One example would be pain. Research published in the Journal of Neuroscience found that when people didn’t know how much a painful heat stimulus would hurt — when they watched a group of others who disagreed wildly about it — they felt more pain than when the group agreed. The heat itself didn’t change. Only the uncertainty did. That single finding opens a door onto something much bigger: the way the brain interprets incoming signals doesn’t just affect physical pain. In fact, it shapes every experience, every emotion, and every belief we form about the world around us.

The Brain Is a Prediction Machine, Not a Camera

Your brain doesn’t work like a camera, passively recording what’s in front of it. It works more like a detective — making its best guess about what’s happening based on past experience, context, and whatever signals it can pick up in the moment. In fact, this is the way AI works the same way because it guesses what you intend when you are dictating to it. That’s based on what you have known to use before. It’s not original; it’s from something you’ve already said or thought.

Scientists call this predictive processing. Fancy words for something that’s simple. The brain is constantly generating a model of reality and checking it against what the senses report. Most of what you experience isn’t raw sensory data. It’s the brain’s best guess, already processed and interpreted before you’re even aware of it.

This has enormous consequences. Because your brain fills in gaps with guesses, your perception of any situation is shaped as much by what you expect as by what’s actually there. Research on how emotions are built in the brain confirms this same pattern. Feelings aren’t simple, automatic reactions that arise out of nowhere. They’re constructed — assembled by the brain from past learning, bodily signals, and whatever the surrounding context suggests is happening — all woven together into something that feels completely immediate and real. Fear, hope, dread, excitement — none of these are just responses to the world. They’re interpretations. And like all interpretations, they can be mistaken.

This might be unsettling to hear. But it’s also genuinely freeing, because it means your perception of reality isn’t fixed. It can be trained.

The Brain’s Thumb on the Scale

Here’s the catch. The brain doesn’t interpret experiences evenly. It has a strong, built-in bias toward the negative. This explains why negative information is so strongly entrenched in our minds. Negative information is stored more vividly in memory and carries more weight in the decisions we make than equivalent positive information does. This isn’t a character flaw. It’s an evolutionary feature.

Our ancestors survived by treating ambiguous situations as dangerous — if a rustle in the bushes might be a predator, it was safer to assume the worst and run. The cost of a false alarm was low; the cost of missing a real threat could be fatal.

In modern life, that same wiring creates serious problems. We’re exposed to more alarming information than any previous generation — not necessarily because the world is more dangerous, but because we carry a device in our pockets that streams us the worst of humanity around the clock. Research on how news consumption affects perception found that a steady diet of threatening content actively cultivates a distorted view of the world, pushing people to overestimate danger (The Scary World Syndrome) and feel a constant sense of impending doom that doesn’t match their actual circumstances.

In one study on risk perception during a health crisis, people overestimated their personal risk of dying from a disease by more than 270 times the actual probability. Their brains weren’t computing risk. They were amplifying fear.

Uncertainty makes all of this worse. Much worse. The same research that revealed how uncertainty increases physical pain also showed that not knowing what to expect activates a specific brain region — one that amplifies the intensity of an experience, for better or worse. And this effect isn’t limited to physical sensation.

Research on stress and health outcomes has found that the threat of losing a job can actually be more damaging to physical health than losing it outright, because the brain treats an uncertain threat as something to brace against continuously — a draining, exhausting posture that takes a real toll on the body over time. Sounds like burnout, doesn’t it? It isn’t just pain that uncertainty turns up. It’s almost everything the brain interprets as potentially threatening, which, given the negativity bias, covers a whole lot of ground.

What makes this particularly important in today’s world is that this feedback loop isn’t passive. The beliefs we form — shaped by perception, fear, and repeated exposure to alarming information — circle back and filter what we’re willing to notice next.

Research on how beliefs affect the brain’s processing of sensory information suggests that what we expect to see and feel actually controls what reaches our conscious awareness. Our beliefs aren’t just conclusions we reach. They become part of the filter that determines what evidence the brain even considers. This is like throwing the wheat away with the chaff.

What You Can Actually Do About It

Understanding how the brain constructs experience isn’t just interesting. It points directly to what we can do differently.

The first step is recognizing that your interpretation of a situation isn’t the same thing as the situation itself. When you feel dread about a conversation you haven’t had yet or are certain something’s going to go wrong, your brain is filling in a gap with a guess — shaped by past experience, current stress, and the negativity bias — not delivering a reliable preview of the future. That awareness alone, when you can genuinely hold onto it, changes your relationship with the feeling. You don’t have to argue with it or push it away. You just don’t have to treat it as truth.

