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  • The core business of medical technology companies (MedTechs) has been manufacturing and marketing physical devices
  • Physical devices will continue to be a substantial part of their business, but on their own, are unlikely to deliver high growth rates, which are more likely to come from artificial intelligence (AI) data driven strategies that improve patient outcomes
 
The impact of big data, artificial intelligence, and machine learning on the medical technology industry
 
James Carville, an American strategist, who played a leading role in Bill Clinton winning the 1992 presidential race, insisted that the campaign focus on the economy and coined the phrase “It’s the economy, stupid”. If Carville was asked today for a winning long-term growth strategy for medical technology companies, might he say, “It’s big data, stupid”?
 
This Commentary suggests that while physical products have been the backbone of MedTech companies in the past, they are unlikely to contribute significantly to future growth rates, which are more likely to come from artificial intelligence (AI) driven big data innovations, which create new solutions that improve patient journeys and outcomes.
 
In this Commentary
 
This Commentary describes the meaning of ‘big data’ in a healthcare context, explains ‘the data universe’ and stresses not only its immense volume, but also its variety, and the phenomenal speed at which the data universe is growing. Today, most industries leverage big data and AI techniques to create innovative offerings that drive growth and enhance competitive advantage. However, with few exceptions, traditional MedTechs have been relatively slow to collect and analyse a wide range of health, medical and lifestyle data which have the potential to provide innovative software offerings that improve patients’ therapeutic journeys and complement physical products. This is partly because the industry must adhere to strict regulations and partly because many medical technology companies lack the necessary capabilities and mindsets to collect and leverage big data. Most have business models that tweak legacy physical products and accept growth rates of ~5% as the ‘new normal’. We provide a brief history of big data and AI business strategies mainly to underline that these are relatively new. It was only in the early 2000s that electronic health records (EHR) began to replace paper-based patient records, which were stored in numerous filing cabinets in healthcare silos. It was not until ~2015 that EHRs became standard practice and researchers started to apply algorithms to EHRs and other data to detect patterns and make predictions that could improve diagnoses and treatments, enhance patient outcomes, and reduce healthcare costs. The increased use of big data and AI techniques in healthcare raises important cybersecurity concerns and trust issues because health professionals and patients do not understand how algorithms arrive at their conclusions and actions. Cybersecurity concerns are addresses by a range of encryption techniques and security protocols. Trust in algorithms has been helped by the development of  ‘explainable AI’, which is software that describes the essence of algorithms in easily understood terms. However, more work is still needed in these two areas. We introduce cloud and cloud services together with an explanation why these have experienced such rapid growth across all industries in recent years. The cloud makes it easier to store and access big data via the internet from anywhere in the world. Cloud services provide security for big data as well as a range of management and analytical tools that help to transform data into revenue generating software offerings. For MedTech companies, the cloud and cloud services provide the basis for more efficacious R&D. The medical technology industry has become bifurcated between companies that leverage AI driven big data strategies to enhance growth rates and those that predominantly focus on legacy physical product offerings and settle for lower growth rates. Over the past decade the nature of the medical technology industry has changed; partly because of AI big data strategies supported by the cloud computing and a large and rapidly growing range of open-source, easy-to-use AI tools. This has given small companies a competitive advantage. The Commentary concludes by describing a few of these small MedTechs with disruptive digital products that target large, rapidly growing, underserved market segments.       
 
Big data and healthcare

Big data are comprised of a wide range of information collected from multiple sources that surpasses the traditionally used amount of storage, processing, and analytical power and is unmanageable using conventional software tools. In healthcare settings, big data include hospital records, medical records of patients, results of medical examinations, and data generated by traditional medical devices as well as various biomedical and healthcare tools such as genomics, wearable biometric sensors, and smartphone apps. Biomedical research also generates data relevant for the medical technology industry.
 
The data universe

The massive amount of data, which is generated from the entirety of the internet is referred to as the ‘data universe’. It is not only its volume that makes this special, but it is also the variety of the data and the phenomenal speed at which the universe is growing. The International Data Corporation (IDC) estimated that the data universe grew from ~130 exabytes in 2005 to >40,000 exabytes in 2020.  To put this in perspective: 1 gigabyte of data is 1bn bytes (18 zeros after the 1 or 230 bytes), and 1 exabyte is equal to 1bn gigabytes.
Data generated healthcare innovations

In the past, collecting and interpreting vast quantities of data was not feasible, partly because computer systems were relatively small and did not generate much data, and partly because technologies to manage big data were underdeveloped. Fast forward to the present, and businesses across most industries now generate enormous amounts of data. Organizations apply AI and machine learning (ML) techniques to these data to create innovative product offerings to access new revenue streams with significant growth potential. Such technologies, combined with health-related big data, can positively impact the medical technology industry by generating novel diagnostics and treatments for patients, streamlining the process of medical record keeping and developing more personalized and responsive care plans that improve patient journeys and outcomes.

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The new rapidly evolving AI data driven healthcare ecosystem

Despite the potential commercial advantages of AI data driven diagnostic and therapeutic solutions, many traditional MedTechs have been slow to collect health and lifestyle data from multiple sources to develop software offerings, which complement their legacy physical products. One notable exception is Philips Healthcare. In the early 2000s, the company was challenged by new entrants to the market who were successfully leveraging information from health wearables and other sources to create and market AI data driven offerings. At the 2016 annual conference of the American Healthcare Information and Management Systems Society (HIMSS) in Chicago, Jeroen Tas, a Philips executive, said, “We are in the midst of one of the most challenging times in healthcare history, facing growing and aging populations, the rise of chronic diseases, global resource constraints, and the transition to value-based care. These challenges demand connected health IT solutions that integrate, collect, combine, and deliver quality data for actionable insights to help improve patient outcomes, reduce costs, and improve access to quality care”.
 
