Over time, it becomes evident that the decisions made in boardrooms carry their greatest weight in those very moments. It would take years to understand it fully, but these moments were not isolated. They were the foundation for something I would later try to give voice to.

The Day the Ordinary Disappeared

In January 1975, I was traveling through Paris on my way to the United States. What should have been a routine journey became something else entirely. Terrorists fired two RPG shells at our plane. They missed us but struck a Yugoslav Airlines JAT aircraft on the tarmac nearby.

The randomness of it all was almost impossible to process. One moment, you are a traveler moving through the world, the next, you are told to hug the floor of the aircraft, confronted with how easily that world can be altered or taken away. I did not have the language for it then; however, I carried the feeling forward. Life is not guaranteed. It is a gift given to us to deploy.

In 1978, I was leading the first Think Tank Peace Mission to Egypt and Israel. There were no direct flights between the two countries. From Cairo, we flew to Cyprus, then to Tel Aviv.

An Air Cyprus flight had landed just before ours. It was overtaken by terrorists. An Egyptian Entebbe-like rescue was attempted. It failed. When we landed hours later, the aftermath was still there — the remains of the Egyptian military C-130 sat on the tarmac, destroyed and covered. It reinforces the adage, “that timing is everything.”

You do not process it fully in the moment. You carry it. An appreciation for what lies beyond our control. A respect for those who act with purpose, regardless of outcome. An understanding that we plan for the future, yet we live in the moment.

Years later, during my military service as a paratrooper and combat medic, that lesson was no longer abstract. It was immediate, urgent and often unfolding before me. I served six frontline combat tours in Lebanon, in places where the noise of conflict was constant and the margin between survival and loss was measured in inches.

I tended to friends and foes under fire. In those moments, there was no room for theory. Care was not a matter of courage or a concept; it was an instinctive action. Communication was not a strategy; it was survival. A word, a look, a clear instruction could steady someone, guide them and save them.

Where Care Is Action, Not Theory

War has a way of stripping away everything except what matters most. You see clearly how dependent we are on one another. You understand that courage is not the absence of fear; it is the determination to act despite it. You learn that presence, simply being there for another person in their most vulnerable moment, is one of the most powerful forms of care.

I thought I understood risk. I thought I had come to terms with uncertainty. Then life reminded me again.

On a flight to visit my parents in the United States, the Tower Air jet I was on caught fire over the Atlantic. Two engines on the left side were burning. We needed to find a place to land quickly or hit the ocean. There is a particular kind of silence that fills a plane in that moment. It is not panic. It is something deeper, more introspective. You feel time stretch. You think about the people you love. You consider what has mattered and what has not.

As we made our emergency landing in Gander, Canada, I remember not relief first, but reflection. Once again, life had placed me in a moment where its fragility was undeniable.

These experiences did not turn me away from the world. They pulled me closer to it. They shaped how I see people, how I listen and how I respond. They taught me that every interaction carries weight, that every conversation can matter more than we realize.

In recent years, I have traveled to Ukraine annually before and during COVID and now during the war, supporting friends and spending time in a small community facing circumstances most of us can only imagine from afar. There, I saw the same truths I had encountered earlier in life. Community becomes everything. Information becomes lifeblood. People look to one another not only for physical support, but for clarity, reassurance and meaning. Even in the darkest conditions, communication is not secondary to care. It is part of care.

Most in the business world know me through my work at FINN Partners as a health communicator, through my writing, speaking and advocacy as a champion of health innovation and a more human-centered health system. They see my professional journey. What they do not always see is the foundation beneath it. Decades of lived experience that have reinforced, time and again, that life is precious, that it can change in an instant and that how we show up for one another in those moments defines us.

At FINN Partners, I have found a community of colleagues who reflect these same values. There is an understanding that our work carries responsibility, and that we are capable of more when we challenge ourselves to rise to it. It is a culture that encourages each of us to think beyond the immediate and contribute to something more enduring.

That understanding became even more personal through my family. My wife and I have walked alongside our child as she navigates the complexities of a rare disease. There are highs and there are lows. There are moments of hope and moments of uncertainty. In those experiences, I have seen health care from another vantage point, not as a cohesive system, but as a series of human interactions that can either comfort or compound the challenge.

When you are a parent in those moments, you listen differently. You look for clarity in every word. You hold on to empathy when it is offered and you feel its absence when it is not. You come to appreciate that communication in health is not an accessory. It is essential. It shapes understanding, trust and the ability to move forward.

The Human Thread Through Every Moment

All of these experiences converge into a single, enduring belief. Communication is not separate from care. It is how care travels along its continuum. There are moments when that truth reveals itself outside the settings we expect.

On a transatlantic flight in 2001, turbulence turned severe. At one point, a call came over the intercom: “Are there any doctors aboard?” No one responded. Minutes later, the request broadened to “any health professionals.”

My wife looked at me and quietly suggested I press the call button.

I was escorted to a passenger, pale and wrapped in a blanket. He had lost and regained consciousness. I introduced myself warmly and began with simple questions to assess his awareness. His name. The President of the United States. The day we had taken off. He answered each one without hesitation. His vitals were stable.

I explained that I was not a physician, but a former military EMT. Given the turbulence and the length of the flight, dehydration and stress were likely contributors. I reassured him and suggested that he follow up with his physician upon landing and, if he needed me, not to hesitate to hit his call button.

As I returned to my seat, a man two rows behind called out, “I’m a neurologist. I would have handled that exactly as you did.”

It was meant as an affirmation. I received it that way. Yet it lingers differently. In that moment, the instinct to act had been replaced by the comfort of waiting. The systems we build, even when grounded in expertise, can condition us to hesitate when action is needed most.

In moments like these, care is not a title or a credential. It is the willingness to engage, communicate, and act.

Across the health ecosystem and in responsible business settings, success is often measured by growth, scale and financial performance. These are necessary markers of progress. They enable innovation, access and reach. However, there is a deeper measure that often goes unspoken. When we understand our role within the continuum of care and recognize the connection between balance-sheet decisions made in boardrooms and people’s experiences felt at the bedside, our work takes on greater meaning. It moves beyond what can be counted to what ultimately counts.

Over time, I came to understand that moments are not separate. They are connected. Each one revealing, in its own way, what happens when people are seen, heard and cared for, and what happens when they are not.

That understanding became Healing the Sick Care System: Why People Matter.

A life of observing, listening, engaging and caring was the kindling. The moments themselves were the spark. Together, they revealed a simple truth: when we lose sight of people, the system falters. When we honor them, it begins to heal.

That truth asks something of us.

It is not simply about words. It is about presence. It is about accountability. It is about the choice to act when action is needed. This is how humanity shows up in systems, and how those systems, in turn, earn the trust of the people they are meant to serve.

The post The Moments That Shape Us: Why Life and People Matter Most appeared first on Medika Life.

