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• Published: 09 April 2024

The potential for artificial intelligence to transform healthcare: perspectives from international health leaders

• Christina Silcox 1 ,
• Eyal Zimlichmann 2 , 3 ,
• Katie Huber   ORCID: orcid.org/0000-0003-2519-8714 1 ,
• Neil Rowen 1 ,
• Robert Saunders 1 ,
• Mark McClellan 1 ,
• Charles N. Kahn III 3 , 4 ,
• Claudia A. Salzberg 3 &
• David W. Bates   ORCID: orcid.org/0000-0001-6268-1540 5 , 6 , 7  

npj Digital Medicine volume  7 , Article number:  88 ( 2024 ) Cite this article

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Artificial intelligence (AI) has the potential to transform care delivery by improving health outcomes, patient safety, and the affordability and accessibility of high-quality care. AI will be critical to building an infrastructure capable of caring for an increasingly aging population, utilizing an ever-increasing knowledge of disease and options for precision treatments, and combatting workforce shortages and burnout of medical professionals. However, we are not currently on track to create this future. This is in part because the health data needed to train, test, use, and surveil these tools are generally neither standardized nor accessible. There is also universal concern about the ability to monitor health AI tools for changes in performance as they are implemented in new places, used with diverse populations, and over time as health data may change. The Future of Health (FOH), an international community of senior health care leaders, collaborated with the Duke-Margolis Institute for Health Policy to conduct a literature review, expert convening, and consensus-building exercise around this topic. This commentary summarizes the four priority action areas and recommendations for health care organizations and policymakers across the globe that FOH members identified as important for fully realizing AI’s potential in health care: improving data quality to power AI, building infrastructure to encourage efficient and trustworthy development and evaluations, sharing data for better AI, and providing incentives to accelerate the progress and impact of AI.

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Introduction.

Artificial intelligence (AI), supported by timely and accurate data and evidence, has the potential to transform health care delivery by improving health outcomes, patient safety, and the affordability and accessibility of high-quality care 1 , 2 . AI integration is critical to building an infrastructure capable of caring for an increasingly aging population, utilizing an ever-increasing knowledge of disease and options for precision treatments, and combatting workforce shortages and burnout of medical professionals. However, we are not currently on track to create this future. This is in part because the health data needed to train, test, use, and surveil these tools are generally neither standardized nor accessible. This is true across the international community, although there is variable progress within individual countries. There is also universal concern about monitoring health AI tools for changes in performance as they are implemented in new places, used with diverse populations, and over time as health data may change.

The Future of Health (FOH) is an international community of senior health care leaders representing health systems, health policy, health care technology, venture funding, insurance, and risk management. FOH collaborated with the Duke-Margolis Institute for Health Policy to conduct a literature review, expert convening, and consensus-building exercise. In total, 46 senior health care leaders were engaged in this work, from eleven countries in Europe, North America, Africa, Asia, and Australia. This commentary summarizes the four priority action areas and recommendations for health care organizations and policymakers that FOH members identified as important for fully realizing AI’s potential in health care: improving data quality to power AI, building infrastructure to encourage efficient and trustworthy development and evaluations, sharing data for better AI, and providing incentives to accelerate the progress and impact of AI.

Powering AI through high-quality data

“Going forward, data are going to be the most valuable commodity in health care. Organizations need robust plans about how to mobilize and use their data.”

AI algorithms will only perform as well as the accuracy and completeness of key underlying data, and data quality is dependent on actions and workflows that encourage trust.

To begin to improve data quality, FOH members agreed that an initial priority is identifying and assuring reliable availability of high-priority data elements for promising AI applications: those with the most predictive value, those of the highest value to patients, and those most important for analyses of performance, including subgroup analyses to detect bias.

Leaders should also advocate for aligned policy incentives to improve the availability and reliability of these priority data elements. There are several examples of efforts across the world to identify and standardize high-priority data elements for AI applications and beyond, such as the multinational project STANDING Together, which is developing standards to improve the quality and representativeness of data used to build and test AI tools 3 .

Policy incentives that would further encourage high-quality data collection include (1) aligned payment incentives for measures of health care quality and safety, and ensuring the reliability of the underlying data, and (2) quality measures and performance standards focused on the reliability, completeness, and timeliness of collection and sharing of high-priority data itself.

Trust and verify

“Your AI algorithms are only going to be as good as the data and the real-world evidence used to validate them, and the data are only going to be as good as the trust and privacy and supporting policies.”

FOH members stressed the importance of showing that AI tools are both effective and safe within their specific patient populations.

This is a particular challenge with AI tools, whose performance can differ dramatically across sites and over time, as health data patterns and population characteristics vary. For example, several studies of the Epic Sepsis Model found both location-based differences in performance and degradation in performance over time due to data drift 4 , 5 . However, real-world evaluations are often much more difficult for algorithms that are used for longer-term predictions, or to avert long-term complications from occurring, particularly in the absence of connected, longitudinal data infrastructure. As such, health systems must prioritize implementing data standards and data infrastructure that can facilitate the retraining or tuning of algorithms, test for local performance and bias, and ensure scalability across the organization and longer-term applications 6 .