Philips had the mindset and resources to respond positively to this rapidly changing ecosystem. In 2017 the company appointed Tas as its Chief Innovation & Strategy Officer, tasked with launching a suite of big data AI driven solutions, the IntelliVue® patient monitors, which support the growing demands of health professionals to provide quality care and improved outcomes for an expanding population of older, sicker patients with fewer resources. These monitoring solutions seamlessly connect big data, AI technology and patients to support health professionals to manage patients as they transition through their care journeys. In 2016, Philips and Masimo, a medical technology company specializing in non-invasive AI data driven patient monitoring devices, entered a multi-year business partnership involving both companies’ innovations in patient monitoring. Philips agreed to integrate Masimo's measurement technologies into its IntelliVue® monitors, to help clinicians assess patients’ cerebral oximetry and ventilation status. The outcome of the collaboration was the launch of a new suite of patient solutions, called Connected Care, which give healthcare providers the ability to monitor patients more effectively and reduce costs.
 
The bifurcation of the MedTech market

In addition to large MedTechs such as Philips and Masimo, there are hundreds of small companies developing AI driven big data offerings aimed at improving patient outcomes. The reasons for many traditional companies’ slowness to fully leverage big data and AI applications are partly because medical devices are required to comply with stringent regulatory guidelines and partly because of the lack of capabilities. The different responses have bifurcated the industry. On the one hand there are traditional MedTechs, which predominantly focus on existing customers and market legacy physical offerings in slow growing markets. On the other hand, there are many small companies and a few very large medical technology corporations, which have embraced AI driven big data patient-centric solutions.
 
A brief history

Big data has its genesis in the 1950s and 1960s when scientists and mathematicians began exploring the possibility of using computers to process large amounts of data to make intelligent decisions. This led to the development of technologies such as the first neural networks, which laid the foundation for modern Deep Learning. In the 1980s, researchers at IBM popularized the concept of big data to describe the process of collecting and analyzing large amounts of data, which empowered organizations to gain insights from information that previously was too complex to process. The 1990s saw the development of AI and ML, which enabled computers to learn from data and make decisions without the need for explicit programming. By the early 2000s, AI-based algorithms empowered machines to learn from data and make predictions. Many organizations, across a range of industries, saw the commercial opportunities of this and acquired capabilities to collect, store and analyse large amounts of information to identify patterns and trends that were previously impossible to detect.  Without large amounts of data, AI and ML techniques are less effective, which is significant for healthcare and the medical technology industry.
 
Big data in healthcare

AI driven big data strategies are becoming increasingly important in healthcare. This is because AI techniques applied to masses of health-related information can improve patient care, enable more effective decision-making, reduce costs, identify new treatments, explore new markets, and create more efficient healthcare systems. Further, such applications can provide more accurate and timely diagnoses, as well as insights into how various treatments affect different people. As increasing amounts of health information become available, and data handling techniques improve, so traditional MedTech companies will have opportunities to boost their growth by complementing their physical devices and volume-based care with digital assets and personalised care.
 
Paper-based mindset

Until recently health professionals were responsible for most of the different types of data associated with a patient’s treatment journey, which included medical histories, known allergies, medical and clinical narratives, images, laboratory examinations, and other private and personal information. Until the early 2000s these data were recorded on paper and stored in filing cabinets across numerous healthcare departments. It was not until 2003 that the US Institute of Medicine used the term ‘electronic health records(EHR). By 2008, only ~10% of US hospitals were using EHRs, which increased to ~80% by 2015. As EHRs became standard practice across multiple providers and data interoperability issues were resolved, the provision of healthcare improved, and medical errors and healthcare costs were reduced. Currently, the American National Institutes of Health (NIH) is inviting 1m people from diverse backgrounds across the US to help build a comprehensive big data set, which can be used to learn more about how biology, environment and lifestyles affect health in the expectation of discovering new ways to treat and prevent disease.
 
Trust and medical algorithms
 
As AI driven big data applications have increased, so trust in algorithms has been raised as an issue. This has been a major concern in healthcare. To address this challenge, explainable AI, has been developed. This is an AI technology that explains decisions and actions made by algorithms in a way that is easily understood by health professionals and patients. Explainable AI has helped to create trust in algorithms by providing a level of transparency, understanding and accountability. Further, incorporating feedback from medical professionals, patients, and other stakeholders into the development of medical algorithms has also helped to build trust. However, this entails collecting a wider variety of data than many healthcare companies are used to.
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Have diversified medical technology companies blown their competitive advantage?
Big data healthcare strategies and security
 
With the increasing number of big data and AI healthcare solutions, cybersecurity has become a concern. Reducing this involves using technologies such as data encryption, secure cloud computing (see below), and authorization protocols to protect data stored in large databases. Additionally, organizations may use AI-driven applications to monitor their systems to find anomalies, detect malicious activity and unauthorized access to sensitive, personal information. To ensure the security of healthcare data, organizations also employ measures such as risk assessments, incident response plans, and regular security training of their staff.
Cloud storage and services

Since the early 1990s, big data have benefitted from cloud storage, which makes it easier to store and access data over the internet and helps businesses to become more efficient and productive. It also offers organizations scalability, more control over their data and reduced costs. Organizations can: (i) easily increase their storage capacity as their data needs grow, (ii) access their data from anywhere in the world, and (iii) stop investing in expensive local storage devices. Further, cloud storage is becoming more secure, with encryption and other security measures making it safer to store data.
 
Companies moving their data from local storage devices to the cloud is more than just a simple transfer process and can be a complex, multi-year journey. Any organization that has accumulated several legacy databases and infrastructures will have to develop and manage a hybrid architecture to transfer the data. However, once in place and shared among stakeholders, cloud-based platforms can assist in unlocking clinical and operational insights at scale while speeding up innovation cycles for continuous value delivery. In combination with a secure and interoperable network of connections to hospital systems, cloud-based solutions represent an opportunity for healthcare leaders to unlock the value of data generated along the entire patient journey, from the hospital to the home. By turning data into insights at scale, it is possible to empower healthcare professionals by helping them to deliver personalized care, improved patient outcomes and lower costs.
 