The second step involves what you feed your brain. Because the brain builds its models of the world out of the patterns it encounters most often, the information environment you live in genuinely shapes how you perceive things — including things that have nothing directly to do with that environment. Heavy exposure to alarming content trains the brain to scan for threats even in neutral situations. Seeking out different perspectives, sitting with ambiguity instead of rushing to resolve it, and spending time in environments where uncertainty is met with curiosity rather than alarm — these gradually reshape the models your brain is running.

The third step is learning to treat uncertainty itself differently. That’s harder than it sounds, because not knowing really activates stress responses that narrow attention and make everything feel more urgent and more threatening. But evidence consistently shows that people who can stay open when they don’t know what’s coming — who can resist the pull toward premature conclusions — think more flexibly, solve problems more creatively, and make sounder decisions. The ability to hold more than one interpretation in mind at once isn’t a fixed personality trait. Like any other cognitive skill, it responds to practice.

None of this is an argument for forced optimism or pretending that hard things aren’t hard. Negative emotions carry real information and serve genuine purposes when they’re in proportion to what’s actually happening. The goal isn’t to replace one distortion with another. It’s important to notice when the brain’s interpretive machinery is running hot — turning not-knowing into catastrophe, amplifying uncertainty into doom — and to remember that what feels like reality is always, to some degree, something the brain has made.

The world you live in isn’t the world as it is. It’s the world your brain has built for you, piece by piece, out of everything it expects, fears, and has learned to look for. That’s not a reason for despair. Actually, it’s an invitation to get curious about the builder — and to ask whether the story it’s been telling you still has to be the only one.

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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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Over 987 million people around the world now use AI chatbots regularly. Research shows that nearly half of Americans with ongoing mental health conditions have turned to a chatbot for emotional support in the past year alone. That’s a huge number of people relying on a technology that’s still very new in mental health care. So what does this mean?

Is it a big step forward in making help more accessible, or are we taking a risky chance? As with most things, the truth is somewhere in the middle. These tools offer real benefits, but they also come with real risks. It’s important to look at both sides honestly.

The Case for AI Chatbots in Mental Health

First, let’s look at why so many people are turning to these tools. There’s a mental health crisis, and not enough providers to help everyone who needs it. Long wait lists, high costs, and the ongoing stigma around seeking help all make it harder for people to get care. For someone who can’t afford therapy, can’t find an available provider, or feels too embarrassed to talk to someone in person, a chatbot that’s always available can feel like a lifeline.
Research supports this to some extent. Corporations are responding to this, and more TV ads are appearing that offer online therapy with or without chatbots.

A systematic review of 31 randomized controlled trials, which is considered the gold standard in research, found that AI chatbots helped reduce anxiety and depression symptoms in adolescents and young adults. Another meta-analysis of 14 strong trials found a clear positive effect on mental health outcomes, showing these tools are more than just placebos. For college students, who often face unique pressures and may avoid formal help, chatbots have shown promise in building coping skills and improving emotional well-being.

Anonymity is important, too. People are more likely to open up when they don’t feel judged. Studies show that users see the chatbot’s lack of social expectations as a big advantage. It’s easier to admit you’re struggling when you don’t have to worry about what someone else thinks. For people with anxiety, this low barrier could mean the difference between getting some support and getting none.

Mental health professionals have noticed these benefits, too. A 2025 study found that many clinicians see AI chatbots as a useful way to offer support between therapy sessions, provide education, and reach people who might not seek care otherwise. When the alternative is no help at all, the accessibility and scalability of chatbots are hard to ignore.

Where These Tools Can Cause Real Harm

This is where things get more difficult. The same qualities that make chatbots appealing, like being available, warm, and endlessly patient, can also make them risky for people in real psychological distress. We need to remember that chatbots are designed to keep users constantly engaged. It can be very hard to disconnect because the connection becomes so strong that it almost feels like leaving a friend.

Researchers have found something called a “compassion illusion” the strong feeling that an AI understands you, cares about you, and responds to your emotions in a meaningful way. An algorithm has no ability to “feel” or “care.” It feels real, but it isn’t. This gap between what people feel and what’s actually happening is where problems can start, especially for vulnerable people who may not realize they’re relying on something with no clinical judgment, no duty of care, and no way to notice if they’re getting worse.

A Stanford University study found that several popular therapy chatbots failed important therapeutic tests. They not only showed stigmatizing attitudes toward conditions like schizophrenia and alcohol dependence, but also gave dangerous responses in crisis situations. In one case, a chatbot responded to a subtle mention of suicidal thoughts by cheerfully naming tall bridges — something a good therapist would never do. Instances such as this have resulted in lawsuits related to suicides.

Another study tested ten AI chatbots using fictional teen mental health scenarios. Nearly a third of the time, the bots supported harmful ideas suggested by the fictional teens, such as dropping out of school or avoiding all human contact. None of the ten bots managed to challenge every dangerous suggestion. By any clinical standard, that’s a failing grade.