There are efforts to help leaders and health systems develop consensus-based evaluation techniques and infrastructure for AI tools, including HealthAI: The Global Agency for Responsible AI in Health, which aims to build and certify validation mechanisms for nations and regions to adopt; and the Coalition for Health AI (CHAI), which recently announced plans to build a US-wide health AI assurance labs network 7 , 8 . These efforts, if successful, will assist manufacturers and health systems in complying with new laws, rules, and regulations being proposed and released that seek to ensure AI tools are trustworthy, such as the EU AI Act and the 2023 US Executive Order on AI.

Sharing data for better AI

“Underlying these challenges is the investment required to standardize business processes so that you actually get data that’s usable between institutions and even within an institution.”

While high-quality internal data may enable some types of AI-tool development and testing, this is insufficient to power and evaluate all AI applications. To build truly effective AI-enabled predictive software for clinical care and predictive supports, data often need to be interoperable across health systems to build a diverse picture of patients’ health across geographies, and reliably shared.

FOH members recommended that health care leaders work with researchers and policymakers to connect detailed encounter data with longitudinal outcomes, and pilot opportunities across diverse populations and systems to help assure valid outcome evaluations as well as address potential confounding and population subgroup differences—the ability to aggregate data is a clear rate-limiting step. The South African National Digital Health Strategy outlined interventions to improve the adoption of digital technologies while complying with the 2013 Protection of Personal Information Act 9 . Although challenges remain, the country has made progress on multiple fronts, including building out a Health Patient Registration System as a first step towards a portable, longitudinal patient record system and releasing a Health Normative Standards Framework to improve data flow across institutional and geographic boundaries 10 .

Leaders should adopt policies in their organizations, and encourage adoption in their province and country, that simplify data governance and sharing while providing appropriate privacy protections – including building foundations of trust with patients and the public as previously discussed. Privacy-preserving innovations include ways to “share” data without movement from protected systems using approaches like federated analyses, data sandboxes, or synthetic data. In addition to exploring privacy-preserving approaches to data sharing, countries and health systems may need to consider broad and dynamic approaches to consent 11 , 12 . As we look to a future where a patient may have thousands of algorithms churning away at their data, efforts to improve data quality and sharing should include enabling patients’ access to and engagement with their own data to encourage them to actively partner in their health and provide transparency on how their data are being used to improve health care. For example, the Understanding Patient Data program in the United Kingdom produces research and resources to explain how the National Health Service uses patients’ data 13 . Community engagement efforts can further assist with these efforts by building trust and expanding understanding.

FOH members also stressed the importance of timely data access. Health systems should work together to establish re-usable governance and privacy frameworks that allow stakeholders to clearly understand what data will be shared and how it will be protected to reduce the time needed for data use agreements. Trusted third-party data coordinating centers could also be used to set up “precertification” systems around data quality, testing, and cybersecurity to support health organizations with appropriate data stewardship to form partnerships and access data rapidly.

Incentivizing progress for AI impact

“Unless it’s tied to some kind of compensation to the organization, the drive to help implement those tools and overcome that risk aversion is going to be very high… I do think that business driver needs to be there.”

AI tools and data quality initiatives have not moved as quickly in health care due to the lack of direct payment, and often, misalignment of financial incentives and supports for high-quality data collection and predictive analytics. This affects both the ability to purchase and safely implement commercial AI products as well as the development of “homegrown” AI tools.

FOH members recommended that leaders should advocate for paying for value in health – quality, safety, better health, and lower costs for patients. This better aligns the financial incentives for accelerating the development, evaluation, and adoption of AI as well as other tools designed to either keep patients healthy or quickly diagnose and treat them with the most effective therapies when they do become ill. Effective personalized health care requires high-quality, standardized, interoperable datasets from diverse sources 14 . Within value-based payments themselves, data are critical to measuring quality of care and patient outcomes, adjusted or contextualized for factors outside of clinical control. Value-based payments therefore align incentives for (1) high-quality data collection and trusted use, (2) building effective AI tools, and (3) ensuring that those tools are improving patient outcomes and/or health system operations.

Data have become the most valuable commodity in health care, but questions remain about whether there will be an AI “revolution” or “evolution” in health care delivery. Early AI applications in certain clinical areas have been promising, but more advanced AI tools will require higher quality, real-world data that is interoperable and secure. The steps health care organization leaders and policymakers take in the coming years, starting with short-term opportunities to develop meaningful AI applications that achieve measurable improvements in outcomes and costs, will be critical in enabling this future that can improve health outcomes, safety, affordability, and equity.

Data availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

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Acknowledgements

The authors acknowledge Oranit Ido and Jonathan Gonzalez-Smith for their contributions to this work. This study was funded by The Future of Health, LLC. The Future of Health, LLC, was involved in all stages of this research, including study design, data collection, analysis and interpretation of data, and the preparation of this manuscript.