The cloud also offers an increasing number of computing services. These are provided by companies such as Amazon Web Services, Google Cloud Platform, Microsoft Azure, IBM Cloud, Oracle Cloud, and Rackspace Cloud. The services include: (i) Infrastructure-as-a-Service (IaaS), which provides users with access to networks, storage, and computing resources, (ii) Platform-as-a-Service (PaaS) helps users to develop, run, and control applications without the need to manage infrastructure, (iii) Software-as-a-Service (SaaS), provides access to a variety of applications, (iv) Data-as-a-Service (DBaaS), gives users access to several types of databases, and (v) Serverless Computing enables users to run code without needing to provision or manage servers. Such services are expected to continue growing and help to transform healthcare. The provision of cloud computing services in healthcare makes medical record-sharing easier and safer, automates backend operations and facilitates the creation and maintenance of telehealth apps. The increasing use of data and cloud services by MedTech companies helps to break down data silos and develop evidence-based personalized solutions for a connected patient journey. In 2020, the healthcare cloud computing market was valued at ~US$24bn, and it is expected to reach ~US$52bn by 2026, registering a CAGR of >14% during the forecast period. Major drivers of cloud services include the increasing significance of AI driven big data applications.
 
Changes the nature of R&D

Further, the cloud can change and speed up R&D. The starting point for MedTech R&D should be evolving patient needs and affordability. Healthcare-compliant cloud platforms offer a flexible foundation for the rapid development and testing of AI driven big data solutions created by cross functional teams working across an entire life cycle of an application: from development and testing to deployment. This changes medical technology companies’ traditional approach to R&D by transforming it into short cycles undertaken by multiple stakeholders. This modus operandi is replacing traditional lengthy and expensive R&D often carried out in an organisational silo and constrained by annual budgeting cycles. This often means that a significant length of time passes before an innovation gets into the hands of health professionals and patients for testing. Digital health solutions, on the other hand, can be tested by physicians and patients early in their development and improved features quickly added.   
 
Free and easy to use AI and ML software libraries

In the early 2000s, when AI and ML were in their infancy, companies needed data engineers with advanced mathematical capabilities to build complex AI systems. Today, this is unnecessary because of the development of simplified AI and ML libraries such as PyTorch and Tensorflow. These are free, easy to use, open-source, scalable AI, and ML packages, which reduce the need for data engineers to have advanced mathematical skills to build effective software health solutions. PyTorch, released in 2016,  was developed by Facebook and then Meta AI, and is now part of the Linux Foundation. The technology is known for its ease of use and flexibility, making it favoured by developers who want to rapidly prototype and experiment with new ideas. Its tools support graphics processing, which is popular with deep learning medical imaging strategies that involve training large, complex models on big data. TensorFlow was developed by the Google Brain team and originally released in 2015 for internal use.  It is a highly scalable library for numerical computations and allows its users to build, train and deploy large-scale ML models. Both platforms have become significant open-source tools for AI and ML due to their ability to support the development and training of complex models on large datasets. They have been widely adopted by researchers and developers throughout the world and are regularly used in a variety of applications relevant to the medical technology industry. Significantly, they give smaller MedTechs a competitive advantage. 
 
Disruptive effects of AI driven big data strategies

The development and availability of big data and predictive AI help small medical technology companies enter markets, grow, and strengthen their competitive positions, which has the potential to change market dynamics. Over the past decade, several large medical technology companies have experienced their markets dented by small companies, which have successfully used open-source AI applications to leverage big data. For example, Philips Healthcare’s market was affected by the emergence of innovative offerings developed by new entrants using cloud computing services and big data from medical wearables. Above we described how Philips robustly responded to this and became a market leader in AI data-driven patient monitoring technology. Siemens Healthineers’ market share suffered from small MedTechs with innovative AI driven offerings. Further, the rise of digital imaging technology caused GE Healthcare’s market share to shrink. These vast companies have since developed AI driven big data strategies and bounced back. However, traditional MedTechs that fail to leverage big data and AI capabilities risk being left behind in an increasingly competitive digitalized industry.
 
Small MedTechs using big data and AI

Examples of small MedTechs that leverage big data, AI, and ML techniques to capture share of large underserved fast-growing market segments include Brainomix, which was spun out of Oxford University, UK, in 2010 and serves the stroke market. Iradys, a French start-up specialising in interventional neuroradiology. Elucid, a Boston, US-based MedTech founded in 2013, which has developed innovative technology that supports the clinical adoption of coronary computed tomography angiography, and Orpyx Medical Technologies, a Canadian company that provides sensory insoles for people living with diabetes. These are just a few examples of small agile companies that collectively have helped to bifurcate and disrupt segments of the medical technology industry by developing offerings predicated upon big data, AI and ML that deliver faster, more accurate diagnoses to ensure that patients get the treatment they need, when they need it.

Brainomex’s lead product offering is a CE-marked e-Stroke platform, which has been developed using data from images sourced across 27 countries including the UK, Germany, Spain, Italy, and the US and provides fast, effective and accurate analysis of brain scans that expedite treatment decisions for stroke patients. The platform has been adopted across multiple healthcare systems throughout the world, and for the past two years, England’s National Health Service (NHS) has been using the technology on suspected stroke patients. Early-stage analysis of the technology predicated on >110,000 patients suggests that eStroke can reduce the time between presenting with a stroke and treatment by ~1 hour and is associated with a tripling in the number of stroke patients recovering with no or only slight disability - defined as achieving functional independence - from 16% to 49%. With this disease, time is of the essence because after a stroke, each minute that passes without treatment leads to the death of ~2m neurons (nerve cells in the brain), which cause permanent damage. It can be challenging for health professionals to determine whether stroke patients need an operation or drugs, because the interpretation of brain scans is complicated and specialist doctors are required. Sajid Alam, stroke consultant at a large regional hospital in the UK, (Ipswich Hospital), reflected: “As a district general hospital, we don’t have ready access to dedicated neuroradiologists to interpret every stroke scan. Having Brainomix’s AI software gives us more confidence when interpreting each scan.

Intradys is a French start-up, which develops algorithms that combine ML and mixed reality to empower interventional neuroradiologists and help them enhance the care of stroke patients. Orpyx Medical Technologies provides sensory insoles for people living with diabetes who have developed peripheral neuropathy to help prevent foot ulcers. The insoles collect data on pressure, temperature, and steps and give feedback to the wearer and healthcare professionals. Elucid is a Boston-based MedTech founded in 2013. The company’s offerings are predicated on big data, AI, and ML to provide fast and precise treatments that improve the outcomes of patients with cardiovascular disease and reduce healthcare costs. Heart attack and stroke are primarily caused by unstable, non-obstructive plaque (the buildup of fats, cholesterol, and other substances in and on the artery walls) that often goes undiagnosed and untreated. Current non-invasive testing cannot visualize the biology deep inside artery walls where heart disease develops. Elucid’s lead offering is an FDA-Cleared and CE-marked non-invasive software to quantify atherosclerotic plaque.
 
