. Velkoff, and Howard Hogan, "An Aging Nation: The Older Population in the United States: Population Estimates and Projections," Current Population Reports, U.S Census Bureau (May 2014), accessed August 1, 2016, https://www.census.gov/prod/2014pubs/p25-1140.pdf .

[9] Medicare Telemedicine Snapshot, Medicare Telemedicine Snapshot (CMS.gov)

Eyes and AI: Early Detection of Systemic Diseases

Sun, 18 Feb 2024 17:15:46 GMT

While Shakespeare popularized the phrase “the eyes are the window to your soul,” new research suggests that our eyes may also be a window to predicting cardiac, pulmonary, metabolic, and neuropsychiatric diseases.

Physician-researchers from Harvard Medical School, Mass Eye and Ear, Massachusetts General Hospital, and the Broad Institute of MIT and Harvard have found that they can estimate how likely a person is to develop eye and other systemic diseases by using AI to combine retinal imaging, genetics, and big data. [i

]

Retinal imaging is already a commonplace procedure used by Ophthalmologists and Optometrists to evaluate eye health. However, the results of this study suggest its use could be widened. The findings focus on how the thinning of different layers of the retina correlates to an increased risk of developing ocular, cardiac, pulmonary, metabolic, and neuropsychiatric diseases.

Previous studies have shown links between retinal health and health conditions, such as aging, cardiometabolic diseases such as diabetes and hypertension, and neurological diseases such as dementia, stroke, and multiple sclerosis.

Unlike previous studies that searched for genes associated with overall retinal health, this study delved deeper into the role of the different cell layers that make up the retina.

Further research is needed to confirm actual causality, but for now, there is evidence to suggest that retinal imaging might be used in the future to predict and better manage multiple systemic health conditions including poor heart, metabolic, lung, and kidney function.

While eye health is critically important on its own, imagine a time when going in for your routine eye examination could also shed light on other areas impacting your future health and well-being.

The new study uncovers possibilities for preventive medicine and cross-collaboration between ophthalmology and other areas of medicine.

[i] U sing Retinal Images to Predict Risk of Eye and Systemic Diseases, Harvard Medical School News and Research, February 1, 2024, https://hms.harvard.edu/news/using-retinal-images-predict-risk-eye-systemicdiseases

Fixing Healthcare is a Generational Thing

Tue, 16 Jan 2024 22:59:38 GMT

I n 2013, the movie “Her” won the Oscar for Best Original Screenplay. The genius of this sci-fi romance was that it took place in the not-too-distant future when the world would be dominated by Millennials (those born between 1982-1997). The movie’s main character, Theodore Twombly (played by Joaquin Phoenix), falls in love with an intelligent operating system named Samantha. We catch glimpses throughout the movie of a future where the Millennials’ love of intelligent technology is ingrained into every aspect of society.

Fast-forward to the present day. One out of every three adults in America is a Millennial. By 2025 Millennials will make up 75 percent of the workforce. ^[i]

And for the record, there are in fact reported cases of humans ending up in therapy because they fell in love with their virtual assistants. ^[ii]

Millennials and GenZers (those born in 1997 or later) have a love affair with smart technologies. After all, they are first generations to be “digital natives” and do not remember a time when the Internet, social media, and smart apps didn’t exist. As a result, they communicate, shop, and manage all aspects of their lives differently than the generations before them.

When it comes to healthcare, their expectations are no different. They want to schedule and complete a medical consultation from the same place they order dinner—their couch. ^[iii]

The Millennials and GenZers highlight the problems and the opportunities faced by healthcare today. Every generation is different. How we serve them is not. Healthcare today largely follows a one-size-fits-all approach to those they serve even though no two consumers are alike.

The days of providing the same experience to all patients and health consumers are ending. As we learned from the pandemic, a growing array AI and digitally driven apps are changing how healthcare works by making it a more personalized experience.

The future of healthcare will be driven by those who understand and embrace the tenet that optimal health experiences are generational.

Satisfaction with today’s health system varies by generation. Not surprisingly younger generations have the highest levels of dissatisfaction. They give the lowest marks for treatment effectiveness and convenience. ^[iv]

Improving satisfaction levels for all generations comes down to accommodating generational preferences. This means better matching the consumer’s needs with their experiences when interacting with the health system.

Look at something as basic as having a designated Primary Care Physician (PCP) who historically served as gatekeepers to services. A high percentage of older generations have a designated PCP because they grew up believing that all things passed through a “family doctor.” In some ways, the PCP serves as their “app.”