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Christina Silcox, Katie Huber, Neil Rowen, Robert Saunders & Mark McClellan

Sheba Medical Center, Ramat Gan, Israel

Eyal Zimlichmann

Future of Health, Washington, DC, USA

Eyal Zimlichmann, Charles N. Kahn III & Claudia A. Salzberg

Federation of American Hospitals, Washington, DC, USA

Charles N. Kahn III

Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, MA, USA

David W. Bates

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Contributions

C.S., K.H., N.R., and R.S. conducted initial background research and analyzed qualitative data from stakeholders. All authors (C.S., E.Z., K.H., N.R., R.S., M.M., C.K., C.A.S., and D.B.) assisted with conceptualization of the project and strategic guidance. C.S., K.H., and N.R. wrote initial drafts of the manuscript. All authors contributed to critical revisions of the manuscript and read and approved the final manuscript.

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Correspondence to David W. Bates .

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Competing interests.

C.S., K.H., N.R., and C.A.S. declare no competing interests. E.Z. reports personal fees from Arkin Holdings, personal fees from Statista and equity from Valera Health, Profility and Hello Heart. R.S. has been an external reviewer for The John A. Hartford Foundation, and is a co-chair for the Health Evolution Summit Roundtable on Value-Based Care for Specialized Populations. M.M. is an independent director on the boards of Johnson & Johnson, Cigna, Alignment Healthcare, and PrognomIQ; co-chairs the Guiding Committee for the Health Care Payment Learning and Action Network; and reports fees for serving as an adviser for Arsenal Capital Partners, Blackstone Life Sciences, and MITRE. C.K. is a Profility Board member and additionally reports equity from Valera Health and MDClone. D.W.B. reports grants and personal fees from EarlySense, personal fees from CDI Negev, equity from Valera Health, equity from Clew, equity from MDClone, personal fees and equity from AESOP, personal fees and equity from Feelbetter, equity from Guided Clinical Solutions, and grants from IBM Watson Health, outside the submitted work. D.W.B. has a patent pending (PHC-028564 US PCT), on intraoperative clinical decision support.

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Silcox, C., Zimlichmann, E., Huber, K. et al. The potential for artificial intelligence to transform healthcare: perspectives from international health leaders. npj Digit. Med. 7 , 88 (2024). https://doi.org/10.1038/s41746-024-01097-6

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With these factors in mind, here's my overview of what I believe will be the most prominent trends in 2024.

Generative AI In Healthcare

AI will be instrumental in many of the trends here, but generative AI, in particular, will be particularly impactful over the next 12 months. It will democratize access to other transformative AI applications, making it easier to implement and interpret results and generate personalized recommendations. It will create synthetic data that can be used to train medical AI algorithms without compromising patient privacy or where there simply isn't enough relevant real-world data. And it can create chatbots and virtual assistants to help at every stage of the patient journey. The applications of generative AI in healthcare are practically limitless, and we'll certainly be returning to it as we discuss the other trends on this list.

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Personalized Medicine

At a high level, this term refers to the creation of tailored treatment plans for individual patients. In practice, this is increasingly being done with technology and data. The most advanced applications are in genomics, where AI is being used to analyze patients' DNA to diagnose and treat diseases and to create medicines that are personalized to specific people down to the molecular level (sometimes called precision medicine ). Many researchers believe that a personalized approach to healthcare leads to better patient outcomes and more efficient use of medical resources and will play an increasingly important role in addressing the healthcare challenges of the future.

Virtual Healthcare Assistants

Virtual assistants and chatbots can help clinicians by providing advice on treatments, diagnoses, and medications. They can also help patients by answering questions about their care and connecting them with the information they need to make more informed decisions about their own care. Increasingly, they will interface with electronic health record systems and be used to book and schedule appointments. They can also help patients stay compliant by reminding them to take medications or exercise. They can even provide companionship for patients who live alone or in remote areas to improve their mental health!

Digital Twins

A digital twin is a virtual model of a real-world system, object, place, tool, or process. It can be used to simulate anything from a single device, such as a needle, to understand how it works in different conditions to an entire hospital to understand how services are delivered. Digital twins of the human body and individual organs have been developed to model the effects of changes in treatment, medication and lifestyle choices. Perhaps the most complex digital twin currently imaginable is a twin of the human brain , which researchers hope to advance by 2024.

IoT-Powered Virtual Hospitals And Telemedicine 2.0

This trend includes both telemedicine and wearable devices connected to the global network known as the Internet of Things (IoT). By using connected devices to remotely monitor patients and provide communication channels for healthcare professionals, more elements of care can be delivered remotely. We call this "telemedicine 2.0" because it goes beyond the simple delivery of remote care, such as remote consultations, to a holistic approach to remote patient care and treatment. Virtual hospital wards are an example of this trend in action in 2024 - where a central location acts as a hub for monitoring multiple patients in their own homes.

Preventative Healthcare

This covers many topics, including exercise, wellness, and immunizations, but it all boils down to the old adage that prevention is better than cure. This shift from reactive to proactive approaches will be a strategic priority for healthcare providers in 2024. Research has shown that it can create long-term benefits for patients, as well as reduce the costs associated with treating preventable conditions. Technological advances, including AI and wearable technology, will also play a major role here, enabling early warning and rapid intervention.