There’s also the problem of people relying too much on chatbots. Since these systems are always available and don’t make human mistakes, they can become someone’s main source of emotional support. Psychiatrists are now seeing cases of what’s called “AI psychosis” in patients, especially those with mental health vulnerabilities, who develop worse delusions or paranoia after spending a lot of time with chatbots. Because chatbots tend to agree and mirror rather than challenge distorted thinking, they can quietly make things worse over days or weeks.

This isn’t just a theoretical risk. It’s happening in clinical offices right now.

What We Still Don’t Know — and Why That Matters

The uncomfortable truth is that we don’t have enough research to know how often AI chatbots help, how often they cause harm, or who is most at risk. A review of 160 studies found that only 16 percent of the newer large language model-based chatbot studies had gone through clinical efficacy testing. Most are still in early testing stages. It’s like handing out a new drug before the clinical trials are finished.

Media coverage hasn’t made things clearer. Studies looking at news reports on AI chatbots and mental health found that journalism often focuses on the most severe, emotional outcomes, like suicides and hospitalizations, and presents them as clear cause-and-effect stories, even though the real evidence is much less certain. In most cases, there were already mental health conditions, substance use issues, or major life stressors involved. AI may have played a part, but it’s rarely the whole story.

Clinicians surveyed about AI chatbots have also raised concerns that aren’t getting enough attention. These include data privacy concerns, the risk that people will rely on chatbots instead of professional care, and the fact that these tools don’t know when to stop. They can’t pause a conversation, send someone to emergency services, or alert a family member. They can’t do the most important things when someone is truly in crisis.

The truth is that we’re still in the early days. Research is growing quickly — the number of studies on mental health chatbots quadrupled between 2020 and 2024. But strong, large-scale clinical evidence is still behind the technology. Millions of people are using these tools while science tries to keep up.

So what does this mean for you? An AI chatbot might really help you get through a tough night or teach you some coping skills. But it could also mislead you, support harmful thinking, or make you feel supported when you actually need a real person to help.

Use these tools carefully. If you’re dealing with serious depression, suicidal thoughts, trauma, or psychosis, they are not a substitute for professional care, no matter how warm or available they seem. If you’re using a chatbot for lighter support or just to sort out your thoughts, notice how you feel over time. Are you feeling more isolated or more dependent on it? That’s important to pay attention to.

This technology is here to stay. What we urgently need are clearer safety standards, better regulations, and more honest conversations about what these tools can and can’t do. Until then, a bit of healthy skepticism is helpful.

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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.

The post AI Will Not Fix Health Care – Leadership Might appeared first on Medika Life.

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.

The post The Invisible Lifeline: Why Supplies, Not Just Science, Determine Patient Care appeared first on Medika Life.

I believe in making it very difficult for people to refuse vaccines. There’s enough of the libertarian about me that I wouldn’t actually strap them down and inject them, but I’m fine with school districts making parents write out their conscientious objections to children being immunised or with sports clubs requiring adult proof of immunisation before people can join. What I or you think is, though, beside the point. Much of the US is walking away from cajoling and compulsion and there’s great pressure in Europe for similar change. We can either go on moaning about how we wish the world hadn’t changed or we can respond effectively.

Before the current US Administration began rewriting vaccine recommendations, one in six US parents wasn’t following them. We used to joke that vaccine-preventable diseases in the West had become diseases of children of the over-educated middle classes who shopped at Whole Foods and did naked yoga classes; vaccine refusers now are still more likely to be white, but they skew to being conservative, very religious, and young. Recommendations actually reduced uptake in this group because most have a deep distrust of the Federal Government and its agencies.

Formal vaccine refusals in Poland more than doubled from 2017 to 2022 and reached over 87,000 in 2023, a 1685% increase since 2003; measles cases surged 10x in early 2024 due to falling rates. Ireland, where I live, has the third-lowest childhood vaccine coverage rate in the OECD.

There are bright spots too, Italy for example, and the battle is far from lost. But the mistrust now endemic to the United States is coming to Europe.

High-handed US and European experts

You can understand confusion, if not mistrust. About half of parents in the USA did not vaccinate their children for flu in the past year, compared with 41 percent who said they had done so, a Washington Post / Kaiser Family Fund poll found. Coverage started declining after 2019. In 2016, the US CDC said that the nasal flu vaccine used in children provided “no measurable benefit” (injectable vaccines for adults were, as usual, highly effective). In the same year, Public Health England said that the same vaccine (produced by a British company in a British factory) was 58 percent effective. Canada followed the UK, saying that its population was very different to the USA! It’s very unlikely that both the Americans and the Canadians were right — despite those obvious population differences…. Few journalists covered the story — I suspect because no-one wanted to be accused of promoting vaccine scepticism. The vaccine is now recommended again in the USA.