Suicide remains one of the leading causes of death in the United States, with young people particularly affected. These are not abstract figures. Each life lost represents a story interrupted, a family altered, and a community left to navigate grief and unanswered questions. Public health requires that we confront this reality not only with data, but with a commitment to building systems that respond to human experience in real time.

From Fragmentation to Continuity Across the Lifespan

For many years, suicide prevention in the United States has been shaped by dedicated organizations working across research, advocacy, education, and crisis response. The American Foundation for Suicide Prevention has played a central role in advancing scientific understanding, funding critical research, and advocating for national policy changes that recognize suicide as a preventable public health issue. Its work has helped elevate awareness, influence legislation, and bring suicide prevention into mainstream health conversations.

The Jed Foundation has taken a complementary path, focusing on upstream prevention by strengthening emotional health among adolescents and young adults. Through partnerships with high schools, colleges, and universities, JED has worked to embed mental health support within the environments where young people live and learn. Its programs have helped institutions move beyond reactive approaches toward more proactive models that build resilience, identify risk earlier, and foster a sense of belonging.

Each organization has demonstrated meaningful impact over time. Each has contributed to saving lives and shaping how mental health is understood. Their efforts, however, have largely operated within distinct domains. One has advanced national research and advocacy. The other has transformed youth and campus mental health systems. Both have addressed critical points along the continuum of care, yet the broader system has remained fragmented.

The decision to merge as equals reflects a recognition that suicide prevention cannot be addressed in silos. Public health challenges of this magnitude require continuity across the lifespan. Early emotional support, community-based intervention, crisis response, and long-term recovery must function as part of an integrated system rather than a series of disconnected efforts.

Connection, Not Scale Alone, Defines Public Health Impact

Public health is often described through infrastructure and policy. Those elements are essential, yet they are insufficient on their own. Public health is ultimately about connection. It connects evidence to action, systems to individuals, and care to lived experience.

Suicide prevention sits at the intersection of these connections. Risk is influenced by social conditions, access to care, stigma, and the environments in which people interact. Protective factors such as trusted relationships, purpose, and community support can alter outcomes when they are present and accessible. The challenge has not been a lack of understanding. The challenge has been delivering that understanding in ways that are coordinated, equitable, and sustained.

A unified organization has the potential to bridge long-standing gaps. It can align research with real-world application, ensuring that scientific insights inform programs that reach people earlier. It can connect youth-focused interventions with broader public awareness efforts, creating continuity rather than gaps as individuals move through different life stages. It can also strengthen advocacy by bringing together complementary perspectives into a more cohesive national voice.

Scale introduces both opportunity and responsibility. A larger organization can mobilize resources, influence policy, and expand reach. Public trust, however, is built in local and personal interactions. The effectiveness of this merger will depend on its ability to maintain proximity to individuals and communities while expanding its national impact. Size alone does not create connection. Intentional design does.

The combined organization is expected to operate with substantial resources, which creates an opportunity to accelerate progress. Resources must translate into accessible programs, stronger partnerships with schools and health systems, and tools that enable families, educators, and clinicians to act with confidence. Public health systems succeed when they reduce friction for those seeking help and make support visible before a crisis emerges.

This moment also offers a broader lesson for the health sector. Fragmentation is not unique to suicide prevention. Across chronic disease, health equity, and digital health, organizations often operate with shared purpose but limited alignment. The willingness of these two organizations to merge reflects an understanding that structural change may be necessary to achieve meaningful outcomes.

The integration process will require thoughtful leadership and a clear sense of purpose. Combining cultures, programs, and strategies requires discipline and humility. Success will not be measured by organizational scale or visibility. It will be measured by whether fewer individuals reach a point of crisis without support and whether more people experience a system that feels connected, responsive, and human.

Suicide is often described as preventable, which places responsibility on the systems designed to address it. Prevention requires more than awareness. It requires intentional coordination, early recognition, and sustained engagement across the continuum of care.

This merger does not resolve the complexity of suicide prevention. No single organization can. It does represent a meaningful step toward greater alignment in how society responds to one of its most pressing public health challenges. Connection is not an abstract ideal in public health. It is the foundation upon which progress depends.

For more information about both organizations, visit these organizations’ websites at afsp.org and jedfoundation.org. 

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Unfortunately, the system has frequently failed to live up to that ideal. I learned that from having a conversation with Matthew Zachary, CEO of We the Patients, a patient advocacy organization. In a recent LinkedIn post, in fact, Mr. Zachary wrote this:

Prior auth takes longer than the time between scan and surgery. Drugs get denied because someone flipped a spreadsheet cell from green to red. Surprise bills show up because the hospital was in network but the anesthesiologist’s LLC was not.

None of this is a glitch. This is the product working exactly as designed. Built to maximize profit and gaslight us into believing WE are the problem for not “navigating” it better.

This is horribly unfortunate, and Matthew Zachary is harnessing his anger at this reality to make a difference through his activism.

There are indeed a lot of problems with the current healthcare system, and fixing them will take a lot of time, effort, and work. And there is one thing we physicians can do to immediately help make things better for the patient: make an intentional effort to overwhelm our patients with compassion.

No one wants to be sick. No one wants to willingly engage with the healthcare system. And when they do, it is because there is a threat to their life and limb.

With the way the current insurance system is set up, it is not uncommon that patients face myriad barriers and pain points to get the care they need. I myself have experienced these barriers and pain points with my own healthcare and that of my family. It can add more stress to an already extremely stressful situation.

How can we help mitigate this stress? Overwhelm our patients with kindness and compassion. Give them a big smile; hold their hand; tell them that we will do everything to help them feel better.

And if they will not get better; if our patient is going to die, then we need to do everything in our power to ensure a death with dignity, comfort, and ease.

Aren’t we supposed to be doing this all along? Most definitely. And, as is the norm of the human condition, we tend to forget amid the drudgery of the day in and day out of working in healthcare and dealing with the very same barriers to care and pain points with which our patients are also dealing.

That’s why I’m so grateful for Matthew Zachary. He has the courage to share his incredible story of illness and recovery and his anger at the system that did not help promote his healing to try and do something about it.

And his story, and his activism, was a potent reminder for me to do all that I can to make my patients in the ICU as comfortable as possible, to make them feel as good as a critically ill person can possibly feel. Will I fail at times? Yes. But I pray that, for the rest of my career, I will keep trying to overwhelm my patients and kindness and compassion. That’s what I can do to help the healthcare system today.

Listen to the entire conversation: https://www.healthcaremusings.com/we-the-patients-are-really-pissed-off-my-conversation-with-matthew-zachary/

The post How Every Doctor Can Improve The Healthcare System Immediately appeared first on Medika Life.

Early in the book, Nosta writes, “The solved can never touch the whole.”  That line lingers. It captures the essence of his argument. AI can solve, generate, synthesize, and accelerate. Yet something about the human experience of thinking, the struggle, the friction, the meaning-making, exists beyond resolution.