Virtual And Augmented Reality In Healthcare

The use of virtual reality (VR) in healthcare is beginning to take off, with several innovative use cases now entering the mainstream. In particular, it has been shown to be effective in helping patients manage long-term chronic pain . It has been shown to be more effective and cause fewer side effects than traditional pharmaceutical pain management, leading to improved quality of life for patients and reduced hospital stays. Meanwhile, augmented reality (AR) is increasingly being used by surgeons to provide digital information as they work without the need to look at separate screens. Another application is wound care management, where it enables non-invasive assessment of the severity, healing status, and best treatment options for a patient's wound.

8 Elderly Care

Many developed nations have aging populations, which will inevitably put increasing pressure on healthcare systems as people live longer and require more support in later life. Innovative solutions that enable the elderly to remain in their own homes for longer, rather than taking up space in hospitals, hospices and nursing homes, will come to the fore. There will also be an increased focus on developing new treatments for diseases that occur specifically in old age and put a strain on care systems such as Alzheimer's and Parkinson's. Other trends discussed here, including preventative care, virtual hospitals and healthcare assistants, will also have important implications.

3D Printing - From Implements To Organs

Additive manufacturing - where products are constructed using processes such as 3D printing - has a major impact on healthcare. In parts of the world where medical equipment is hard to come by, it can be used to print tools and devices on demand, including surgical instruments, orthopedic or dental implants, and prosthetics. Research is also underway into the viability of 3D-printed organs for transplant using biological tissue taken from the patient's body. If proven effective, this could provide a solution to the chronic shortage of organs available for transplant and dramatically reduce the cost of these procedures.

Convergence Of Mental and Physical Healthcare Delivery

For most of the history of medicine, mental and physical health care have been relatively siloed. The COVID-19 pandemic has changed that, as providers increasingly recognize the intrinsic links between physical and mental well-being and the need for a holistic approach. Examples of this in action in 2024 will include frontline healthcare providers, such as primary care physicians, increasingly screening for ways in which mental health issues may impact the treatment and recovery of physical ailments.

You can read more about these topics in my books , The Future Internet: How the Metaverse, Web 3.0, and Blockchain Will Transform Business and Society , Future Skills: The 20 Skills And Competencies Everyone Needs To Succeed In A Digital World and Business Trends in Practice , which won the 2022 Business Book of the Year award. And don’t forget to subscribe to my newsletter and follow me on X (Twitter ), LinkedIn , and YouTube for more on the future trends in business and technology.

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Healthcare’s next chapter: What’s ahead for the US healthcare industry

Uncertainty has been the norm in healthcare in 2023, and that’s not likely to change in 2024. A presidential election year looms in the context of pressure on federal government finances from large budget deficits and the impact of higher interest rates on federal debt servicing costs. In addition, the healthcare industry faces uncertainty about the financing of Medicare and Medicaid; regulation, including views about horizontal and vertical integration; and overall industry economics.

In the face of this uncertainty—some might call it opacity—discerning senior management teams can act on a few trends that are clearer. Some of the trends and possible responses germane to strategy and performance of healthcare organizations in 2024 are highlighted below.

What’s ahead for healthcare players: An overview

We outlined in 2022 how the gathering storm fueled by inflation and workforce shortages would put pressure on healthcare over the next few years. Indeed, the pressure on healthcare leaders continues unabated. In response, industry players will have to consider repositioning their businesses as well as gearing up to ensure superior business performance:

• Hospital systems face a 200-basis point gap between reimbursement rates and cost inflation, according to McKinsey analysis. The gap could require performance transformations on the part of health systems, including more outsourcing, ramping up digital and automation efforts, and business rationalization.
• In 2024, employers are facing rising health insurance premiums well above their comfort zone of annual increases of less than 4 percent. 1 Kathryn Mayer, “Aon report: Big increase projected for 2024 employer health care costs,” SHRM, August 29, 2023. As payers see continued increases in medical costs and accelerating prescription drug costs, this pressure will require health plans to renew focus on medical and administrative cost control.
• These cost pressures offer many opportunities for tech-enabled services companies that can show customers near-term return on investment from their products. At the same time, many healthcare services and technology companies without demonstrable return will face severe downside to their businesses.
• Higher interest rates and less liquidity in the financial markets have raised the hurdle rate for private equity (PE) and venture capital firms. In these circumstances, private investors must ensure their portfolio companies deliver bottom-line performance, produce organic growth backed by proven business models, and have the ability to make any inorganic growth accretive based on robust capabilities. Large, well-capitalized healthcare companies will find a favorable valuation environment for acquiring PE portfolio companies as well as for forming strategic partnerships with private investors.

What’s ahead for payers

Payer value creation continues to shift from administering health benefits and providing insurance to managing care and capturing delivery and pharmacy economics. Partnering with and enabling physicians, likely in risk-based arrangements, will continue to gain in importance relative to other models of utilization management.

As pressure from rising medical and prescription costs mount, scaling proven physician partnership models (for example, primary care–centered value-based care) as well as innovating new ones (specialty benefit management and specialty value-based care) will grow in importance. Enhancing health outcomes and members’ care experience, prompted by both the incentives in government programs but also rising demand from employers, will be important priorities.