Millennials and Gen Zers grew up in a time of online services, urgent care clinics, and retail health. They are less likely to use a system that requires being tethered to a PCP. 74% would rather see a doctor through telemedicine. And when a situation calls for more than a video chat, they want to avoid a primary care doctor and go straight to specialists and alternative solutions. ^[v]

Providing the same patient experience across the board no longer works. Most consumers still want in-person visits, but younger generations prefer virtual over in-person care. Among Gen Z,

41% prefer a virtual or digital experience with a doctor or other medical professional, along with 33% of millennials. ^[vi]
Almost half of all Millennials trust big tech companies to provide health and wellness services. ^[vii]
Twenty-five percent of consumers are open to seeking and receiving care from brands such as Walmart and CVS.
Even among seniors, more than one in four would consider receiving virtual care from these new purveyors of health services. ^[viii]

Spurred by the pandemic, the health consumer movement will continue to unfold. Successful organizations will offer services better geared towards the lifestyles, preferences, and values of those being served.

Preferences vary by generation, but the overarching trend among all health consumers is the growing use of data, AI, and digital solutions that allow health consumers of all ages to manage health services on their terms.

Consumers today expect intelligent technologies to make health services more effective and personalized. Their preferences are driving the development of AI-enabled, seamlessly connected clinician-patient interactions.

While providing for those who are sick or injured remains important, consumers are also demanding a focus shift from just healthcare to health and well-being. This means more resources (time, money, and attention) will be allocated from the end of the healthcare value chain (treatment and aftercare) to the beginning. ^[i This includes greater focus and investment in promoting healthy lifestyles, vitality, and wellness, primary and secondary prevention, and early diagnosis.

New AI and digitally driven ser vices are connecting consumers to manage health and wellness based on the needs and preferences of each person served. Such services will not replace but rather augment provider teams who can work within more flexible and digitally-enabled care environments to transform services being provided.

This means that the care experience will be more seamless across all care settings. Innovative health organizations are responding with new options like virtual-first health plans and digital front doors.

As we enlist the power of data and intelligent systems to better understand and manage each individual's health, we can personalize the experience to better fit the unique values, needs, and life circumstances of individuals and populations.

A new value chain is emerging around health data that goes beyond the typical data captured and used by traditional health systems.

In the future, consumers will have more access to and control over their data through intelligent digital technologies. As this occurs, the historical dynamics that have benefited Traditional Health Systems will give way to a growing population of informed and empowered health consumers.

Going forward, health consumers will no longer be bound by the processes use d by longstanding healthcare system incumbents. Instead, consumers will create their own personal health management “ecosystems” quite literally in the palms of their hands. They will do this by using cloud-based tools based on their own preferences. This includes clinical preferences such as how they wish to monitor and manage their health and healthcare. It will also allow them to personalize how they manage their health benefits and payments.

As this movement grows, two realities are likely. One is that the change taking place will be driven or facilitated by better use of a variety of data to power intelligent apps and experiences. The second is that fundamental shifts in the current balance of power will occur. Going forward health consumers will increasingly vote with their feet and wallets in seeking out the services that best meet their health and convenience needs.

References Used In this Blog:

[i] Beth Jones Sanborn, 'Digital natives' will lead the healthcare consumer revolution, HealthcareIT News, March 26, 2018, https://www.healthcareitnews.com/news/digital-natives-will-lead-healthcare-consumer-revolution

[ii] XiaoIce robot users have ended up in therapy for falling in love with their Artificial Intelligence, Entrepreneur, August 26, 2021, https://www.entrepreneur.com/article/381966

[iii] Beth Jones Sanborn, 'Digital natives' will lead the healthcare consumer revolution, HealthcareIT News, March 26, 2018, https://www.healthcareitnews.com/news/digital-natives-will-lead-healthcare-consumer-revolution

[iv] Today’s consumers reveal the future of healthcare, Accenture, February 12, 2019, https://www.accenture.com/us-en/insights/health/todays-consumers-reveal-future-healthcare

[v] What Millennials Want When It Comes To Healthcare, MediaPost, December 23, 2016, https://www.mediapost.com/publications/article/291796/what-millennials-want-when-it-comes-to-healthcare.html

[vi] How can Health Leaders Make Digital Health Gains Last?, Accenture, https://www.accenture.com/_acnmedia/PDF-130/Accenture-2020-Digital-Health-Consumer-Survey-US.pdf

[vii] Ibid

[viii] Ibid.