Few American paediatricians and even fewer nurses would have been able to explain this to parents because no-one ever bothered to give the professionals an explanation. What do we think doctors told parents who asked why a vaccination was recommended then was not and then was again? British parents who did a web search (this was pre-Chat GPT, remember) might have asked why their children were getting an apparently ineffective vaccine and would have met equally bemused stares from their health providers. Did anyone brief social media influencers or health journalists? Of course not, who do they think they are? What impudence…

I know some of those involved and I’m sure that there was no subterfuge and nothing sinister going on; the answer is likely to be dull and involve methodology and surveillance systems.

This is the way we all used to approach treatment discussions 40 years ago — the doctor told you what to do, you thanked him (it was nearly always a him) and you did it. Questions were a sign of disrespect, of even psychological illness. I was recently treated by a Russian dentist, now practising in Ireland, who was shocked and outraged when I questioned his recommendation to use antibiotics prophylactically; if he had been Irish, he would have been completely used to it.

Nonsensical recommendations in developing countries

Vaccine hesitancy looks a bit different in France. Those least likely to have their children vaccinated tend to be more educated, high users of the internet for information and to have lower trust in health authorities. Those who refuse vaccines for themselves tend to be at the lower end of the social hierarchy with less education and fewer financial resources. Many are ​immigrants and descendants of immigrants, and residents of French overseas departments. Both are probably likely to know about the vaccines which Western experts recommend for children in the developing world, including in Francophone countries.

I remember doing a policy interview with the health minister of a large Indian state. I was trying to find out what he might pay for an effective TB vaccine. “But”, he said, “we already have a TB vaccine. Why do I need a new one?” His top civil servant was sitting behind him and frantically gesticulating to me to try to stop me explaining that the BCG vaccine, given to almost every Indian newborn, may do nothing to prevent TB infections and, at best, may make the disease less severe in some of the children who contract it. It is, though, very good at causing severe side effects. No developed economy uses it; almost every poor one does.

I’m ashamed to say that I did not explain BCG as clearly as I should have to the minister. He was the norm, not the exception, in that series of policymaker interviews: few of those making decisions about TB vaccine policy had ever been given a thorough, honest briefing about the limitations of the vaccines their expert advisers recommended. None of the parents, of course, were ever told about any of these reservations.

There might also be a case for the current practice of giving many children in Africa and Asia a vaccine that sometimes causes polio, instead of preventing it, although I doubt it. The risks of a child contracting polio from the live-attenuated oral vaccine are probably underestimated when they’re presented to politicians and policy influencers. Hardly any parents who bring their children forward for these vaccines are told about the risk or the rationale for continuing to use them, rather than the perfectly safe inactivated vaccine used throughout the rich world.

Is it any wonder that those with insight into the developing world are sceptical? The real wonder is that vaccine confidence is still so high in Africa and Asia. That probably comes from everyday encounters with the tragic consequences of infection by vaccine-preventable illnesses, an experience blessedly denied to most Americans and Europeans.

What we need to do now

The road ahead has been cleared for us. Thirty years ago, I went out with a trainee doctor at the Royal College of Surgeons in Ireland. He was upset one evening because he had been berated by his tutor for telling an older patient that she had cancer — it had been agreed with the family that she would be told that she had a “growth” to avoid upsetting her. At least she found out: King George VI of the United Kingdom sent his daughter, Princess Elizabeth, on a world tour in 1952 because neither he nor she had been told that he had lung cancer and that it was terminal. He never saw her again. These stories shock us now because honesty, realism and communication are taken for granted in what we tell patients who are ill. These principles need to be the new basis for what we tell people who are healthy and want to stay that way.

First we need a change in attitude. Whether to be immunised or not is a decision that people will take — actually, a series of decisions. We don’t need to think about whether we like the concept or not, it is the way things increasingly are. We have to get ordinary people used to making good decisions, just as they do about other life issues such as house buying or insurance or continuing education. Ordinary people are not property experts or risk analysts or trained evaluators of course offerings, but they mostly make reasonable choices. They can do the same thing with vaccines.

Then, we need to communicate much more. Vaccine producers are free to talk to the public about recommended vaccines in many countries; where they are not, they need to be allowed to. Then they need to accept their responsibility to speak often, clearly and loudly. They are the experts on the vaccines they produce and they must tell potential recipients or the parents of recipients about the benefits and disadvantages. Of course, they need to do it in an honest and balanced way. They will be more successful if they communicate in partnership with professional organisations, charities and respected consumer groups. They can be transparent: they have a commercial interest in getting people to accept vaccines but a legal responsibility to set out all the factors in deciding whether to or not. It’s like banks selling mortgages and car dealerships selling warranties.