Takeaways
 
The potential benefits for medical technology companies that leverage AI driven big data strategies include: (i) improved diagnoses and treatments, (ii) enhanced patient journeys and outcomes, (iii) cost savings, (iv) a better understanding of stakeholders’ needs, (v) superior decision-making, (vi) more effective products and services, and (vii) increased competitive advantage. Big data strategies may also be used to uncover insights from large datasets to develop predictive models that can automate repetitive tasks, optimize care processes, free up resources for healthcare professionals to focus on providing care, and staying ahead of the competition by providing greater insights into customer trends and needs. Medical technology companies that do not leverage AI driven big data strategies to develop innovative products for growth and competitive advantage potentially risk: (i) falling behind the competition in terms of product innovation, (ii) missing out on key market opportunities, as data-driven insights can help identify new trends and customer needs, (iii) struggling to keep up with the changing pace of technological change, as staying ahead of the competition requires a deep understanding of the latest developments in data-driven product development and (iv) losing the trust of customers, as they may be wary of MedTechs that do not use advanced technologies to develop their product offerings. Future significant growth for medical technology companies is more likely than not to come from AI driven big data strategies. Start collecting data.
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  • After decades of high growth and high valuations, large diversified medical technology companies (MedTechs) are faced with low growth and challenged to create long-term value
  • This is partly due to exogenous macroeconomic conditions and partly due to companies themselves eschewing broader strategic considerations and focussing on short-term performance
  • MedTechs’ past period of stellar performance benefited from company concentrations in large rapidly growing wealthy markets and benign fee-for-service business models that rewarded volume
  • During this time, large diversified MedTechs engaged in weak competition at a level of health plans, payers, and hospitals - an institutional level - and ignored competition at a patient level
  • Creating long-term future value for all stakeholders will require companies to compete at a patient level and accelerate the adoption of value-based care programmes that remunerate patient outcomes
  • To compete effectively at such a level requires vast amounts of patient data and sophisticated data handling and security capabilities, which many companies do not have
  • MedTechs that respond efficaciously to the rapidly evolving healthcare ecosystem and develop data and competences to compete at a patient level will have opportunities to create future long-term value  
  • Companies that continue with the status quo are likely to struggle to create long-term value and shall become acquisition targets
 
Have diversified medical technology companies blown their competitive advantage?
 
 
In the current fiscally constrained healthcare environment, creating long term value for medical technology companies (MedTechs) is challenging and many industry leaders have accepted ~5% annual revenue growth rate as the “new normal”. It has not always been like this. Between ~1990 and the late 2010s, medium and large diversified MedTechs were high growth, high value enterprises, which benefited from weak competition, large and rapidly growing underserved wealthy markets, barriers to entry, advancing medical technologies and benign fee-for-service business models that rewarded volume.
 
MedTechs’ recent decline in enterprise growth rates is partly due to worsening macroeconomic conditions, but a big part is due to companies themselves. Many became trapped in an outdated, narrow approach to creating value where a significant proportion of scarce corporate resources are focused on optimizing short-term financial performance. Albeit essential, this often meant that unmet market needs, and broader long-term strategic influences tended to be overlooked. We explore how this happened and what can be done about it.
 
In this Commentary

This Commentary describes how after ~3 decades of stellar growth many medium to large diversified medical technology companies (MedTechs) have become trapped in short-term performance-oriented cultures and struggle to create long-term value for all stakeholders. During their stellar years these companies operated at the level of payers, health plans and hospitals - an institutional level - where competition was, at best, weak, and patients’ therapeutic pathways largely ignored. Today, many diversified MedTechs struggle to create long-term value in the face of low growth rates, fiscal and regulatory constraints, vast and escalating healthcare costs, and increasing competition from giant tech companies and innovative start-ups. Further headwinds come from payers shifting away from benign fee-for-service payment models that reward volume to value-based care, which remunerates patient outcomes. To create long-term value MedTechs will need to radically change their strategies and business models. This will entail replacing legacy technology systems that hinder efficiency and innovation, tightening their security risks and improving their business process flows. If corporations do this efficaciously, they will be positioned to compete at a patient level where value is created and destroyed. However, competing at this level requires vast amounts of patient data and sophisticated data handling capabilities. Many companies neither have such data nor the capabilities to analyse and manage them. It seems reasonable to suggest therefore that, in the near- to medium-term, MedTechs that eschew retooling and competing at a patient level will struggle to create long-term value and likely become acquisition targets.
 
Structural challenges

As populations in wealthy economies age and shrink, due to increasing longevity and declining fertility, so healthcare headwinds increase and challenge MedTechs. Consider the US, which is an exemplar of most wealthy nations. Today, >56m Americans are ≥65, which accounts for ~17% of the nation's population. By 2030, when the last of the baby boomer generation ages into older adulthood, it is projected there will be >73m older adults, which means  >1 in 5 Americans will be of retirement age. As the American population ages a growing number of people present with age-related chronic conditions, which are costly to treat. Today, in the US, ~86% of people ≥65 is living with a chronic disease. This increases the risk of insuring the average US citizen, and the higher the risk, the higher the cost of annual health insurance premiums. According to the Centers for Medicare & Medicaid Services, in 2020, the US national health expenditure (NHE) grew ~10% to ~US$4trn, which equates to ~US$12,530 per person, and ~20% of the nation’s Gross Domestic Product (GDP). By 2030, US NHE is expected to reach ~US$7trn.
 