Finally, a renewed focus on reducing administrative costs will be high on the agenda for payers to ensure sustainable margins, offer a better experience for members and clinicians, and to free up resources to invest in strategic capabilities.

What’s ahead for health systems

Healthcare delivery will continue its restructuring. The definition of at-scale systems has changed in the past few years; today, it takes more than $13 billion to be a top-20 system by revenue, and many have reached their current position through inorganic growth, according to McKinsey analysis. The recent wave of M&A, however, is distinct from its predecessors. It is characterized by cross-geography deals designed to create value by scaling investments in platform capabilities across digital, analytics, shared services, and workforce management.

Beyond scale, sites of care have shifted increasingly from the hospital to ambulatory, home, and virtual care. This trend was playing out before the COVID-19 pandemic and was certainly accelerated by it. But the pivot toward ambulatory sites has been slower than expected, given the impact such a transition has on health system revenue, among other structural issues. Disruptors are vying to meet consumers’ demand for convenient access, but patients can be stuck navigating a complex system of healthcare organizations when their needs become more acute.

In parallel, health systems have struggled to fill their clinical workforce needs. The nursing shortage has become more acute: more than 100,000 nurses left the profession from 2019 to 2022, and health systems could face a shortage of 200,000 to 450,000 nurses by 2025. 2 Gretchen Berlin, Meredith Lapointe, Mhoire Murphy, and Joanna Wexler, “ Assessing the lingering impact of COVID-19 on the nursing workforce ,” McKinsey, May 11, 2022. Anticipated physician shortages are also an issue, though health system employment of physicians has slowed. Regulation (for example, price transparency and the 340B drug pricing program) and rising costs of capital (due to macroeconomic factors as well as ratings trajectories) will continue to create uncertainty.

While health system performance has generally improved over the past year as the industry emerges from the pandemic, a subset of players is really shining. Those that appear to be breaking away are hyperfocused on resilience, taking a multilever approach to growth while continuing to identify and take actions to ensure sustainable margins.

What’s ahead for artificial intelligence in healthcare

Generative artificial intelligence (gen AI) has created considerable excitement in the industry. Gen AI could be catalytic in accelerating the application of digital and automation in healthcare, thereby offering some answers to the twin challenges of affordability and workforce availability. For example, adopting currently available technology (including but not limited to automation, AI, and gen AI) could allow payers to reduce administrative costs by 13 to 25 percent, reduce medical costs by 5 to 11 percent, and increase revenue by 3 to 12 percent.

However, healthcare has lagged behind other industries in adoption of AI. For several reasons, the industry has had a hard time adopting the technology. For example, AI requires time-consuming and often manual preparation of clean and structured data; well-planned, narrow use cases (such as predicting a specific event or outcome); modern infrastructure; and hard-to-hire talent (such as data scientists and data engineers).

Given the need for empathetic and intelligent interactions in a service industry such as healthcare, the recognition, comprehension, and content creation capabilities of gen AI represent a major opportunity. It is particularly appealing in its simplicity: gen AI thrives on unstructured data, which is plentiful in healthcare; it is pretrained; and it is broadly understood by people across the organization. The potential use cases for gen AI cross every domain and function. Gen AI use cases, in addition to existing analytics use cases, could help address real burdens, including reducing preparation time and improving quality of clinical documentation, modernizing outdated or legacy applications, and personalizing patient and member outreach at scale.

Unlocking this value will be a leadership challenge. Senior healthcare executives will need to educate their boards, leadership teams, and employees; attract talent; drive adoption; and pursue change management initiatives such as workflow shifts. Scaling pilots to production-scale solutions with concurrent process changes will be important differentiators in 2024.

What’s ahead in prescription drugs

GLP-1 drugs hold the promise of treating type 2 diabetes (in 11 percent of the US population; 38 percent of the population has prediabetes 3 National Diabetes Statistics Report , Centers for Disease Control and Prevention, accessed November 20, 2023. ) and obesity (42 percent of adults 4 “Adult obesity facts,” Centers for Disease Control and Prevention, accessed November 20, 2023. ), potentially helping to avoid many other ailments, such as heart and chronic kidney disease. The population of patients meeting clinical eligibility criteria for GLP-1s is one of the largest of any new drug class in the past 20 to 30 years.

Although there is much to be excited about, experience shows that taking advantage of medical advances is often elusive in healthcare. GLP-1s must be taken consistently to maintain weight loss; however, initial studies indicate persistency and adherence to therapy is poor (32 percent of members remain persistent at one year and 27 percent during the second year 5 “Real-world analysis of glucagon-like peptide-1 antagonist (GLP-1a) obesity treatment one-year cost-effectiveness and therapy adherence,” Prime Therapeutics and MagellanRx Management, July 11, 2023. ).

Nonetheless, the shift in care and financing models that accompany GLP-1 drugs are likely to be material. The growth of the GLP-1 market has amplified the conversation around preventive care and demonstrated the impact of media awareness and consumer-driven demand in treatment decisions. Its expansion has also fueled the rise of telehealth providers, broadening access points for consumers.