[ix] John Luijs, Mathieu va n Bergen, and Lucien Engelen, The health(care) future of the Netherlands, Deloitte, 2020.w Paragraph

Generative AI and Precision Medicine – The Future is Not What It Used to Be

Tue, 09 Jan 2024 22:59:14 GMT

“When we look back in (the year) 2041, we will likely see healthcare as the industry most transformed by AI."

- Kai-Fu Lee, AI 2041

Generative AI is a new and rapidly emerging form of artificial intelligence that has the potential to revolutionize precision medicine by improving diagnosis, treatment, and drug discovery. It’s comprised of Large Language Models and other intelligent systems that replicate a human's ability to create text, images, music, video, computer code, and more.

So, naturally, when Damian Doherty, Editor-in-Chief of Inside Precision Medicine, approached me last fall about writing an article on Generative AI, the first thing I did was ask the latest version of ChatGPT to provide a 2,800-word manuscript on the opportunities and issues of its application to precision medicine.

The content it generated was relevant, logically organized, and backed up with factual information. Sentence structures were precise and delivered in an easy-to-understand format. There was a formulaic beginning, middle, and end, with the correct provisos stated for being wrong.

The result was quite good, but in the end, it was a little too GPT-ish. There were many things my human brain wanted to know that it didn’t cover or guide me towards.

In some ways, this exercise mirrors the deeper discussions and explorations that are just getting underway to both understand our new and evolving AI capabilities and define a logical pathway to help clinicians and researchers make the practice of medicine more precise.

I’ve had the benefit of working with the application of AI in health and medicine for over a decade. Here are my very human thoughts on what should be considered as we approach this opportunity.

An AI Taxonomy

Generative AI is a relatively new form of AI that has been released into the wild. As such, there are very few experts. This means that we are all early in the journey of understanding what it is and how we apply it to do good.

The chart below provides a simple taxonomy to help differentiate generative AI from other forms of Predictive Analytics.

While there is a great deal of hype over generative AI, there is a growing body of evidence on the things it can do well with humans in the loop: [i]

• Write clinical notes in standard formats such as SOAP (subjective, objective assessment and plan)

• Assign medical codes such as CPT and ICD-10

• Generate plausible and evidence-based hypotheses

• Interpret complex laboratory results

Going forward generative AI will provide benefits in many areas including:

Drug Discovery and Development: Assistance in the discovery of new drugs and their development by predicting molecular structures, simulating drug interactions, and identifying potential drug candidates more quickly and accurately. AI can identify existing drugs that could be repurposed for new therapeutic uses, potentially speeding up the drug development process and reducing costs.

Personalized Treatment Plans: Analyze large-scale patient data, including genetic information, medical records, and imaging data, to guide physicians in the creation of personalized treatment plans tailored to an individual's unique genetic makeup and health profile.

Disease Diagnosis: Assistance in the early and accurate diagnosis of diseases by analyzing medical images, genomic data, and clinical records, helping healthcare professionals make more informed decisions.

Medicine has Been Here Before – Change is Hard

Since medicine came out of the shadows and into the light as a data-driven, scientific discipline we’ve always aspired to be better. The reality is that change is hard. It requires us to think and act differently.

When cholera was raging through London in the 1850’s Dr. John Snow was initially rebuffed when he challenged the medical establishment by gathering and presenting data demonstrating that the root cause of cholera was polluted water rather than the prevailing view that it was caused by bad air. From this came the early stages of epidemiology. [ii]

In the 1970’s the introduction of endoscopy into surgical practice was met with resistance in the surgical community which saw little use for “key-hole” surgery as the prevailing view and practice was that large problems required large incisions. Today, the laparoscopic revolution is seen as one of the biggest breakthroughs in contemporary medical history. [iii]

Generative AI and Large Language Models are part of medicine’s next frontier. They are already challenging current practices across the spectrum of research, clinical trials, medical and nursing school curricula, and the front-line practice of medicine. It’s not a matter of whether it will affect what you do but rather how and when.

With the right dialogue and guidance from a diverse set of stakeholders, we will create a path forward that leverages the benefits of our evolving creations to improve health and medical practices while ensuring that appropriate guardrails are put in place to monitor and guide its use.

It’s Not About Going Slow. It’s About Getting Things Right

In some ways, the challenge of generative AI today is less about increased AI capabilities and more about the velocity of change it is driving.

Generative AI came screaming into mainstream consciousness in the fall of 2022. ChatGPT, a generative AI product from OpenAI, racked up 100 million users in two months. In the history of humans, there has never been a product that has seen such rapid adoption. Shortly after ChatGPT reached this milestone the next version of GPT was released with greatly increased capabilities.