Researchers and healthcare providers need training in communication and answering questions. They need to be much better at helping policy makers to make decisions about vaccines. Today, too few vaccines are reimbursed and many are offered only to some of those who would benefit from them. In many countries, it is still too hard to get vaccinated and even where rules have changed, practices have not — look at Poland, for example. Politicians and public officials can unleash vaccines so that they can do even more to boost productivity, growth and wealth in society.

Those same scientific and medical experts need to be much better at talking to people who are making decisions about immunisation. Research tells us clearly what helps the right decision, but too few professionals follow the evidence. The most powerful prompt to action is a trusted health professional saying, “I would like you to do this”. Setting a good example works wonders too, but too few health professionals have had all of the vaccines recommended for them.Communication can change all of this.

The vast majority of social media influencers want to give good advice and powerful motivation but no-one talks to them — after all, we want people to follow the guidelines, not think, don’t we? For example, have you seen Dr Mike Varshavski take on 20 vaccine sceptics at once? Thirty million people probably have over various platforms and he’s brilliant. Industry and professionals need to work with influencers who specialise in women’s issues, childhood, workplace effectiveness and, of course, health. Look at this from Dr Ahmed Ezzat — his videos on RSV reduced calls to the emergency services by 25% — and just think what he can do for vaccines.

Journalists are discouraged from writing pieces about vaccine decisions — “just tell people to follow expert recommendations”. Many, consequently, avoid writing about vaccines. We need to treat these journalists as powerful allies in helping lay people to make important decisions with lifelong implications for their risk of developing chronic illnesses. It’s the way that property developers treat journalists who write about houses,

Honestly, I still think it would be simpler and still ethically correct to just nudge almost everyone into getting immunised but that is not an option in many places now and, given the global market in ideas, won’t be one anywhere soon.

Parents get things right

Asia should encourage us. Many parents save and spend to get their children the best vaccines. The state often provides old tech or nothing, so middle-class parents take their children to private clinics for the best protection and pay full price for it. Of course, it’s not fair to poorer children and it is crazy public policy given that population sizes will plunge across Asia over the next 30 years so every child, whether middle class or not, is a precious national resource. Still, it shows that individual families can and do make better decisions than health policy makers when the routes of communication are open and used well.

The post We Have to Earn Better Vaccine Coverage Rates appeared first on Medika Life.

In later life, weight loss can be a double‑edged sword. A few pounds off the joints can be both helpful and risky. Shedding a few pounds may ease joint pain, but losing weight without meaning to can be a warning sign. Fast weight loss can also lead to muscle loss, which is key to staying independent.

Experts also point out practical issues: injections need good vision, steady hands, and a regular routine. Stomach and bowel side effects can be tougher for seniors, especially if they’re already losing weight without trying. complicate life for older adults — and how to approach them with a “safety first” mindset.

1) Aging changes the risk–benefit math (even when a drug “works”)

Older adults, especially those who are frail or have several health issues, are often left out of clinical trials. This is important because average trial results may not match the real-life experience of a 75-year-old who takes several medications and needs to manage appetite and hydration.

A 2024 debate paper on GLP-1 drugs in older patients, including those with kidney disease, points out that limited trial data and multiple medications make it harder to judge safety and effectiveness for frailer seniors. Clinicians need to make decisions based on each person, not just on averages. In simple terms, the real question is not whether GLP-1s are good or bad, but whether they help this specific older person with their unique health needs.

There’s another subtle issue: in later life, the goal is often less about chasing an ideal weight and more about protecting function—walking safely, rising from a chair, maintaining balance, staying hydrated, and maintaining enough strength to live independently. So for older adults, the most important question isn’t “How much weight will I lose?” It’s “What will this do to my strength, my nutrition, and my ability to stay steady on my feet?”

2) Common side effects can become serious for older adults.

GLP-1s often cause nausea, vomiting, diarrhea, constipation, and less appetite. Younger people may find these symptoms unpleasant but manageable. For older adults, though, these issues can quickly lead to dehydration, dizziness, and falls, especially if they also take blood pressure medicines or diuretics.

Current FDA labeling for semaglutide products highlights this pathway: stomach and bowel side effects can lead to volume depletion, and acute kidney injury has occurred, including in postmarketing reports. The label advises monitoring kidney function when starting or increasing doses in people who develop severe gastrointestinal reactions, and it notes that dehydration has been part of reported kidney injury cases.

This is how many real-life problems start: a few days of not being able to eat or drink much, then feeling lightheaded, falling, or needing emergency care for dehydration. Older adults may not feel as thirsty and may have less ability to recover. So, it’s important to watch hydration, electrolytes, blood pressure, and kidney function, especially in the first months of treatment and after increasing the dose.