This tension defines the book. It is not anti-technology. Nosta is deeply engaged with AI and candid about its value. He describes large language models as tools that “move faster and connect more disparate concepts than our minds could ever manage on their own.”  He is equally clear that this capability introduces a subtle risk. We may begin to outsource not just tasks, but thought itself.

That distinction matters more than many may be willing to admit.

From Tools to Thought

One of the most compelling contributions of The Borrowed Mind is its framing of AI not as the next step in computing, but as a turning point in cognition. Nosta traces a clear arc. Gutenberg unlocked words. Google unlocked facts. AI, he argues, is unlocking thought. 

That progression is elegant, yet also unsettling. Words and facts could be externalized without fundamentally altering the structure of human reasoning. Thought is different. It is intimate. It is identity. It is how we become.

Nosta reminds us that thinking once required effort, a type of natural friction that created sparks of innovation. “The distance between question and answer created space for our discernment.”  Within that space, judgment formed, curiosity deepened, and understanding took root.

AI compresses that distance. It removes friction. It delivers coherence with remarkable speed.  One of the book’s most important insights emerges here. Coherence is not the same as understanding.

Nosta introduces the concept of “anti-intelligence,” describing it as “fluency without understanding. Coherence without experience.”  AI does not think. It mirrors the structure of thinking. It produces language that resembles reasoning without sharing its origin.

In health, where evidence, interpretation, and judgment must coexist, this distinction is not academic. It is operational. It shapes how clinicians trust tools, how leaders deploy them, and how patients ultimately experience care.

The Seduction of the Socratic Mirror

One of the most original sections of the book is Nosta’s description of the “Socratic Mirror.” He draws a parallel between classical dialogue and modern AI interaction. Socrates asked questions to surface the truth. AI, in a different way, reflects our thinking back to us, reframed, extended and sometimes clarified.

Nosta writes that the model “…does not tell me what to think but creates the conditions under which my own thinking could deepen.” This is where the book moves beyond critique and into possibility.

Used well, AI becomes a cognitive partner. It expands perspective, accelerates exploration, and invites iteration. In clinical research, patient engagement, and system design, this capacity holds enormous promise.

Nosta does not romanticize the relationship. He recognizes its asymmetry. The model has no interior life. It does not ponder. It does not carry consequence. It does not bear responsibility. That responsibility remains human.

Rethinking the Fear of Displacement

A persistent anxiety runs beneath every conversation about AI. Many fear it will become a job slayer, a force that displaces rather than elevates human contribution. That concern is understandable, yet not new.

Every meaningful advance in technology has reshaped how people work. The wheel did not eliminate labor. It redefined movement. The stethoscope did not replace physicians. It extended their ability to listen and interpret. The tollbooth transponder did not end transportation roles. It changed the flow and focus of human involvement. Each innovation shifted roles, demanded new skills, and expanded what people could do.  AI belongs in that lineage.

What distinguishes this moment is not the elimination of work, but the redistribution of cognitive effort. The real risk is not that machines will think for us, but that people may become less inclined to think for themselves. Nosta’s warning is subtle yet profound. Surrendering curiosity, judgment, and reflection to systems that generate answers with ease risks dulling the very faculties that define human intelligence.

This is why The Borrowed Mind is such an important read at this moment. It does not dismiss concerns around job displacement. It reframes it. The central challenge is not protecting roles as they exist today, but strengthening the uniquely human capacities no system can replicate. Creativity, discernment, ethical reasoning, and the ability to navigate ambiguity are not diminished by AI. They become more essential.

The book offers reassurance without complacency. The future of work will favor those who sharpen their thinking, engage deeply with ideas, and remain active participants in their own intellectual development. The machine is not the adversary. Neglecting the development of one’s own mind is a danger.

Composite Intelligence and the Limits of the Machine

Nosta introduces “composite intelligence” to describe the interaction between human and machine cognition. Composite does not mean blended into sameness. It means distinct contributions working in concert. The model brings speed and breadth. The human brings depth.

This triad becomes one of the most useful frameworks in this book. AI excels in velocity and scale. Depth, the slow transformation of understanding, remains human. As Nosta writes, “Models do not ponder.” 

In health, this distinction is profound. Data can inform. Algorithms can suggest. The act of deciding, especially in moments of uncertainty, requires something more. It requires what Nosta elevates as the defining human contribution. Virtue.

Drawing on Aristotle’s concept of practical wisdom, Nosta reminds us that judgment is forged through experience, consequence, and accountability. A model can generate options. It cannot live with outcomes.

This is where the book resonates most deeply for those working in health. Intelligence is becoming abundant. Discernment is becoming scarce and, therefore, more valuable.

The Risk of the Borrowed Mind

The book’s title is not metaphorical. It is a warning. Nosta argues that as engagement with AI deepens, internal dialogue begins to change. The model becomes a cognitive tuning fork, subtly shaping how questions are framed, how ideas are explored, and how answers are anticipated. This dynamic is not inherently negative. It can elevate thinking, accelerate learning, and make complex domains more accessible. Dependency remains the concern.

Reliance on generated thought risks weakening the muscle of original thinking. Access can be mistaken for understanding. Individuals may become, in Nosta’s words, “cognitive clones.” 

This concern is particularly relevant in health ecosystems already strained by time, complexity, and administrative burden. The temptation to offload cognitive work will be strong. The discipline to remain intellectually engaged will be essential.

A Book About AI That Is Not About AI

What makes The Borrowed Mind stand apart is that it is not ultimately about technology. It is about humanity. Nosta writes, “This book is not really about technology. It is about you.”  That idea anchors this work.

Readers are challenged to consider what it means to remain “the authors of our own minds.”  Not passive recipients of generated insight, but active participants in meaning-making.

This question sits at the center of the health ecosystem’s future. As AI becomes embedded in clinical workflows, research, and patient engagement, the issue is not whether it will improve efficiency. It will.

The deeper question is whether it will deepen humanity or dilute it. Will it create space for clinicians to think more deeply, connect more meaningfully, and act more wisely? Or will it create a system that values speed over reflection, output over understanding, and coherence over truth?

Nosta offers no simple answers. He offers a framework for asking better questions.

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I’m always surprised that the LSHTM gives me the privilege of returning to talk about the shifting landscape of funding and how to help assure that it is spent well and to benefit Africa’s future. As I met the Zoom room full of bright, engaged students (many of whom are living the challenges of adequate funding daily in countries such as Uganda, Nigeria, Kenya, and Cameroon) I was struck by how fast the familiar old world of advocacy died, and how urgent it is that we build a new one.