From the practice of medicine to the development of new drugs, generative AI’s “speed of progress” is not following the normal path that economists refer to as linear growth. This is where something new is created that adds incremental value, which then creates a small gap between the time of its creation and when it starts being used. As adoption occurs there is another small gap between uptake and the time it takes for policymakers to develop necessary guard rails to both guide its use and safeguard users from risks. Linear growth is steady and predictable and what clinical and operational systems are set up to manage.

Generative AI is upending linear growth. It’s taking a different trajectory that economists call exponential growth. This is where something increases faster as it gets bigger. Most of our systems are not designed to accommodate this dramatic escalation in change. Exponential growth doesn’t last and eventually, the pace of change returns to linear growth. But when it’s happening it feels like the world is inside a tornado.

The European Parliament approved landmark rules for artificial intelligence, known as the EU AI Act which aims to bring generative AI tools under greater restrictions. This includes generative AI developers being required to submit these systems for review before releasing them commercially. [iv] Here in the United States the Biden administration issued an Executive Order last fall to build momentum within federal agencies and the private sector to put better guardrails in place for the use of AI.

The rapid change driven by generative AI has some calling for measures to slow or even suspend AI development to evaluate its impact on humans and society. A petition from the Future of Life Institute was put forward and signed by leaders including Elon Musk calling for a six-month moratorium on AI development. [v]

While there is uncertainty in what we are creating and how it should be applied, it is unlikely that any mandates will slow the pace of AI innovation.

Instead of attempting to slow progress, let us expedite the education and dialogue among policymakers, medical and research leaders, and frontline practitioners to chart a course for progress in applying our new intelligent capabilities. These groups are also most relevant to ensuring that a necessary set of laws, regulations, and protocols are in place to safeguard those both providing and receiving health and medical services.

The Creation of Enforceable Responsible AI Principles

Let’s recognize and support the overall good that can come from AI innovation. At the same time, we must be mindful of how our ever-expanding AI capabilities can replicate and even amplify human biases and risks that work against the goal of improving the health and well-being of all citizens.

Prioritizing fairness and inclusion in AI systems is a socio-technical challenge. The speed of progress is spawning a new set of issues for governments and regulators. It’s also challenging us with new ethical considerations in the fields of medical and computer science. Ultimately the question is not only what AI can do, but rather, what AI should do.

While legislators and regulators work on finding common ground, health and medical organizations using AI today should have a defined set of Responsible AI principles in place to guide the development and use of intelligent solutions. Most often, these principles or guidelines are reviewed and approved at the highest level of leadership and incorporated into an organization’s overall approach to Data Governance.

AI in Medicine is Not About Technology. It’s About Empowerment

AI has a PR problem. The narrative in the popular press and professional journals is often negative. Headlines like “Half of U.S. Jobs Could be Eliminate With AI,” paint a picture of a future work world dominated by what novelist Arthur C. Clarke calls robo-sapiens. [vi] [vii]

It’s no wonder that people are worried. According to a study by the American Psychological Association, the potential impacts that AI could have on the workplace and jobs is now one of the top issues impacting the mental health of workers. [viii]

Generative AI is already impacting today’s workplace and will be the single greatest change affecting the Future of Work in the next decade. It will impact how all work is done. As you let that statement sink in, recognize that the issues to be addressed go beyond productivity. After all, work brings shape and meaning to our lives and is not just about a job or income.

In this regard, there is growing evidence to suggest that AI can increase not only productivity but also job satisfaction.

In a randomized trial using generative AI, 453 college-educated professionals were given a series of writing tasks to complete. Half were given support with ChatGPT. The control group was not given access to Chat GPT. The results showed that the time taken to complete tasks was reduced by 40% among those using this form of generative AI. Beyond increased productivity, those using ChatGPT reported an increase in job satisfaction and a greater sense of optimism. Most importantly, inequality between workers decreased. [ix]

Done right, AI is not about technology. It’s about empowerment. Properly curated, generative AI will help solve one of the most significant challenges facing healthcare - The shortage of human capital.

The effective introduction and use of generative AI in health and medicine enables both cost-cutting automation of routine work and value-adding augmentation of human capabilities. As it and other forms of AI become pervasive in health and medicine, a new intelligent health system will emerge. It will facilitate systems that improve health while delivering greater value. It will provide a more personalized experience for consumers and patients. It will liberate clinicians and restore them to be the caregivers they want to be rather than the data entry clerks we’re turning them into by forcing them to use systems and processes conceived decades ago.