In 2020, Medicare spending rose by 3.5% to ~US$830bn or ~20% of total NHE. In the same year, Medicaid spending grew by 9% to ~US$671bn, or ~16% of total NHE. The largest shares of America’s total health spending are provided by the federal government (~36%) and households (~26%).  The private business share accounts for ~17%, local state governments account for ~14%, and other private revenues account for ~6.5%. According to the 2022 annual Kaiser Family Foundation (KFF) healthcare survey the average insurance premium for family healthcare coverage in the US increased 20% over the previous 5 years and 43% over the past decade. The average premiums for employer-sponsored health insurance are US$7,911 for single coverage and US$22,463 for family coverage.
 
Such changes are forcing the medical technology industry to adjust what products and services it develops and how value is created.
 
Stellar growth and short-term performance

During ~3 decades before ~2015, the medical device industry benefitted from unmet clinical needs, significant barriers to entry, technological advances, benign fee-for-service payment systems that reimbursed volume and industry concentrations. During this time MedTechs enjoyed stellar growth, and high valuations. Investors prioritized revenues over profit and cash flow, which encouraged enterprises to engage in portfolio moves: M&A, divestitures, and spin-offs. This had the advantage of helping companies to exit low-growth businesses and enter higher-growth segments, without engaging in years of uncertain and expensive R&D. It had the disadvantage of encouraging short-term performance rather than long-term value creation. During this period many senior leadership teams became weighed down with the demands of quarterly reporting and grew accustomed to using a variety of short-term accounting measures and ratios as their principal means to drive business and reward executives.
 
As a result, ‘successful’ medical technology companies had high growth rates but a deficit in ideas to unlock transformative new treatments for underserved patients and plans to seize opportunities presented by technological advances. The industry’s indifference to develop and leverage digitalization is indicative of corporations overlooking broader strategic influences and unmet market needs. Consequently, by ~2015, many large diversified MedTechs had fragmented technology systems that hindered efficiency and innovation and were overburdened by legacy products overexposed in slow growth markets. This made them ill-equipped to either respond quickly to innovative trends or compete with disrupters. According to a McKinsey & Company report published in June 2022, “84% of CEOs believe that innovation is critical to growth, but only 6% are satisfied with their company’s innovation performance”. To survive and stand a chance to create long-term value MedTech functions from R&D to sales will need to change.
Slow response to market changes

As MedTechs’ performance slowed and executives accepted ~5% growth as the “new normal”, markets continued to evolve: consumer-centred healthcare increased, clinical procedures moved out of hospitals into daycare centres and homes, regulation tightened, international markets expanded, medical technology continued to advance at pace, and tech giants and new entrants disrupted healthcare markets with innovative solutions and digital platforms that served patients rather than surgeons and hospitals. Because of MedTech companies’ lack of preparedness to respond positively to such changes, many doubled down on their traditional business models. This meant their M&A ecosystems were kept intact and active, and R&D continued with incremental additions to legacy products that mostly served the needs of surgeons and hospitals rather than patients.
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According to the Center for Studying Health System Change, the prominent trend of M&A in America’s healthcare industry increased consolidation and decreased competition, which is critical for lowering costs and improving productivity and innovation. With weak competition providers and insurers were able to drive up their prices unopposed. Findings of a study published in the American Journal of Managed Care found that hospitals in concentrated markets could charge considerably higher prices for the same procedures offered by hospitals in competitive markets. Although price increases often exceeded 20% when mergers occurred, studies suggest such increases neither improved healthcare quality nor patient outcomes.
 
With MedTechs focussed on consolidations and increasing the prices of their legacy offerings as a way of maintaining and increasing their revenue growth rates, many failed to keep current with the accelerating pace of technologies that were transforming healthcare. For example, over the three decades of stellar growth in the medical device industry, digitalization improved customer experience, connected devices, integrated, and leveraged external data sources and patients’ electronic health records, and connected with other stakeholders. This changed the way patients were diagnosed and treated, changed the way healthcare professionals communicated and collaborated, and changed how biomedical research was conducted. Notwithstanding, MedTechs were reluctant to digitize and continued to employ outdated labour-intensive business processes to market their product offerings. Today, providers, payers and patients are increasingly demanding digital solutions that are easier to use and more cost effective. This presents a challenge for traditional medical technology companies slow to adapt their business models to meet the needs of changing market conditions.  

 
The impact of Covid-19

The medical technology industry, along with many others, was adversely impacted by the Covid-19 crisis. In 2020, most medium to large MedTechs saw their revenues drop significantly. During lockdowns many experienced reductions in sales mobility, changed purchase demand profiles, supply chain disruptions, and increased risk aversion towards unnecessary spending. Such headwinds prompted some companies to re-evaluate their business models and set new directions for future success. This included digitally enhancing existing products, unlocking customers in new geographies, and monetizing data from existing devices to create new patient-centred solutions. Notwithstanding, today many MedTechs with reduced growth rates struggle to create long-term value for all their stakeholders.
 
There is no single answer to how value might be achieved as strategies will vary depending on specific industry segments and specific product offerings. However, some general suggestions include: (i) continue portfolio moves to divest low growth legacy products and reduce risk pathways to innovative offerings and growth. Target acquisitions with healthy growth prospects, well-stocked innovation pipelines and product offerings positioned to benefit from leveraging larger company infrastructures,  (ii) establish a pro-active venture function aimed at early-stage companies with disruptive offerings, (iii) invest in R&D to create new products and services that enhance patients’ therapeutic journeys, (iv) look beyond core devices and increase digital offerings and capabilities as software and digital solutions have become an essential part of patient journeys and clinical practice, (iv) shift away from volume-based care and accelerate value-based care to improve patient outcomes and reduce costs.
 
Value-based care

Healthcare experts have suggested that the fee-for-service healthcare payment model is wasteful, outmoded and partly responsible for US healthcare spending being significantly higher than other Western nations, but with patient outcomes no better and often worse. During the past two decades health plans, payers, employers, and patients have been requesting that healthcare systems deliver on value. The market responded to this with a shift towards value-based care, which instead of rewarding volume, pays providers based on patient-centric health outcomes. According to America’s Health Care Payment Learning & Action Network’s (LAN) annual survey; >60% of US healthcare payments in 2020 included some form of value component, which is up from ~53% in 2017 and ~11% in 2012. Similarly, 49% of primary care practices responding to the American Academy of Family Physicians (AAFP) 2022 Value-Based Care Survey said they are participating in some form of value-based payment, and 18% are developing the capabilities to do so.