The growth of the GLP-1 market presents cost challenges in the near term because benefits will accrue over time. The annual wholesale acquisition cost per patient ranges from $12,000 to $16,000. The high cost of the therapy raises complex coverage decisions for payers and plan sponsors, made even harder by the potential spending waste from therapy discontinuation.

GLP-1 drugs are not the only broad population drugs emerging or in the late-stage pipeline; others include treatments for Alzheimer’s and non-alcoholic fatty liver disease. New drugs have the potential to not only improve patients’ health but also heighten the need for better therapy and cost management. The resulting business model changes across the healthcare value chain are likely to be meaningful.

We hear from many healthcare leaders that this is an unnerving time given the relentless pressure and uncertain outlook they face. They also tell us that this is an exciting time that presents opportunities for innovation to improve members’ and patients’ health and lives, to reimagine current organizations, and build new capabilities and businesses. We would suggest healthcare leaders address known trends and avoid trying to predict future trends, given the considerable uncertainty ahead. Building resilient and agile organizations capable of rapidly adapting to new challenges as they emerge will be important to succeed in this environment.

Shubham Singhal is the global leader of McKinsey’s Social, Healthcare, and Public Entities (SHaPE) Practice in McKinsey’s Detroit office, and Drew Ungerman is the global leader of McKinsey’s Healthcare Practice and the McKinsey Health Institute in the Dallas office.

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Why writing by hand beats typing for thinking and learning

Jonathan Lambert

If you're like many digitally savvy Americans, it has likely been a while since you've spent much time writing by hand.

The laborious process of tracing out our thoughts, letter by letter, on the page is becoming a relic of the past in our screen-dominated world, where text messages and thumb-typed grocery lists have replaced handwritten letters and sticky notes. Electronic keyboards offer obvious efficiency benefits that have undoubtedly boosted our productivity — imagine having to write all your emails longhand.

To keep up, many schools are introducing computers as early as preschool, meaning some kids may learn the basics of typing before writing by hand.

But giving up this slower, more tactile way of expressing ourselves may come at a significant cost, according to a growing body of research that's uncovering the surprising cognitive benefits of taking pen to paper, or even stylus to iPad — for both children and adults.

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In kids, studies show that tracing out ABCs, as opposed to typing them, leads to better and longer-lasting recognition and understanding of letters. Writing by hand also improves memory and recall of words, laying down the foundations of literacy and learning. In adults, taking notes by hand during a lecture, instead of typing, can lead to better conceptual understanding of material.

"There's actually some very important things going on during the embodied experience of writing by hand," says Ramesh Balasubramaniam , a neuroscientist at the University of California, Merced. "It has important cognitive benefits."

While those benefits have long been recognized by some (for instance, many authors, including Jennifer Egan and Neil Gaiman , draft their stories by hand to stoke creativity), scientists have only recently started investigating why writing by hand has these effects.

A slew of recent brain imaging research suggests handwriting's power stems from the relative complexity of the process and how it forces different brain systems to work together to reproduce the shapes of letters in our heads onto the page.

Your brain on handwriting

Both handwriting and typing involve moving our hands and fingers to create words on a page. But handwriting, it turns out, requires a lot more fine-tuned coordination between the motor and visual systems. This seems to more deeply engage the brain in ways that support learning.

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"Handwriting is probably among the most complex motor skills that the brain is capable of," says Marieke Longcamp , a cognitive neuroscientist at Aix-Marseille Université.

Gripping a pen nimbly enough to write is a complicated task, as it requires your brain to continuously monitor the pressure that each finger exerts on the pen. Then, your motor system has to delicately modify that pressure to re-create each letter of the words in your head on the page.

"Your fingers have to each do something different to produce a recognizable letter," says Sophia Vinci-Booher , an educational neuroscientist at Vanderbilt University. Adding to the complexity, your visual system must continuously process that letter as it's formed. With each stroke, your brain compares the unfolding script with mental models of the letters and words, making adjustments to fingers in real time to create the letters' shapes, says Vinci-Booher.

That's not true for typing.

To type "tap" your fingers don't have to trace out the form of the letters — they just make three relatively simple and uniform movements. In comparison, it takes a lot more brainpower, as well as cross-talk between brain areas, to write than type.

Recent brain imaging studies bolster this idea. A study published in January found that when students write by hand, brain areas involved in motor and visual information processing " sync up " with areas crucial to memory formation, firing at frequencies associated with learning.

"We don't see that [synchronized activity] in typewriting at all," says Audrey van der Meer , a psychologist and study co-author at the Norwegian University of Science and Technology. She suggests that writing by hand is a neurobiologically richer process and that this richness may confer some cognitive benefits.

Other experts agree. "There seems to be something fundamental about engaging your body to produce these shapes," says Robert Wiley , a cognitive psychologist at the University of North Carolina, Greensboro. "It lets you make associations between your body and what you're seeing and hearing," he says, which might give the mind more footholds for accessing a given concept or idea.