My perspective is shaped by 35 years as a policy and communications consultant working across the continent. I have seen the era of the “Great Man” advocacy, where we simply tried to bend the ear of a US President or a billionaire philanthropist. We look back at those days with rose-tinted glasses: the billionaires and rich-country leaders were fickle and their focus was often on getting recognition or a seat at the top table, not on the real need. Even when they did try to assess the real needs, it was usually through the uninformed eyes of over-priced management consultants whose only knowledge of Africa came from airport VIP lounges. The billionaires were also shockingly bad at effective advocacy for something as obviously cost effective as health spending.

In any case, those days are over. If we want to secure the future of health in Africa, our work to influence policy must evolve to meet a much harsher, more complex fiscal reality.

The Shifting Foundation of Global Health Funding

We have seen a fundamental failure in advocacy around health funding. The data released by the OECD reveals a stark trend: the era of expanding bilateral aid is ending. Total Official Development Assistance (ODA) is contracting, and 96% of that decline is driven by just five donors: Germany, the UK, Japan, France, and most significantly, the USA.

The US alone is responsible for three-quarters of the global decline in health funding. While Germany has technically become the largest provider of ODA for the first time in history, even it is cutting budgets, albeit in an attempt to become more efficient. Meanwhile, traditional multilateral ODA, money flowing to the WHO or the World Food Programme for example, is shrinking less than bilateral grants, but the overall pie is getting smaller.

The good news is that the World Bank and regional development banks such as the African Development Bank (AfDB) are stepping in to fund some health projects. There are questions over “additionality”: are these institutions really funding things that private equity or other lenders to states would not? And there are frequent criticisms that the banks have failed to create funding buckets for innovative models such as low-cost private-sector primary care. However, there are real successes. The AfDB in particular has said loudly and clearly that economic growth depends in large measure on better health and has encouraged governments and funding agencies to invest accordingly.

The Rise of the America First Bilateral Accords

US funding has not disappeared: it has shrunk and mutated into the America First health policy. This administration is moving away from broad global initiatives toward strict bilateral health accords between the US and individual African countries. These are not just funding agreements; they are ideological and strategic contracts that come with significant strings attached.

Under these accords, the US makes a five-year commitment with a clear “exit strategy”: funding is front-loaded but tapers off to zero, forcing national governments to take on “ownership.” While national ownership sounds positive, the requirements are often demanding.

The focus is what you would expect from an administration with an ideological focus derived from Project 2030. It is on maternal and child health (and, yes. The State Department often says that it is the health of children “born and unborn”) and infectious disease.

These accords also require African countries to share pathogen data and specimens with the US within five days of an outbreak. This creates a parallel data mechanism to the WHO and, more importantly, seeks to capture what one of the post-graduate students called, “the new oil.” Africa holds 80% of humanity’s genetic diversity. In an era of genetic medicine, this data is a massive national asset. Several students at LSHTM rightly pointed out that countries like South Africa and Kenya see this as a key resource to be traded for R&D investment, not just given away for a few years of HIV funding. Africa is also developing national health databases that can be used to assess and model the impact of interventions and, as when the continent pioneered payments from mobile phones, it is less encumbered with antiquated existing systems and threatened vested interests.

Most alarmingly to me, these accords are sometimes tied to non-health issues. We’ve seen Zambia refuse to sign because the US tied HIV funding to access to critical minerals and mining data.

One Path Forward: the Accra Reset

The Accra Reset sets out to be a roadmap for this new era. It aims for 55% of health spending to be domestic by 2030, funded in part through “sin taxes” on sugar-sweetened beverages and tobacco. Other means of national funding include surcharges on profitable data transactions and health solidarity funds. Its organisers say that these taxes will raise £750 million in 2026 in six countries alone. I think that’s a high estimate, but there is real money there.

The Accra framework is, though, delusional in thinking that out-of-pocket health can be reduced over the next five years. The AfDB projection is that the private health market in Africa will explode. This is not necessarily bad news for health equity: much of the growth will come in highly efficient fixed-cost private primary care models targeted to working people (although, admittedly, rarely to the bottom of the pyramid or the working poor). These models can be valuable ways to give fast access to innovation and convenient, timely provision of sexual and reproductive health services.

Recommendations for the New Advocate

Given this backdrop, I suggested that these elite advocates do the following.

1. Make Health Explicitly Political

We often hear that health should be non-political. This is a mistake. Non-political subjects are boring and ignored. We need health to be the subject of election campaigns, impassioned debates and social media memes. When health becomes a political must-have, politicians make promises they can be held to. We want people shouting about health in the streets of Accra, Nairobi, and Lagos.

2. Frame Health as a Capital Asset, Not a Cost Centre

We must stop arguing for funding based solely on morality. We need to speak the language of Finance Ministers. According to the World Bank and the AfDB, health is a growth engine.

• ROI Data: For every $1 spent on malaria treatment, the economy gets $35 back. For paediatric immunisation, it’s $20. For SRHR, the returns are less often quantified rigorously but similarly massive because they enable women to enter the workforce and stay productive.
• Preventative Care as Infrastructure: Just as investing in robotics improves productivity, investing in the health of a citizen from birth to age 65 creates a stock of human capital that belongs on a national balance sheet, as the World Bank has now recognised.

3. Build Alliances with FBOs

Faith-Based Organisations (FBOs) provide roughly 30% of healthcare in Africa. The America First plan prioritises them, in part because it plays well to US domestic audiences and, in part, because they are efficient and embedded in communities. While we may disagree with some FBOs on abortion or family planning for unmarried youth, they have incredible national reach. As one student noted, a Pentecostal church in Nigeria aiming for a branch every 15 minutes of walking distance is a more powerful delivery network than any government programme. We must engage them to improve quality and advocate for rights within their frameworks.

4. Harness the Power of Media and Social Media

We can’t forget about media, especially in Africa where so many people are still dependent entirely on TV and local radio and where online and offline newspapers are declining less slowly.

Increasingly, though, we must go where the people are — which is social media. During the lecture, students raised concerns about medical influencers spreading misinformation or misogyny. My response: then we must flood the zone. We need to train responsible influencers. When Joe Fazer, a bodybuilding influencer with about 30 million followers produces content about health equity, he can mobilise a generation we will never reach through traditional policy papers.

Overall, we are in a time of great opportunity and serious danger. The transition from aid to co-investment is the only way to escape the whims of Washington or Berlin. We must be like the “trained revolutionaries” Lenin spoke of — professionals who know how to stir up movements and demand that our governments prioritise health not because a donor asked them to, but because their own citizens demand it.

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Health systems are not stepping into artificial intelligence from a place of calm or control. In the United States, spending now exceeds $4.5 trillion, with a significant share tied up in administrative work that adds complexity more than clarity. Clinicians are caring for more patients, navigating more data and making more decisions under pressure than ever before. The system is stretched. Artificial intelligence is entering at a moment when change is no longer a choice.