Much of the energy for value-based care comes from America’s Affordable Care Act (ACA), (“Obamacare”), which is the most significant regulatory overhaul and expansion of healthcare coverage since the enactment of Medicare and Medicaid in 1965. The 2010 Act was originally developed to help reduce the rate of hospitalizations and readmissions by focussing on quality outcomes rather than quantity of patient visits. Value-based healthcare concepts have grown, and the ACA has created new incentives and penalties designed to encourage providers to deliver higher quality care at lower costs. These include the Hospital Value-Based Purchasing Program, which ties Medicare reimbursement to hospital performance on a set of quality measures, and the Medicare Shared Savings Program, which rewards provider groups for achieving cost savings while meeting agreed quality targets. The Centers for Medicare & Medicaid Services (CMS) supports value-based care as part of its “larger quality strategy to reform how health care is delivered and paid for”.
Omar Ishrak and value-based care
 
Omar Ishrak, CEO and chairperson of Medtronic plc  between 2011 and 2020, championed value-based care by incentivizing and leading discussions about how MedTechs should align value and price and how suppliers should get paid according to patient outcomes. He believed “[clinical] value has to be tied to economic value, otherwise people will not be able to afford the care we provide”. Before joining Medtronic, Omar Ishrak was the head of GE HealthCare and was well-versed in global politico-economic challenges associated with markets with a deep understanding of the human toll that comes from inadequate healthcare systems. “We live in a world where we get paid for our technology with a promise to improve outcomes, not a guarantee, a promise”, said Ishrak. While at Medtronic he extended value-based healthcare by insisting that efficacy is aligned with patient expectations and MedTechs get paid for medical outcomes rather than medical devices. He was convinced that value-based care incentivises MedTechs to develop and deploy products, services, and solutions, which improve patient outcomes per dollar spent, and measure value in terms of long-term patient outcomes rather than short-term transactions.

In 2016 Medtronic established a value-based care partnership with UnitedHealthcare, an American multinational managed healthcare and insurance company, which gave its customers living with diabetes access to Medtronic’s insulin pump and support services. After the first year, the partnership reported ~27% decline in the rate of preventable hospital admissions compared to patients using traditional daily insulin injections. Between 2015 and 2018, UnitedHealthcare's payments to physicians and hospitals tied to value-based care programmes were reported to be ~US$65bn and projected to grow to ~US$75bn within two years.

In February 2018, Medtronic signed a 5-year value-based care partnership with Lehigh Valley Health Network, (LVHN) based in Allentown, Pennsylvania. The two organizations established processes to treat more than 70 medical conditions using Medtronic devices to improve patient outcomes and cut costs. The endeavour reached ~0.5m patients in Northeast Pennsylvania and cut the cost of care by ~US$100m. Another benefit of the partnership was Medtronic obtained access to thousands of patient insights to their products, which the company used to establish baselines to monitor and improve outcomes. Another example of Medtronic linking a product directly to outcomes is its Tyrx Absorbable Antibacterial Envelope, a mesh used to hold pacemakers and implantable cardioverter defibrillators (ICD) in a stable environment and release antimicrobial agents over a period when the chance of infection related to surgery is high. These are just a few examples of devices that Ishrak linked to value-based payment schemes, there are many others. Cumulatively they “had a real differentiating value for Medtronic”, said Ishrak.

Although manufacturers of medical devices were slow to follow Ishrak’s example, the economic slowdown has led to a heightened cost-consciousness among healthcare providers and accelerated a shift towards value-based care and a growing influence of healthcare group purchasing organizations (GPOs). This, in turn, has incentivized MedTechs to increase their M&A activity to expand their portfolios and allow them to provide high-volume, discounted product bundles. Furthermore, value-based care has moved purchasing decisions away from physicians toward hospital administrators, who are more focused on costs than devices and their features. This has resulted in a downward pricing pressure across the MedTech landscape and rendered market entry more challenging for small companies, which provides large diversified MedTechs with further potential acquisition targets.
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Low Back Pain and the global spine industry


 
Spinal surgery and value-based care
 
A segment of the medical technology industry that looks ripe to benefit from value-based care is spinal surgery for low back pain (LBP), which is a common age-related health condition associated with degenerative spinal disorders. According to the World Health Organisation (WHO), LBP is one of the top ten global disease burdens and ~80% of all individuals will experience the condition at some point in their lifetime.
In the US, ~3 in 10 adults - ~72m - currently suffer from chronic LBP.  Each year, ~0.3m people present with LBP but only ~0.7-4.5% of these will have specific identifiable causes for their condition. This is because LBP is challenging to diagnose as there is no established protocol to evaluate the condition and it may be a symptom of many different causes. Notwithstanding, American third-party payers have tended to reimburse spine surgery for LBP more than non-invasive therapies, but this is changing.  America has the highest rate of spine surgeries in the world, and each year, clinicians perform ~1.6m spinal fusions in an attempt to cure LBP. Between 2004 and 2015, the volume of spinal fusions increased by 62% and aggregate hospital costs increased ~177%, exceeding US$10bn in 2015, and averaging >US$50,000 per admission. A 1994 international comparative study found that, “the rate of back surgery in the US was at least 40% higher than in any other country and was more than five times that in England. Back surgery rates increased almost linearly with the per capita supply of orthopaedic and neurosurgeons in the US”.
 
A significant percentage of patients with LBP continue to experience pain after surgery, which is referred to as ‘failed back syndrome’ (FBS) and is characterized by an inability to return to normal activities. A study reported in the American Journal of Medicine suggests that recurrent spine surgeries do not necessarily mean success. Notwithstanding, when a primary surgery fails to cure LBP, a significant percentage of patients have further surgeries. However, with each recurrent surgery the probability of a successful outcome drops: ~50% success rate after the first repeat surgery, ~30% after the second, ~15% after the third and ~5% after the fourth.
 