And while generative AI is coming at us fast with much to understand in how we use it, it could not have come at a better time.

The full article written for Inside Precision Medicine may be found at https://www.insideprecisionmedicine.com/topics/precision-medicine/generative-ai-and-precision-medicine-the-future-is-not-what-it-used-to-be/

References Used in This Blog:

[i] Peter Lee, Carey Goldberg, Isaac Kohane, The AI Revolution in Medicine: GPT-4 and Beyond, Pearson Education, 2023

[ii] Theodore H. Tulchinsky, MD MPH, John Snow, Cholera, the Broad Street Pump; Waterborne Diseases Then and Now, Case Studies in Public Health, March 30, 2018

[iii] Endoscopic surgery: the history, the pioneers. Litynski GS.World J Surg. 1999 Aug;23(8):745-53. doi: 10.1007/s002689900576.PMID: 10415199

[iv] Ryan Browne, EU lawmakers pass landmark artificial intelligence regulation, CNBC, June 14, 2023, https://www.cnbc.com/2023/06/14/eu-lawmakers-pass-landmark-artificial-intelligence-regulation.html

[v] Pause Giant AI Experiments: An Open Letter, Future of Life Institute, March 22, 2023, https://futureoflife.org/open-letter/pause-giant-ai-experiments/

[vi] http://business.rchp.com/home-2/half-of-all-jobs-eliminated/

[vii] Arthur C. Clark, Britannica, https://www.britannica.com/biography/Arthur-C-Clarke

[viii] Worries about artificial intelligence, surveillance at work may be connected to poor mental health, American Psychological Association, September 7, 2023, https://www.apa.org/pubs/reports/work-in-america/2023-work-america-ai-monitoring

[ix] Shakked Noy, Whitney Zhang, Experimental evidence on the productivity effects of generative artificial intelligence, Science, July 13, 2023, https://www.science.org/doi/10.1126/science.adh2586

Genetic Code vs. Zip Code – The Social Determinants of Health

Tue, 02 Jan 2024 20:57:45 GMT

“The future is already here. It’s just not evenly distributed.”

-William Gibson, Futurist

With today’s growing array of AI capabilities and the explosive growth in both the types and quantity of data available to help monitor and manage health, here’s a question: Which is a better predictor of health status – your genetic code or your zip code?

Where you live affects how you live. It impacts whether you have access to healthy food, places to exercise, or health services when needed. Your “living location” also affects your personal and family’s economic prosperity based on the availability of jobs, unemployment rates, educational and training opportunities. These “social” factors shape and determine health and longevity across your lifespan.

Social determinants of health (SDOH) matter when it comes to addressing how we improve the health status of individuals, communities, and nations. SDOH are conditions where people live, learn, and work that affect a wide range of health and quality-of life-risks. ^[i] Whether at the international, regional, state or local levels, the distribution of money, power, and resources shapes these circumstances. [ii]

Here’s an example: Two 60-year-old women live 10 miles apart in the Washington, DC area. They’ve both been prescribed beta-blockers for high blood pressure, have family histories of Type 2 diabetes, and have missed their last few annual check-ups. Shouldn’t their care plans be the same?

Clinically, they’re identical images. However, one piece of data dramatically tilts the equation. Their zip code. One will likely live 33 years longer based on their location. This dramatic life expectancy gap can be chalked up to differences in income, education, and access to grocery stores. ^[iii]

Traditional Health Systems have historically used data to understand the physiologic aspects of a health or medical condition. Such data is important in making diagnoses and managing health, but only shows part of the picture. Social and environmental factors are much more indicative of a patient’s health outcome than once thought. One study suggests that 60% of a patient’s healthcare outcome is driven by their behavior and social and economic factors, 10% by their clinical care, and 30% by their genetics. ^[iv]

Unfortunately, a study by American Health Information Management Association (AHIMA) found that while nearly eight in 10 U.S. healthcare organizations collect social determinants of health (SDOH) data many are not making good use of it because of challenges related to the collection, coding, and use of this clinically relevant data. [v]

The Color of C OVID

Neighborhoods with large populations of Black Americans tend to have lower life expectancies than white, Hispanic, or Asian communities. Such racial differences reflect the places where people live, not the individual characteristics of people themselves. ^[vi]

The early stages of the COVID-19 pandemic gave voice to these issues. At the beginning of the pandemic, the data showed that Black Americans were twice as likely to die from COVID-19 even though they were a smaller percentage of the overall population.