Those extra footholds are especially important for learning in kids, but they may give adults a leg up too. Wiley and others worry that ditching handwriting for typing could have serious consequences for how we all learn and think.

What might be lost as handwriting wanes

The clearest consequence of screens and keyboards replacing pen and paper might be on kids' ability to learn the building blocks of literacy — letters.

"Letter recognition in early childhood is actually one of the best predictors of later reading and math attainment," says Vinci-Booher. Her work suggests the process of learning to write letters by hand is crucial for learning to read them.

"When kids write letters, they're just messy," she says. As kids practice writing "A," each iteration is different, and that variability helps solidify their conceptual understanding of the letter.

Research suggests kids learn to recognize letters better when seeing variable handwritten examples, compared with uniform typed examples.

This helps develop areas of the brain used during reading in older children and adults, Vinci-Booher found.

"This could be one of the ways that early experiences actually translate to long-term life outcomes," she says. "These visually demanding, fine motor actions bake in neural communication patterns that are really important for learning later on."

Ditching handwriting instruction could mean that those skills don't get developed as well, which could impair kids' ability to learn down the road.

"If young children are not receiving any handwriting training, which is very good brain stimulation, then their brains simply won't reach their full potential," says van der Meer. "It's scary to think of the potential consequences."

Many states are trying to avoid these risks by mandating cursive instruction. This year, California started requiring elementary school students to learn cursive , and similar bills are moving through state legislatures in several states, including Indiana, Kentucky, South Carolina and Wisconsin. (So far, evidence suggests that it's the writing by hand that matters, not whether it's print or cursive.)

Slowing down and processing information

For adults, one of the main benefits of writing by hand is that it simply forces us to slow down.

During a meeting or lecture, it's possible to type what you're hearing verbatim. But often, "you're not actually processing that information — you're just typing in the blind," says van der Meer. "If you take notes by hand, you can't write everything down," she says.

The relative slowness of the medium forces you to process the information, writing key words or phrases and using drawing or arrows to work through ideas, she says. "You make the information your own," she says, which helps it stick in the brain.

Such connections and integration are still possible when typing, but they need to be made more intentionally. And sometimes, efficiency wins out. "When you're writing a long essay, it's obviously much more practical to use a keyboard," says van der Meer.

Still, given our long history of using our hands to mark meaning in the world, some scientists worry about the more diffuse consequences of offloading our thinking to computers.

"We're foisting a lot of our knowledge, extending our cognition, to other devices, so it's only natural that we've started using these other agents to do our writing for us," says Balasubramaniam.

It's possible that this might free up our minds to do other kinds of hard thinking, he says. Or we might be sacrificing a fundamental process that's crucial for the kinds of immersive cognitive experiences that enable us to learn and think at our full potential.

Balasubramaniam stresses, however, that we don't have to ditch digital tools to harness the power of handwriting. So far, research suggests that scribbling with a stylus on a screen activates the same brain pathways as etching ink on paper. It's the movement that counts, he says, not its final form.

Jonathan Lambert is a Washington, D.C.-based freelance journalist who covers science, health and policy.

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What is the process of an athlete being 'medically retired' due to concussion?

by Annette Greenhow, The Conversation

In recent years, a growing number of professional athletes are medically retiring from sport, particularly in some of Australia's most popular football codes.

In April, Collingwood player Nathan Murphy, 24, medically retired due to advice about his concussion history. He follows 28-year-old Angus Brayshaw as another high-profile, mid-career player who announced his retirement on medical grounds this year.

In other codes, Cronulla Sharks co-captain Dale Finucane retired last month due to concussion concerns. He joined other NRL players Boyd Cordner, Jake Friend and Andrew Davey in retiring on medical advice or by personal choice.

Rising Australian cricket star Will Pucovksi, with a long history of concussions, is currently working with medical experts from in the sport to determine his playing future.

Medical retirement can happen at any level of any sport, but media and public attention tends to focus on the elite codes, drawing attention to the heightened public awareness of concussion and concerns around the cumulative effects of repeated head impacts and links to longer term neurological conditions.

But what is the process these players go through in reaching this decision? Is there any room for pushback should a player want to continue to play despite being advised otherwise?

Living the dream

We first need to understand the context of the sporting field as a workplace. These are performance-driven athletes with identities shaped by the pathways they take to reach the top.

To illustrate, the annual AFL draft involves around 1,500 young hopefuls trying out for selection, with less than 10% getting an offer to join professional ranks.

So a measure of success is being selected and employed by a team and then staying on a club's active list for the longest period possible.

This brings us to the other point of difference—the very short average length of a player's career at the elite level.

According to the AFL Players' Association (AFLPA), the average length of a footballer's professional career is less than six years .

So in terms of financial rewards and sponsorship opportunities, this means making a living from perusing this dream is much shorter than the average worker, and athletes often do everything they can to keep playing—occasionally risking their health to do so. Sociologists call this the "sport ethic" , involving risk, pain and injury tolerance to win at all costs.

Sorry, but the dream might be over

With this context, receiving medical advice recommending early retirement must be devastating for an athlete .