The discussion drew on the experience of three leaders who are not observing this shift. They are guiding it. Hal Wolf leads HIMSS, influencing digital health policy and implementation across more than 100 countries. Isaac Kohane, MD, PhD, Chair of Biomedical Informatics at Harvard Medical School, has spent four decades defining how data informs clinical care. Ran Balicer, MD, Chief Innovation Officer at Clalit Health Services, operates within one of the world’s most integrated health systems, where data and care are aligned across generations.

These are not just star panelists. They are system-wide architects.  What emerged from the hour-long conversation was not what artificial intelligence can do. It was a recognition that it is already doing more than most systems are prepared to guide and govern.

Dr. Kohane captured the tension immediately. “I think that we have to worry about the fact that we’re going both too slow and too fast.”

That statement reflects a reality many leaders feel but rarely express. Governance takes time because it must. Patient safety, validation and accountability require structure. Practice moves in real time. Clinicians do not have the luxury of waiting for perfect systems.

“They’re so desperate to do right by their patients to use other resources,” Dr. Kohane adds.

That instinct is not a weakness. It reflects a commitment to doing what is right for the patient. When clinicians turn to external AI tools, they are seeking clarity, speed, and confidence in their decisions. Artificial intelligence is already present at the point of care, shaping how physicians assess information, validate thinking, and move forward. The system is not adopting AI. The system is catching up.

This creates a condition that is difficult to measure and even harder to manage. Different clinicians use different ChatGPT platforms. Those tools produce different answers. Different assumptions shape those answers. Over time, consistency erodes. The system begins to operate with multiple definitions of truth (and the risk of varied outcomes).

Dr. Kohane’s warning is not about misuse. It is about misguided permanence. “The worst outcome will be if the worst parts of medicine get concrete poured over it, by AI.”

Artificial intelligence does not fix a system; without leadership, it accelerates the integration of incorrect assumptions. If workflows are inefficient, they become more efficiently inefficient. If bias exists in data, it becomes more precise. If fragmentation defines care, it scales.

This is not a failure of technology. It is a mirror held up to system-wide leadership.

Hal Wolf, among the health sector’s leading policy and operational voices, grounded this moment in proven experience. Health care has seen this pattern before. When internet connectivity entered hospitals, clinicians moved faster than governance. They created access where it was needed. Systems responded later. Risks were discovered after adoption.

Artificial intelligence now follows that same trajectory, though at far greater speed and with far greater consequences. Web connectivity gave quick access to information. Artificial intelligence influences how that information is interpreted and acted upon.

“We have to go faster,” Mr. Wolf said. “But there needs to be structure around it.”

That is the leadership challenge of this moment. Speed without structure creates exposure. Structure without speed creates irrelevance. The tension between the two is not something to resolve. It is something to manage continuously.

The industry has predictably responded to artificial intelligence. It has started where risk is lowest and return is clearest. Documentation, scheduling and revenue cycle optimization have become the entry points. These applications reduce burden and improve efficiency. They are necessary. However, they are not transformational.

The shift occurs when artificial intelligence moves into clinical decision-making. At that point, the question is no longer whether the system works. The question becomes whether it should be trusted.

Who owns a decision informed by an algorithm? How is accuracy validated? What happens when a clinician disagrees with a recommendation? These are not technical questions. They are questions of accountability. Artificial intelligence does not assume responsibility. It does not carry consequence. That remains with leadership.

Dr. Balicer reframed the conversation, shifting how the room thought about artificial intelligence. “There’s no such thing as AI neutrality. Algorithms are just opinions embedded in code.”

That insight is easy to acknowledge and difficult to operationalize. Every model reflects choices. What data is included? What outcomes are prioritized? What trade-offs are accepted? Those decisions are embedded in the system, shaping how it interprets information.

When a health system adopts an AI tool, it is not simply implementing technology. It is adopting a perspective.

At Clalit Health Services, alignment across payer and provider creates a system where priorities are consistent. Even there, external AI models introduce new assumptions. Those assumptions may not align with the system’s goals. If leadership does not define its own values, it inherits someone else’s.

This becomes real in proactive care. Artificial intelligence enables systems to identify patients at risk before they present. It allows for earlier intervention, often improving outcomes.

It also creates a new kind of pressure. “The toughest choice is what not to do,” Dr. Balicer said.

That statement deserves more attention than it receives. Health care has been built around responding to need. Artificial intelligence introduces the ability to anticipate it. When every patient can be flagged, every risk predicted and every intervention suggested, the system is no longer constrained by insight. It is constrained by capacity.

Artificial intelligence expands what can be done. It does not expand who can do it. Leadership becomes the act of choosing who does what based on validated data.

There is a moment that captures this shift. Imagine a primary care physician starting the day not with a schedule of patients who have called for appointments, but with a list generated by AI identifying individuals who are likely to experience clinical complications in the next six months. Some will develop chronic conditions. Some will require hospitalization. Some can be helped now – preventively.

The physician cannot see them all. Artificial intelligence expands what is possible. Leadership decides what is essential and permissible.

The industry often responds to complexity with activity. Organizations pilot, test and explore. They engage broadly without committing deeply. This creates motion. It rarely creates progress. Pilots are nothing more than experiments. At some point, leadership must decide what to scale, what to stop and what defines value.

Hal Wolf grounded the conversation in discipline. Without a defined, shared objective, effort becomes noise. Pilots create learning, though they often avoid decision-making. Leadership requires clarity. What problem are we solving? What outcome defines success? What are we willing to prioritize? Without those answers, artificial intelligence adds another layer of complexity to an already complex system.

Dr. Kohane brought the conversation back to the discipline of leadership. It cannot remain abstract. It must be informed by experience.

“Go and pay a few bucks and use three or four of the models… get a feel for what this does,” Dr. Kohane advised.

That is not a call for technical fluency. It is a call for leadership proximity. Leaders cannot guide what they do not understand. Artificial intelligence does not behave consistently across models. It produces different answers, shaped by different assumptions. Without direct engagement, those differences remain hidden, and leadership becomes removed from the very decisions it is responsible for guiding.

This is where many organizations hesitate. Artificial intelligence feels complex and complexity invites delegation. At this moment, delegation creates distance. Leadership is required to move closer, not further away.

Artificial intelligence is not reducing the role of leadership. It is redefining it.

This is not a gradual transition. It is already underway. Artificial intelligence is embedded in workflows, shaping decisions and influencing behavior in real time. The system is adapting whether leadership is ready or not.

The question is no longer whether artificial intelligence will shape the future of health. It will. The question is whether leadership will shape how it is applied.

Artificial intelligence will not fix health. It will scale whatever we allow it to touch. The question is whether it will scale what is best in health or what we have yet to fix.

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This is the hidden reality shaping patient care today. A life-saving treatment has little meaning if it is not within reach when a patient needs it.