In taking a closer look, two things became self-evident—first, higher death rates related to where people lived. Second, the “twice as likely to die” was a statistical average. Underneath this average was the true story. In reality, if you were Black and living in Washington DC, you were six times more likely to die of COVID at that time. Living in Michigan meant that you were four times more likely to die of COVID. ^[vii]

Black communities are less likely to have access to resources that promote health, like grocery stores with fresh foods, places to exercise, and quality healthcare facilities. This is true even in middle-class neighborhoods . ^[viii] ^[ix] ^[x]

Artificial Intelligence (AI) as a Turning Point

AI gives us the ability to better understand and proactively address social determinants impacting health.

To factor SDOH into h ealth planning, health organizations must first be able to identify consumers facing adverse SDOH. Once identified, such factors can be incorporated into personal health management and population health strategies.

AI can help automate the identification of people whose health is likely impacted by their living situation. Opportunities include adding intelligent features to EMRs and proactive assessments of patient populations. Such activities help to identify and triage at-risk populations and enable organizations to build intelligent workflows for referrals and follow-up.

O ne study found that AI accurately predicted inpatient and emergency department utilization using only publicly available SDOH data such as gender, age, race, and address. ^[xi ^]

AI promises to make it more practical to incorporate SDOH into care management and population health strategies. AI can identify consumers whose health issues are related to SDOH and then help clinicians with targeted interventions to help them better manage their health while maximizing the use of resources.

Understanding and incorporating Social Determinants of Health in health planning is at the heart of moving toward healthier citizens and communities. We are seeing a trickle rather than a stampede of activity to leverage the power of SDOH. What can we do to make this go faster?

For a deeper dive download this free whitepaper from the American Health Information Management Association (AHIMA).

Endnotes:

[i] Centers for Disease Control (CDC). https://www.cdc.gov/socialdeterminants/index.htm

[ii] Outright International at the UN. [ Feb; 2022 ]. 2018. https://outrightinternational.org/content/world-health-organizations-says-being-trans-not-mental-disorder

[iii] Greg Kefer, Zip codes have become a better predictor of health outcomes than genetic codes. Technology may be ready to fix that.Medcity News, August 24, 2021, https://medcitynews.com/2021/08/zip-codes-have-become-a-better-predictor-of-health-outcomes-than-genetic-codes-technology-may-be-ready-to-fix-that

[iv] Shroeder, SA. (2007), “We Can Do Better – Improving the Health of the American People,” NEJM, 357:1221-8

[v] AHIMA White Paper Identifies Opportunities and Challenges with Collecting, Integrating, and Using Social Determinants of Health Data, American Health Information Management Association (AHIMA), February, 2023, https://www.ahima.org/news-publications/press-room-press-releases/2023-press-releases/ahima-white-paper-identifies-opportunities-and-challenges-with-collecting-integrating-and-using-social-determinants-of-health-data/

[vi] U.S. Small-area Life Expectancy Estimates Project: Methodology and Results Summary, NATIONAL CENTER FOR HEALTH STATISTICS, September 2018. https://www.cdc.gov/nchs/data/series/sr_02/sr02_181.pdf

[vii] APM Research Lab. The Color of Coronavirus: COVID-19 deaths by race and ethnicity in the

U.S. Data updated as of June 10, 2020. Accessible via: https://www.apmresearchlab.org/covid/deaths-by-race

[viii] Ibid

[ix] Nicole I. Larson, PhD, MPH, RD Mary T. Story, PhD, RD Melissa C. Nelson, PhD, RD. Neighborhood Environments Disparities in Access to Healthy Foods in the U.S., American Journal of Preventive Medicine. November 03, 2008, : https://doi.org/10.1016/j.amepre.2008.09.025

[x] Rayshawn, Ray, An Intersectional Analysis to Explaining a Lack of Physical Activity Among Middle Class Black Women

Wiley Online Library, September 2014, https://doi.org/10.1111/soc4.12172

^[xi] Soy Chen, MS , Danielle Bergman, BSN, RN , Kelly Miller, DNP, MPH, APRN, FNP-BC , Allison Kavanagh, MS , John Frownfelter, MD, MSIS , John Showalter, MD , Using Applied Machine Learning to Predict Healthcare Utilization Based on Socioeconomic Determinants of Care. The American Journal of Managed Care, January 2020, Volume 26, Issue 01. https://www.ajmc.com/view/using-applied-machine-learning-to-predict-healthcare-utilization-based-on-socioeconomic-determinants-of-care