3) Muscle and frailty: losing weight does not always mean better health.

The headline benefits of GLP‑1s often focus on pounds lost. But the body doesn’t lose only fat. Lean mass (including muscle) can drop, too. This matters in older adults because age‑related muscle loss (sarcopenia) is already common — and it’s tightly linked to frailty, falls, and loss of independence.

A 2025 mini-review on older adults warns that starting and stopping GLP-1s repeatedly can change body composition, sometimes leading to ‘sarcopenic obesity’ — having too much fat and too little muscle. The authors are not saying to avoid GLP-1s, but to remember that weight loss does not always mean better health for older people.

More pointedly, a 24‑month retrospective cohort study in older adults with type 2 diabetes reported that semaglutide use was associated with muscle loss and functional decline, particularly at higher doses and in patients who already had sarcopenia. The authors emphasize individualized risk–benefit assessment and the need for monitoring and intervention.

If you’re reading this as an older adult, it may help to translate the research into plain questions to bring to your next appointment: “If I lose weight, how will we protect my muscles?” “How will we check whether I’m getting weaker?” “What would make us stop or change course?” An older adult who becomes “smaller but weaker” has not gained health — only risk.

4) Other complications: gallbladder, pancreas, vision, and low blood sugar

Gallbladder and bile duct problems can be an unexpected issue. Losing weight already increases the risk of gallstones, and GLP-1s seem to increase it even further. A large review found that using GLP-1 drugs increases the chance of gallbladder or bile duct disease, especially at higher doses, for longer periods, or when used for weight loss.

For older adults, this might present as sudden pain in the upper right side of the belly, nausea, fever, or pain spreading to the back or shoulder. These symptoms should be checked by a physician right away.

GLP-1 drug labels also warn about the risk of sudden pancreatitis and say to get medical help for severe, ongoing belly pain. The overall risk is low, but older adults may have additional risk factors, such as gallstones or high triglycerides. Severe belly pain in later life should always be checked quickly.

Then there’s the risk of blood sugar dropping too low. GLP‑1s don’t usually cause hypoglycemia by themselves, but the risk rises when combined with insulin or sulfonylureas. Semaglutide labeling warns that concomitant use with an insulin secretagogue or insulin may increase the risk of hypoglycemia and may require dose reductions of those agents.

In older adults, hypoglycemia can be particularly dangerous: it can cause falls, confusion, fainting, and cardiac stress. It’s also easier to miss, because symptoms may look like “just being tired” or “a little off today,” especially in someone who already has memory or balance problems.

Eyes and vision deserve special attention. Semaglutide labeling includes a warning about diabetic retinopathy complications and recommends monitoring patients with a history of retinopathy. Beyond labeling, post‑marketing safety monitoring continues to explore visual signals.

A 2025 analysis of FDA adverse event reporting data found a potentially elevated risk of vision‑impairment reports with semaglutide use compared with some other diabetes and weight‑loss medications, and it called for vigilant surveillance and further research. That doesn’t prove the drug causes vision loss in an individual patient, but it is enough to justify a cautious posture: new blurring, blind spots, or sudden changes deserve a same‑week medical call, not a “let’s see if it passes.”

5) Surgery and sedation: delayed stomach emptying can cause problems

GLP‑1 medications slow stomach emptying — one reason people feel full sooner. But that same effect can complicate anesthesia and deep sedation if food remains in the stomach despite standard fasting. A 2024 review describes the connection between GLP‑1 medications, delayed gastric emptying (including gastroparesis), and increased risk of aspiration during anesthesia, as well as possible effects on the absorption of other medications.

This issue has become important enough that several medical groups have created guidelines for surgery. The 2024 guidance says many people can continue taking GLP-1s, but doctors should look for higher-risk situations, such as people with stomach problems or other risks of food entering the lungs, and adjust plans as needed.

This is important for older adults because they are more likely to undergo procedures requiring sedation, such as colonoscopies, joint injections, cardiac procedures, dental work, or surgeries. The easiest and most often missed safety step is to tell every physician involved — surgeon, anesthesiologist, endoscopist, dentist — that you are taking a GLP-1 medication and when you last took it. Do not assume it will be clear in your medical chart.

6) A senior‑friendly “yes, with a plan” approach

If you’re an older adult considering a GLP‑1 (or already taking one), a safer approach often looks like “yes, with monitoring.” That means starting with function, not just the scale: tracking energy, steadiness, and strength in everyday life, not only pounds.

It also means treating hydration as a real medical concern. Ongoing nausea, vomiting, or diarrhea is not just part of getting used to the medicine. These symptoms can affect blood pressure and kidney function, especially when changing doses.