Zebra Technologies’ recent hospital vision study brings this issue into sharp focus by examining materials management across health systems. The findings reveal that patient outcomes are influenced by clinical expertise and operational readiness. Nearly three-quarters of hospital leaders report that procedures or surgeries have been delayed or canceled because necessary supplies or equipment were unavailable. Each statistic reflects not an abstract system failure, but a human experience marked by anxiety, disruption, and risk.

Access the survey here.

“At Zebra, we remain closely attuned to the needs of the healthcare market. Our findings indicate that a significant majority of non-clinical leaders, 84%, consider the integration of automated, digital systems for tracking all materials used in patient care to be a key initiative for their organizations,” commented Boyede Sobitan, Global Healthcare Strategy Lead at Zebra Technologies.

In most industries, “stockouts” are a consumer inconvenience. In health, it carries far greater consequences. The absence of medication, a device, or equipment can alter the trajectory of care. It can delay treatment, extend suffering, or force clinicians into difficult compromises. The implications reach beyond logistics into the realm of patient safety, trust and survival.

This reality calls for a broader understanding of how care is delivered. Health care is often framed as a relationship between patient and clinician. That relationship remains central, yet it exists within a larger ecosystem. Supply chain leaders, inventory specialists and operational teams play a defining role in whether care can be delivered as intended. The Zebra study notes that 84 percent of decision-makers recognize that inventory management directly affects patient safety. This acknowledgment signals an important shift in thinking.

Care mat begins at the bedside, but the infrastructure that ensures continued implementation begins much earlier, in the systems that ensure readiness.

One of the more revealing insights from the study concerns something deceptively simple: language. Hospitals often lack a shared definition of what it means for an item to be out of stock. For some, it may indicate that inventory has dropped below a threshold. For others, it may mean that an item is unavailable in a specific department, even if it exists elsewhere in the system. This inconsistency creates confusion, delays response, and limits the ability to anticipate problems before they escalate.

Communication failures in health care are frequently associated with clinical interactions. This study highlights that operational communication is equally important. When teams lack a shared understanding, coordination suffers. When coordination suffers, patient care is affected.

“It’s essential that hospital teams have real-time visibility into the location and condition of their most vital resources, and we are observing a clear trend of accelerated investment in technologies that provide both location awareness and automation,” adds Zebra’s Sobitan.

The challenge is compounded by fragmentation across systems. Hospitals have invested significantly in digital tools, from electronic health records to procurement platforms. These investments have improved individual functions, yet they often operate in isolation. Data resides in separate systems. Visibility is incomplete. Teams spend valuable time searching for information or confirming availability.

This fragmentation introduces inefficiencies that extend beyond cost. It places additional strain on clinicians who must navigate uncertainty while maintaining focus on patient care. It also contributes to burnout in a workforce already managing intense demands. Time spent searching for equipment or resolving supply issues is time taken away from direct patient interaction.

There is, however, a clear path forward. The study points to a growing adoption of digital inventory management systems that bring greater standardization and visibility to supply chains. These systems create a shared source of truth, allowing teams across departments to access consistent, real-time information. When inventory levels are transparent and definitions are aligned, organizations can shift from reactive responses to proactive management.

This transition represents more than a technological upgrade. It reflects a cultural shift toward integration and collaboration. When data is accessible and consistent, decisions become more informed and more timely. When teams operate from the same understanding, coordination improves. The result is a system better equipped to support clinicians and patients alike.

It is tempting to view materials management as a background function, separate from the clinical mission. The findings suggest otherwise. Inventory is not peripheral to care delivery. It is foundational to it. Without reliable access to supplies and equipment, even the most advanced clinical capabilities cannot be fully realized.

This perspective reframes the role of operational teams within healthcare. Their work creates the conditions for care to occur. It supports clinicians by removing barriers and reducing uncertainty. It strengthens the system’s ability to deliver on its promises to patients.

At its core, this issue is about trust. Patients enter health-delivery settings with the expectation that the system is prepared for them. Providers rely on that same expectation as they make decisions and deliver care. When supplies are unavailable or systems are fragmented, that trust is tested. When readiness is consistent and reliable, trust is reinforced.

The future of health will continue to be shaped by scientific discovery and technological innovation. Those advances must be matched by equal attention to the operational readiness that enables their delivery. Investment in supply chain visibility, data integration, and operational alignment is not separate from the mission of care. It is integral to it.

Health leaders have an opportunity to rethink what constitutes innovation. It includes not only what is developed in laboratories or deployed in operating rooms, but also what ensures that those advancements reach patients without delay or disruption. Elevating materials management to a strategic priority reflects a commitment to reliability, safety, and patient-centered care.

A quiet transformation is underway in how healthcare systems approach this challenge. It is visible in efforts to standardize processes, integrate data, and connect teams across traditional boundaries. It may not generate headlines, yet its impact is profound.

The most advanced health system is defined by the skill of its patient-facing staff, the sophistication of its treatments, and its readiness to deliver care. It ensures that when a patient needs care, every piece of the operational puzzle is in place to provide it.

That readiness often goes unnoticed when it functions well. Its absence, however, is immediately felt.

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History, however, offers a useful caution. Breakthrough technologies in medicine rarely achieve their full potential simply because they exist. Their real impact depends on whether the institutions responsible for health-care delivery know how to adopt them wisely, integrate them responsibly and align them with their mission to improve patient health.

Artificial intelligence now stands at that same threshold. The industry has moved beyond fascination with what algorithms can do and entered a more demanding phase: determining how these tools should be evaluated, governed, and integrated into the environments where care is delivered. At the same time, some health professionals are turning to AI – not to augment their knowledge – but assuming the information is patient-care ready.

Across the health ecosystem, leaders are discovering that the most important questions about artificial intelligence are not technological. They are organizational, ethical and operational. Which AI systems genuinely improve clinical decision-making? Which tools strengthen the efficiency of hospitals and health systems? Which innovations introduce complexity without delivering measurable benefit?

Answering those questions requires a perspective that bridges policy leadership, real-world care delivery, and the scientific foundations of biomedical informatics. That convergence of experience sits at the center of a “Views From the Top” mainstage discussion at the HIMSS Global Health Conference & Exhibition, where some 35,000 leaders whose work spans the global health ecosystem will examine how organizations can recognize the true value proposition of artificial intelligence applications before embedding them into health-care systems.

The perspectives shaping this discussion reflect three essential dimensions of responsible artificial intelligence in health: governance frameworks that guide innovation, operational insights from large-scale health care delivery, and scientific rigor grounded in biomedical informatics. Together, these vantage points illuminate the path from technological promise to practical value.

Governing Innovation in a Rapidly Changing Health Ecosystem

Digital transformation in health rarely succeeds simply because technology exists. It succeeds when organizations develop leadership frameworks capable of evaluating innovation, managing risk and aligning new tools with patient-centered goals.