Research published in theBritish Journal of Pain, suggests that the overall failure rate of lumbar spine surgeries is between ~10 and 46%. A study reported in a 1992 edition ofSpine, followed 53 patients for an average of 20 months after a spinal fusion surgery and found that only 50% reported improved outcomes. Another study, published in the journal Trials, suggests that ~40% of lumbar fusion patients experience ongoing back pain and limited function two years after surgery; and research findings published in the Asian Spine Journalfound ~5 and 36% of people who undergo a discectomy for a lumbar herniated disc saw their leg and back pain return two years after surgery.
 
Such failure rates have prompted health insurers in the US to reassess their fee-for-service payment policies.According to a New York Times article,  reimbursements for spine surgeries are becoming tighter, and “financial disincentives accomplished something that scientific evidence alone didn’t”. The  article draws on research published in the journal Spinewhich found that, “spinal fusion rates continued to soar in the US until 2012 and shortly afterwards Blue Cross of North Carolina said it would no longer pay for such surgeries”. It seems reasonable to assume that benign fee-for-service reimbursement policies are partly responsible for the increase in spine surgeries that fail to cure LBP. Following the Blue Cross decision other insurers followed, and US payers started to move away from fee-for-service models towards  reimbursing “value. This transfers the costs of over-treatment, revision surgeries and adverse clinical outcomes from payers to providers and is expected to utilize resources more efficiently. Such shifts are beginning to happen in all the major medical technology markets. For example, in Europe fiscal pressure on healthcare systems has meant rationing and/or delaying elective spine surgeries, and in Japan more spine surgery costs are being shifted to employers and patients.
 
Given the changing ecosystem in the spine market, a potential opportunity for MedTechs might be to apply machine learning AI techniques to patient data in an endeavour to determine what products and procedures are most likely to produce optimal solutions for individuals contemplating spine surgery for LBP. Assuming enough relevant data are collected, and successful algorithms developed, this process might help to reduce the high failure rates of spine surgeries for LBP, improve patient outcomes and lower healthcare costs.

 
Weak competition at the wrong level

Value-based care has the potential to: (i) improve patient outcomes by incentivising providers to focus on the quality of care, (ii) create a more efficient healthcare system by eliminating wasteful spending, (iii) improve patient satisfaction by making the healthcare system more patient-centered, (iv) make it easier for enterprises to commercialize new products and services by providing a pathway to reimbursement, and (v) provide a platform for companies to partner with other healthcare stakeholders to improve care delivery and patient outcomes.
 
However, MedTechs are not well positioned to transition expeditiously to value-based care. This is because, for decades they have benefited from a benign fee-for-service business model and participated in weak competition at an institutional level: the level of health plans, providers, and hospital groups. Competition at this level is weak and neither creates value nor benefits patients. This is because the principal actors behave as if playing 'pass the parcel', i.e. shifting costs onto one another, restricting services, stifling innovation, and hoarding information.
 
In the medical technology industry value can only be created or destroyed by competition at a patient level, but this has been absent throughout the history of the industry. Because of this deficit company costs are high and rising, services are restricted, clinical procedures overused, standards of care often fail to adhere to clinical guidelines, diagnosis errors are common, quality and cost differences persist across providers and geographies, best practices are slow to spread, and innovation is resisted. In most other industries such outcomes are inconceivable.
 
The future for MedTechs must be at a patient level where costs and quality persist and where competition can drive improvements in efficiency and effectiveness, reduce clinical errors and incentivize innovation. Notwithstanding, competition at this level requires devising patient outcome measures for specific devices and procedures that are acceptable to all industry stakeholders. Data are essential to develop such measures and may be provided by surveys, electronic health records, personal devices and clinical studies or a combination of all four. However, the analysis and utility of such data require sophisticated data handling and security capabilities, which many MedTechs do not have. Companies that successfully re-tool and become eloquent at competing at a patient level will be well positioned to create long-term value for all stakeholders. Companies that fail in these endeavours will likely become targets for acquisitions.
 
Takeaways

MedTech companies have become trapped by their former commercial success and legacy structures and operating models that were neither set up to respond quickly to innovative trends nor to compete with disrupters. For ~3 decades high growth rates and valuations persisted in the medical technology industry despite companies ‘competing’ weakly at the wrong level and their cultures being defined by short-term financial performance. Such entrenched business models and the time and resources they consumed did not leave room for broader in-depth strategic considerations that could influence long term value creation. Today, MedTechs are at a crossroad: they can either change their strategies and business models and compete at a patient level or they can continue their weak competition at an institutional level. The former positions companies well to create long-term value for all stakeholders while the latter does not.
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"When you fail to reach your goals don’t adjust your goals, adjust your actions"
 
On Saturday 20th October 2022, the Chinese Communist Party (CCP) ended its twice-a-decade Congress. It amended its charter and elected Xi Jinping for a historic third 5-year term, making him China's most powerful ruler since Mao Zedong, the founding leader of the People's Republic. Given these outcomes, followers of HealthPad suggested we re-publish the Commentary, ‘Learn from the Chinese, but don’t misjudge Beijing’, which we do below. The Commentary describes the tightening of China’s regulatory and competitive environments and suggests that Western corporations, with interests in China or thinking of entering the Chinese market, should not underestimate: (i) the large and growing differences between China and the US, and (ii) the CCP’s uncompromising ambition to become economically self-reliant, a world superpower and a global high-tech leader.

Deteriorating East-West relationships
Xi Jinping used the Congress to tighten his hold over the CCP by evicting all remnants of factional opposition, placing political allies in key positions and establishing complete control over the Party and the country. Xi re-emphasized the significance of making science and technology cornerstones of China’s strategy for national economic and military “self-reliance”. He also hinted that China will further decouple its economic links with the US and Europe and increase market restrictions on Western companies trading in China. With Xi’s increased authority and China’s increased global power and influence, it seems reasonable to assume that, in the near-term, China is likely to develop a more aggressive foreign policy, and the US and its Western allies will doubtless respond with a more confrontational approach to China. This significantly raises the possibility that East-West geopolitical relationships will deteriorate further.
 

Guanxi
China and the Chinese are different to the West and Westerners. Whereas most Western nations, have a deep sense of individualism based on democracy with social and political freedoms, China and the Chinese are rooted in Confucian collectivist principles with a top-down hierarchical structure that views individuals as part of a community with ordered and friendly relationships. This is perhaps best understood by the Chinese term, ‘Guanxi’ (关系), which refers to tacit mutual commitments, reciprocity, and trust, and is central to all personal, business, and politico-economic relationships.