Because muscle matters so much in later life, protecting it should be part of the prescription. That can include discussing protein intake, adding a realistic strength plan (even chair‑based work or physical‑therapy guided resistance), and reassessing the medication if weight loss is accompanied by weakness, poor balance, or reduced stamina.

Older adults should also have their medications reviewed with a focus on preventing low blood sugar. If insulin or a sulfonylurea is being used, doses may need to be adjusted as appetite decreases and blood sugar improves.

Finally, it is important to take symptoms seriously. New stomach pain, ongoing vomiting, or sudden vision changes should be checked by a doctor right away. Before any procedure with anesthesia or deep sedation, make sure to tell the medical team about your GLP-1 use — do not assume they already know.

The GLP-1 medications can help some older adults, but there is less room for mistakes. Side effects can quickly lead to dehydration, frailty, falls, or problems during procedures. The safest approach is not just ‘yes’ or ‘no,’ but ‘yes, with a plan’ — one that protects hydration, nutrition, muscle, vision, and safety during medical care.

The post GLP‑1 Medications in Later Life: Why the “Miracle Shot” Needs a Senior‑Specific Safety Lens appeared first on Medika Life.

When I read stories that appear throughout the book, the room becomes pin-drop silent. Not uncomfortable, but attentive. People lean forward. Some close their eyes. Others quietly wipe away tears. Even after reading these stories again and again, my own eyes still mist. These are not reactions to theory or argument. They are responses to a painful reality many recognize.

What becomes clear in those rooms is that the frustration is not isolated to one role or perspective. Patients speak about waiting and uncertainty. Clinicians describe exhaustion and moral strain. Innovators and policymakers wrestle with systems that move more slowly than the problems they are trying to solve. The details differ, but the throughline is the same: people want care that recognizes their presence and treats them as more than a process to be managed. When that recognition happens, the tone of the conversation changes.

Since its listing, the book has spent several consecutive weeks on Amazon’s Top New Releases list. That matters in a conventional sense. Still, rankings, whether in print or digital format, do not explain what happens when people hear their own experience reflected back to them with clarity and respect. Stories do that work. Many are weary of facts and figures deployed to justify positions rather than illuminate lived reality.

Human experience carries a different kind of truth. It does not compete with data, but it precedes it. When experience is named accurately, people do not feel persuaded. They feel recognized. That recognition opens space for reflection, dialogue, and ultimately for change.

A Question That Changes the Room

I finished a book talk and signing with The Marfan Foundation, and the impact lingers beyond the formal program. During the signing, people ask thoughtful, personal questions. I often ask permission to respond by reading a short passage from the book. Then I listen to stories of courage, love, and endurance that surface naturally and without prompting.

Parents speak about children. Siblings talk about one another. Families describe navigating medical uncertainty and emotional trauma over years, sometimes decades. Individuals share how they discover the strength they did not know they possessed, and how they learn to share that strength with others walking similar paths. These are not stories of abstraction. They are lived, detailed, and deeply human.

The Marfan Foundation is one of the patient and professional communities reflected in the book, and in the room, the reason is unmistakable. Physicians are spoken of by first name – Alan, Duke, Kim and Reed – not title. They are described not as distant experts, but as people who show up consistently and with care. These stories remind everyone present that even in the most complex conditions, care is sustained by relationships as much as by scientific excellence.

Between Two Meetings, on a Moving Train

As I board a Brightline train for the next meeting, the contrast stays with me in a quiet, persistent way. I am traveling from a gathering centered on shared human experience to SCOPE Summit 2026, a global convening focused on clinical trials and research infrastructure. The agenda centers on development planning, protocol optimization, patient-centric trial design, site engagement and recruitment, generative AI, and the technologies that move science from hypothesis to evidence.

One meeting is rooted in lived journeys, where science is received as hope amid uncertainty. The other is grounded in structure and precision, where science is designed, measured, and scaled. Both spaces matter deeply, and both are essential to progress. Clinical research is where rigor lives and where uncertainty is reduced in ways that allow care to advance responsibly.

Yet the transition between these two gatherings and two cities reveals something essential. People do not leave their humanity at the door of the operating room or the halls of science. They carry it with them into protocols, endpoints, enrollment decisions and trial participation. Patients do not experience trials as abstractions. They experience them as acts of trust layered onto already complex lives.

When Structure Forgets Experience

Too often, human experience is treated as something to be accounted for after systems are built, rather than as a foundation for their design. Trials are optimized for efficiency and compliance, yet struggle when recruitment falters, participation drops, or trust erodes. These outcomes are not solely technical failures. They are relational failures.

Patient-centric trial design is not a feature added late in development. It is a mindset that shapes questions, assumptions, and priorities from the start. Site engagement is not a procedural step, but a relationship built over time. Technology reduces burden only when shaped by empathy, context, and understanding.