Few leaders have observed the evolution of digital health across as many national systems and institutional environments as Hal Wolf, president and chief executive officer of HIMSS, Ran Balicer, MD, PhD, chief innovation officer of Clalit Health Services and Isaac Kohane, MD, PhD, chair of biomedical informatics at Harvard Medical School. The three will step onto the mainstage at HIMSS to share their “View from the Top” in a session titled: “Recognizing the ‘Value Proposition’ Criteria While Selecting AI Applications.”

Through his work with global government health ministries, hospital networks, and technology innovators worldwide, Wolf has consistently emphasized that technological progress must be anchored in governance and trust.

“Digital health transformation is not about technology alone. It is about leadership, governance, and the trust that allows innovation to improve care,” Wolf has said in discussions about global digital health transformation.

Artificial intelligence intensifies this leadership challenge because its influence extends far beyond traditional clinical tools. AI systems increasingly operate across multiple layers of healthcare delivery. Some applications assist clinicians by analyzing medical data or suggesting treatment options. Others function within hospitals’ and health systems’ operational infrastructure, helping manage patient flow, prioritize diagnostic reviews, and allocate scarce resources.

These operational algorithms rarely capture headlines; however,  they shape the environment in which health care is delivered. Decisions about which cases are reviewed first, how clinicians allocate their attention, and how health systems manage capacity can profoundly influence patient outcomes.

For leaders responsible for health systems, artificial intelligence cannot be treated as simply another technological upgrade. It must be evaluated through governance structures capable of understanding how algorithms function, what assumptions shape their recommendations, and how their use aligns with institutional priorities.

Without that oversight, innovation risks amplifying complexity rather than improving care. Instead of informing, it can spread misinformation.

Aligning Artificial Intelligence With the Values of Medicine

Governance provides the policy foundation for responsible adoption of artificial intelligence, but real-world implementation reveals a second challenge: ensuring that AI systems operate effectively within healthcare delivery itself.

Large population health systems increasingly use advanced analytics to anticipate risk, manage chronic disease, and allocate clinical resources across diverse communities. Within these environments, artificial intelligence is no longer a theoretical innovation. It is already influencing how health organizations prioritize patients, coordinate care and deploy limited resources.

That operational perspective is central to Ran Balicer, MD, PhD, of Clalit Health Services, one of the world’s most advanced data-driven health systems. The Clalit integrated infrastructure connects hospitals, clinics, and community health programs through longitudinal datasets that support predictive analytics at the national scale.

Experience within such systems reinforces an important insight: artificial intelligence models do not function independently of human judgment. They reflect priorities embedded in their design and the assumptions guiding their deployment.

“Algorithms are opinions embedded in code,” Balicer has observed in discussions about the role of artificial intelligence in population health.

In practice, this means that AI systems interpret clinical data through frameworks shaped by human choices. The way a model defines risk, prioritizes cases, or recommends interventions reflects decisions about what matters most within a healthcare environment.

Those decisions carry ethical implications. When artificial intelligence helps determine which patients receive immediate attention or which cases are escalated for further review, transparency about how algorithms function becomes essential to maintaining trust among clinicians and patients alike. The scientific frontier of health-care AI reinforces that concern.

Isaac Kohane, MD, PhD, who has also served as a co-author of the Institute of Medicine Report on Precision Medicine, which has served as the template for national efforts, has spent decades exploring how machine learning can advance medicine while preserving the judgment that defines clinical practice. His research emphasizes that artificial intelligence in healthcare must align with the ethical traditions and professional responsibilities of medicine.

“AI systems in medicine must ultimately reflect the values of the profession they serve,” Kohane has written in discussions about AI alignment in biomedical informatics.

This perspective highlights a crucial distinction between technological capability and clinical responsibility. Many AI models entering healthcare environments were originally designed for broader computational tasks rather than the nuanced realities of patient care. Medicine operates within a landscape shaped by uncertainty, empathy, and accountability, and technologies introduced into that environment must reflect those values.

Ensuring that artificial intelligence aligns with the principles guiding health-care delivery, therefore, represents one of the most important scientific and ethical challenges facing the future of health.

The Discipline Required to Make Innovation Matter

The health sector has experienced waves of technological enthusiasm before. Electronic health records promised seamless information exchange, but then introduced administrative burdens on health professionals when implemented without thoughtful workflow design. Data analytics promised unprecedented insight, but sometimes led to fragmentation when systems failed to communicate across institutions.

Artificial intelligence now stands at a similar moment in the evolution of health technology.

Its capabilities in supporting decision-making flow are extraordinary, yet realizing them will require disciplined leadership to evaluate, integrate and govern AI tools within health-care delivery systems. Health leaders must learn to ask deeper questions before embracing the next algorithmic breakthrough. What problem does this system truly solve? How does it strengthen clinical practice? What assumptions guide its recommendations? How does its use advance the mission of improving patient health?

These questions move the conversation beyond technological novelty toward operational practicality. It’s among the many reasons these three global leaders step to the HIMSS stage together.

Artificial intelligence will undoubtedly reshape the health ecosystem in the years ahead. Its long-term impact, however, will not be determined solely by the sophistication of algorithms or the speed of technological progress. Along with how to leverage AI, ChatGPT and LLMs, users require heightened cognitive awareness.

It will be determined by whether the health community develops the discipline and ability required to translate innovation into systems that strengthen care, support clinicians and improve the health of the populations they serve.

The real story of artificial intelligence in health is no longer about what machines can do. It is about how wisely the health sector chooses to use them.

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Scientific Promise and Practical Benefits

A major strength of brain organoid research is its potential to improve our understanding of neurological and psychiatric conditions. Researchers can generate organoids from people with known genetic mutations to study how specific genes affect early brain development. This method has been used to study conditions like autism spectrum disorders, epilepsy, schizophrenia, and Alzheimer’s disease. It helps scientists find cell abnormalities that might not show up in animal studies.

Brain organoids are also useful for drug discovery and safety testing. Many treatments that work in animal models do not succeed in humans, especially for brain disorders. Organoids give scientists a human-based way to test how drugs affect neural cells. This can help spot toxic effects or benefits earlier, potentially lowering the risk of expensive late-stage failures and reducing unnecessary testing on people.

Limitations, Misconceptions, and Ethical Concerns

Even though brain organoids show promise, they have important limitations that are sometimes missed in public discussions. They lack blood vessels, immune cells, and sensory input, all of which are needed for normal brain function. Because they lack a vascular system, organoids obtain oxygen and nutrients only by diffusion, which limits how large and mature they can become. Most organoids end up looking like early fetal brain tissue, not fully developed brains. Does the appearance of something mean it will have the same abilities?

Variability is another challenge. Organoids grown in different laboratories — or even within the same lab — can vary in structure and cellular composition. This makes standardization difficult and complicates the interpretation of results. Additionally, reports of electrical activity within organoids have sometimes been mischaracterized as evidence of consciousness. Most neuroscientists agree that current organoids do not possess awareness, sensation, or thought, but the debate highlights broader uncertainties about how consciousness arises in biological systems.