Both the AFLPA and the Rugby League Players Association (RLPA) have developed support mechanisms to help athletes navigate the process in the event that retirement may be on the cards, recognizing the toll it can take on a player's mental health and well-being.

But what are the steps in the lead-up to a medical decision?

The player's first point of contact is typically a club doctor or other club-appointed health professionals. These health professionals are closely involved in assessing a player's fitness and use league-approved concussion and head injury assessment diagnostic tools and processes.

In 2019, the AFL adopted a process in which a panel of three medical specialists assesses a player and makes a recommendation to assist decision-making about future participation.

Triggered by a referral from the club doctor, each panel member examines and assesses the athlete. They see the player, review all notes from the team doctor, along with the player's medical history, reports and records, including scans and test results.

If required, further testing is done.

The panel aims to reach a medical consensus—all experts agreeing on the outcome, either recommending retirement or a follow-up. A consensus is important as it reduces the risk of an athlete "shopping around" to get a favorable result if they want to continue playing.

The model is similar to that in workers' compensation assessments but instead of assessing compensation, it's about assessing fitness to continue playing.

Medical and legal risks of continuing

The AFL's medical expert panel provides a recommendation to the player, but the ultimate decision rests with the athlete.

If the athlete chooses to ignore medical advice and continue to play, then there could be legal factors to consider for the player, their club and the club doctor.

As an employee of a club, an athlete is bound to comply with the legal obligations under the player's employment contract and the collective bargaining agreement.

A common obligation involves being fit to play and an obligation to follow medical advice from club doctors and club-appointed health professionals. If a player elects to continue to play despite medical advice to the contrary, they could be risking a breach of contract.

In the context of the club as an employer, workplace-related issues could arise in regard to obligations of health and safety processes and compliance.

For club doctors and clinicians, Michael Turner—medical director of The International Concussion and Head Injury Research Foundation—and colleagues developed a framework to assist clinician decision-making in complex cases.

But another legal issue to consider is the assumption of the risk—if a player ignores medical advice, they bear the responsibility and assume the risk of harm.

Creating a 'concussion smart' future

Murphy and the other brave players who tell their stories raise public awareness and help people understand that these are serious matters.

Instead of wearing a " badge on honor " to play on through injuries at the expense of future health, these athletes are playing a pivotal role in reshaping the narrative.

Their stories and willingness to publicly share the toughest of decisions deserve recognition, making a major contribution to Australia's "concussion smart" future.

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Low testosterone levels linked to higher risk of dying early, new research suggests

• A study of 24,109 men found low testosterone linked to a higher risk of early death.
• The findings suggest the hormone is an important indicator of health and longevity for men. 
• It's not clear whether hormone therapy boosts longevity but habits like diet and exercise can help. 

Testosterone levels may be an important indicator of longevity for men, new research suggests.

A study of more than 24,000 men from around the world found that low testosterone was linked to a higher risk of dying early, according to a study published May 13 in the Annals of Internal Medicine .

Researchers from the University of Western Australia worked with a global team of scientists to compare baseline testosterone levels to health outcomes using data from previous studies on older men, ranging in age from late 40s to mid-70s on average.

They found a higher risk of dying early, from any cause, among men with a low baseline testosterone level — defined as below 213 nanograms per deciliter (ng/dL). Healthy testosterone levels can range from 260 to 900 ng/dL depending on age, a urologist previously told Business Insider.

The analysis also found that men with very low testosterone levels (below 153 ng/dL) had a higher risk of dying from cardiovascular disease.

The findings are observational, which means the researchers found a pattern but didn't directly show that low testosterone causes a higher mortality rate.

Related stories

Still, the new study helps to shed light on mixed research around longevity and the hormone, particularly when it comes to boosting low testosterone with hormone therapy, an independent researcher wrote in an editorial published alongside the study .

Testosterone is a big deal in the longevity and biohacking field

The latest study focused on endogenous testosterone, the kind naturally occurring in the body, not hormone therapy. However, understanding how testosterone may help or hurt longevity could make big waves in the booming hormone therapy market of products and services advertised to help men reclaim their youth with pills, patches, injections, or gels.

Many of the entrepreneurs touting testosterone as an anti-aging panacea are also involved in biohacking , using science to try to optimize health and extend lifespan.

However, as yet, it's not clear whether supplementing testosterone will boost longevity , and there's some evidence to the contrary. The FDA previously issued a warning that testosterone-boosting treatments may raise the risk of heart attack or stroke, although subsequent research has since found no significant increase in heart problems.

Signs of low testosterone, and what to do about it

Testosterone levels tend to drop with age and can also dip in response to health conditions and medications.

Low testosterone can cause symptoms such as fatigue, brain fog, and disruptions in mood and libido.

Lifestyle factors such as eating a nutritious diet, getting enough exercise, and managing stress are linked to healthy testosterone levels and can also play a role in preventing heart disease and other chronic conditions.

Treatments like hormone replacement therapy via pill, injection, gel, or patch can help raise testosterone to normal levels. However, medical supervision is key to avoid any unexpected side effects of changing hormone levels, doctors previously told Business Insider.

• Main content

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