Rare disease communities such as The Marfan Foundation understand this instinctively. When systems fall short, patients and families organize, advocate, and collaborate more intentionally. In doing so, they model what the broader system aspires to scale: trust, continuity, shared language, and partnership. People do not fragment their lives the way systems fragment care.

When Experience Finally Counts

At SCOPE, this question becomes practical rather than theoretical. I moderate a fireside chat with StuffThatWorks executives Yael Elish and newly appointed CEO Julie Ross, exploring what happens when patient experience is treated not as a marginal input but as the foundation of artificial intelligence itself. Billions of dollars are invested in pre-clinical discovery, yet clinical trials remain a costly bottleneck, often stretching beyond seven years before therapies reach patients.

One story from the book captures why this matters. A woman living with a chronic autoimmune condition follows treatment guidelines faithfully yet struggles with side effects that force her to stop therapy repeatedly. Her medical record reflects non-adherence, not struggle. It is only when she joins a patient-driven community where thousands share lived experience that patterns emerge her clinicians have never seen.

Within weeks, she learns how others adjust dosing, manage side effects, and balance treatment with daily life. When these experiences are aggregated and analyzed, they do not contradict clinical science. They complete it. What once looks like noise becomes a signal when the human story is allowed to remain intact.

This is why patient-derived models matter. Real-world evidence is not simply post-market surveillance. It is the accumulated story of how people actually live with disease, navigate treatment, and make trade-offs that controlled environments rarely capture. These data are not neutral artifacts. They are lives rendered into patterns with meaning.

Restoring What Was Lost

What I witness in quiet rooms, at signing tables, and in conversations that follow readings is not resistance to science. I see the same truth as a fireside chat moderator, alongside people dedicated to bridging patient voice, data, and science in ways that honor those it seeks to serve. What emerges, again and again, is a longing for connection.

People are not asking to be spared complexity, nor do they believe science belongs only in a sterile laboratory. They are asking not to be erased by it. They want science that recognizes them even as it advances, and systems that remember who they are designed to serve.

This is where Why People Matter ultimately resides. Healing does not begin when systems are optimized or when data moves faster. It starts when relationships are restored and when people feel recognized within the structures meant to help them. Science advances when trust is present, and trust grows when listening is treated not as an accessory but as a foundation.

If there is a path forward, it is not found by choosing between humanity and innovation. It is found by refusing to separate them. Data matters because people do. And when science remembers that progress becomes worthy of the lives it touches.

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If you’re an adult in the U.S., you can expect to gain 10 to 25 pounds between your 20s and your 40s. Starting between ages 30 and 40, you may find losing weight and exercising more challenging. The exercise you do may not have the same effect as before. It’s not necessarily a sign that something is wrong. This weight gain in middle age—known as “middle-age spread”—is a natural consequence of aging.

“Your metabolism tends to slow down as you get older,” says NIH’s Dr. Rafael de Cabo, an expert on aging. “But your appetite and your food intake do not. So, you have a steady increase of body weight with age.”

Much of the weight gain comes in the form of fat tissue. The distribution of fat in your body also shifts. There’s less under your skin and more around your internal organs. Meanwhile, you start to lose lean muscle with age. Many people also become less active as they age, especially if they have a job that involves a lot of sitting. This can lead to further fat gain and muscle loss.

Those extra pounds have consequences beyond your clothes not fitting. The risk of many chronic diseases, such as diabetes, heart disease, and neurodegenerative diseases, goes up with age. Excess weight can further heighten these risks.

Fortunately, you can take steps to maintain a healthy weight as you age. Your diet can play a key role. Having a slower metabolism means you’ll need fewer calories. But you also want to make sure you still get all the nutrients your body needs. Get tips on healthy eating as you age.

De Cabo studies the effects of dietary changes on health and longevity. One example is intermittent fasting, in which meals are interspersed with long fasting periods. For example, you might limit eating to only eight hours per day. Studies suggest intermittent fasting may help some people to eat less and keep weight off. But De Cabo and others have been finding that it might also have benefits for your metabolism.

His work has shown that mice live longer and stay healthier when they go for long periods between meals. This was true even if they were eating the same amounts and types of foods as mice that ate whenever they wanted. Other studies have also suggested that periods of fasting may bring benefits beyond weight loss.

Physical activity is important for combating the changes that come with aging, too.

“The key is to maintain an active lifestyle,” de Cabo says. “Try to incorporate daily walks or daily visits to the gym. If you have an office job, get a standup desk, so you spend a few hours a day standing instead of sitting. Small doses of exercise throughout the day will help tremendously.”

Visit: https://newsinhealth.nih.gov/2024/10/stopping-middle-age-spread for more information.

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