As the science has advanced, ethical questions have also increased. There are concerns about informed consent when donor cells are used to make neural tissue, especially if donors did not know this could happen. Other worries come up when human organoids are put into animals, which raises questions about species boundaries and oversight. Although these experiments are closely regulated, many ethicists say clearer rules are needed as the technology develops.

Future Directions and Responsible Progress

Researchers are now trying to make brain organoids more realistic and useful. They are working on adding vascular-like systems, combining different organoid types to study how brain regions interact, and making results more consistent between labs. These improvements could help us better understand complex brain disorders and lead to more personalized treatments.

At the same time, ethical guidelines are changing to keep up with new scientific advances. Many experts say that as organoid research moves forward, it should be matched by openness, oversight from different fields, and regular public involvement. Brain organoids are not miracle cures or major threats; they are powerful but imperfect tools that can help neuroscience when used carefully. The future of this research will depend on both technical progress and a strong focus on ethics and public trust.

If all of this sounds like something from a Frankenstein movie, that would be one approach to take, but it isn’t realistic. We are only at the very beginning of understanding what the potential and the problems involved are for us. The research holds great promise, but it also requires informed restrictions that will not prevent advances.

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Primary care continuity allows physicians to develop a longitudinal awareness that no episodic encounter or health tech tool can replicate. Over time, physicians learn what is normal for each patient and what represents meaningful clinical change. Subtle physiological shifts, early symptoms or emerging risk factors appear not as isolated data points from a blood exam, but as part of a social narrative unfolding across time. Early recognition allows earlier intervention, often before disease takes its profound toll.

Clinical evidence confirms the protective effect of continuity. It’s not a matter of opinion. A systematic review published in BMJ Open found that patients with sustained continuity of care had significantly lower mortality than those with fragmented care. Continuity did not just improve satisfaction; it altered survival. The physician who knows the patient can detect disease earlier and guide care more effectively.

Listening allows physicians to detect patterns that laboratory values alone cannot explain. Patients share information differently when they believe that their physician understands them and remembers their history. This sustained awareness allows physicians to identify emerging illnesses without relying solely on reactive diagnostics. Continuity transforms listening into clinical intelligence and a deeper care partnership.

In Healing the Sick Care System: Why People Matter, which has become a surprise Amazon bestseller, one insight repeatedly emerges: patients do not seek care only for treatment; they seek reassurance that someone who knows them is guiding their journey. Physicians who listen across time accumulate knowledge that cannot be captured in a chart alone. That memory allows earlier recognition, more accurate interpretation, and wiser intervention. Healing begins in that continuity of understanding.

Transactional Care Solves Symptoms but Sacrifices Understanding

Health has, for some time, been undergoing a structural shift toward transactional encounters. Walk-in clinics, urgent care centers, and virtual platforms provide speed and accessibility that patients value. These models address immediate symptoms efficiently and fill important gaps in care delivery. Accessibility has improved, yet continuity has weakened.

Transactional medicine treats episodes rather than trajectories. Each encounter begins without the benefit of longitudinal understanding. Clinical decisions are made with time-stamp specific knowledge of how symptoms emerged or how physiology has changed over time. Care becomes reactive rather than interpretive.

Research demonstrates the consequences of this fragmentation. Studies published in the Annals of Family Medicine show that sustained primary care continuity reduces hospitalizations and lowers healthcare expenditures. Early recognition prevents complications that require more invasive, costly interventions. Fragmentation delays recognition and increases clinical risk.

In fact, physicians in the vanguard of building relationships encourage their patients to ask questions.  In their co-authored book Let Patients Help! A “Patient Engagement” handbook – how doctors, nurses, patients and caregivers can partner for better care by “e-Patient Dave” deBronkart with Daniel Z. Sands, MD, MPH, the founder of the Society for Participatory Medicine, offer 10 suggestions that clinicians say to encourage patient engagement.

This shift also alters how patients engage with care. Connections that develop over time can be lost quickly when continuity disappears. Patients become consumers navigating isolated services rather than partners guided across time. The clinical relationship weakens, and with it the interpretive depth that makes prevention possible.

Health systems globally recognize the value of continuity. The Organization for Economic Co-operation and Development (OECD), a Paris-based international organization that promotes policies to improve economic and social well-being globally, reports that hospital admissions for chronic diseases, often preventable through effective primary care, account for a substantial share of healthcare utilization. Systems that preserve physician-led primary care continuity achieve better outcomes and greater efficiency. Relationship stabilizes care.

Innovation Requires Connection to Fulfill Its Potential

This shift toward transactional care carries life-threatening implications that extend far beyond the patient experience. It also directly affects whether health innovation fulfills its promise or becomes a compensatory tool addressing fragmentation. Innovation depends on context to generate meaningful insight. Context emerges through continuity. That context can devalue life-saving innovations.

Artificial intelligence, predictive analytics, and remote monitoring technologies are designed to detect patterns across time. These tools require longitudinal clinical awareness to distinguish meaningful change from statistical variation. Physicians who know their patients can interpret innovation correctly and act earlier. Innovation becomes transformative when anchored in relationship.

Fragmented care weakens this interpretive capacity. Data collected across disconnected encounters lacks coherence. Predictive tools lose precision when longitudinal context is absent. Innovation becomes reactive, identifying disease after symptoms emerge rather than predicting disease before it develops.

Technology achieves its highest value when it extends the physician’s ability to listen and observe. Remote monitoring allows earlier recognition of physiological change. Predictive analytics strengthens preventive intervention. Innovation amplifies continuity when guided by sustained physician leadership.

Team-based primary care models reflect this principle. Nurse practitioners and physician assistants expand access while physician leadership preserves interpretive continuity. Research published in Medical Care Research and Review confirms that coordinated team-based care maintains strong clinical outcomes. Physician oversight ensures that innovation remains integrated within longitudinal care. It also improves health professional job satisfaction and reduces burn-out.

Innovation cannot replace the relationship at the center of medicine. Algorithms detect patterns but do not understand meaning, and they do not strengthen physician/patient ties. Devices collect data, but do not know the patient behind the data. Physicians translate information into guidance by integrating technology with human understanding.

The future of health innovation depends on preserving continuity between patient and physician. Technology deployed within sustained relationships strengthens prevention and improves outcomes. Technology deployed within fragmented systems often compensates for structural weakness rather than transforming care. Continuity determines whether innovation fulfills its promise.

Health systems now face a defining moment. Transactional care offers speed and convenience. Relational care offers understanding and prevention. Innovation will achieve its full potential only when it strengthens the continuity that allows physicians to listen, learn, and guide patients across time.

Healing begins with being heard. Health technology succeeds when it helps physicians listen more deeply and act more wisely in the service of the people who entrust them with their care.

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