China’s ambition
None of China’s renewed global posturing should surprise Western corporate leaders with their fingers on the pulse of their international strategies. For decades China has been increasing its power and influence in the world. In his 2017 report to the 19th Party Congress, Xi Jinping stressed the decline of America’s  international authority and the “substantial and rapidly growing” global power and influence of China. He predicted that, by the mid-21st century, China will have become “a global leader in terms of comprehensive national power and international influence,” and will be a development model for the world.

The past 5-years
Also in 2017, Xi advocated a more aggressive and activist Chinese foreign policy, and over the ensuring 5 years, Beijing has: (i) weakened foreign enterprises trading in China and raised the bar for new entrants, (ii) strengthened Chinese domestic companies and incentivized them to trade internationally, (iii) ratcheted-up pressure on Taiwan, (iv) exerted greater control over Hong Kong, and (v) increased China’s rhetoric and tactics in defence of its interests.
 

Business-as-usual versus strategically active
Over the past 3 decades, China has strategically invested in innovation-driven development, which has helped the nation improve its core competitiveness, and significantly shape its international leadership role. During this time, many Western companies with interests in China have been strategically passive and pursued ‘business-as-usual’ policies, which often meant they: (i) continued to invest in products and services that had been overtaken by technology and were losing market share, (ii) were relatively slow to invest in emerging technologies and develop new offerings, (ii) tended to fixate on their initial success and failed to quickly recognise that something new was replacing it, and (iii) focused scarce resources on short-term performance rather than long-term value. For many corporates, such policies resulted in missed commercial opportunities and weakened global competitiveness.
 

Reducing the healthcare gap
Over the past decades while many Western companies have been strategically passive, China, by contrast, has been strategically active, aggressively developing innovative and technologically advanced solutions to narrow its healthcare gaps caused by increased healthcare demand and shrinking numbers of healthcare professionals. Witness Chinese start-ups that rapidly grew to become significant companies by leveraging data and artificial intelligence (AI) to develop digital healthcare solutions that enhanced patient outcomes and reduced costs. Examples include: WeDoctorAlibaba HealthJD Health, DXY.cn. and Ping An Good Doctor. These, and other digital innovations, provide a range of health services including, online consultations, hospital referrals and appointments, health management, medication regimens, medical insurance, and wellness and prevention programmes. Such initiatives have provided vast numbers of Chinese citizens with easier access to healthcare and enhanced patients’ therapeutic journeys while reducing vast and escalating healthcare costs and shifted many healthcare services out hospitals into peoples’ homes.

Hospital services shifting to the home
This shift is nothing new and not exclusively Chinese. Twelve years ago, Devi Shetty, a world-renowned heart surgeon, was emphasising the impact that digitalization would have on traditional hospital based services. In just 2 decades, Shetty built Narayana Health (NH), India’s 2nd largest hospital group. In 2019, Narayana was recognised by  Fortune Magazine as, “one of the world’s most innovative healthcare providers”. In 2000, Shetty, like his Chinese counterparts, was emphasising that the “next big thing in healthcare is not going to be a magic pill, or a faster scanner, or a new operation. The next big thing in healthcare is going to be IT, which will change the way a health professional will interact with the patient. Every step of patient care will be dictated by a protocol stored on a handheld device. That will make healthcare safer for the patient and shift most hospital activities to the home. The doctor and patient can interact regardless of time and place”. See video.
 
 
Two types of capitalism
The difference between Western and Chinese corporates reflects two different types of capitalist systems: liberal meritocratic capitalism in the West, and state-led authoritarian capitalism in China. In the former, the emphasise on quarterly reporting and the time, effort and costs associated with it tends to encourage short-term performance while the latter creates more opportunities for generating long-term value. There is plenty of evidence to suggest that when executives consistently invest in long-term strategic objectives their companies’ productivity increases, they generate more shareholder value, create more jobs, and contribute to higher levels of economic growth than do comparable companies that focus on the short-term performance. Data also suggest companies that implement effective environmental, social and governance (ESG) strategies, which address the interests of all stakeholders, achieve better long-term value.

Fink criticizes business executives
In 2014, Laurence Fink, chairman of Black Rock, the world’s largest asset manager, criticized Fortune 500 CEOs for their focus on short term corporate behaviour. While recognising the market pressures on company executives, Fink said, “It concerns us that many companies have shied away from investing in the future growth of their companies” and increasingly engaged in actions that “deliver immediate returns to shareholders, such as buybacks or dividend increases, while underinvesting in innovation, skilled workforces, or essential capital expenditures necessary to sustain long-term growth”.

Takeaways
Western corporate leaders are challenged to devise ethical strategies that create long-term value rather than just short-term performance. Following Fink’s suggestions policies to create long-term value might include: (i) developing a suite of strategic initiatives expected to deliver returns that exceed the cost of capital (ii) allocating resources to initiatives that create most value, (ii) focusing on generating value not only for shareholders but for all stakeholders, and (iii) resisting actions that only boost short term profits.
 
  • China is the world’s second largest economy after the US
  • Its MedTech sector is the world’s second largest after the US and accounts for 20% of the global market
  • The size of China’s market is attractive to Western MedTechs but its regulatory and competitive environments are changing, which makes it more challenging for foreign corporations to enter or grow their franchises in China
  • China’s healthcare system has similar structural challenges as those of the US and other wealthy nations: the demand for care is increasing and overwhelming health professionals, which creates care gaps
  • China is ahead of the US and other nations in attempting to reduce such gaps with patient-centric innovative digital therapeutic solutions, which is supported by a deep bench of capabilities
  • Western MedTechs have a lot to learn from Chinese digital health innovations
  • However, Beijing is engaged in an unprecedented mission to become a self-reliant, high-tech economy and a world superpower within the not-too-distant future
  • Misjudging Beijing can have significant commercial consequences
 
Learn from the Chinese, but don’t misjudge Beijing


An earlier Commentary ended by posing the question whether Western MedTechs can compete with China’s large and rapidly growing domestic medical device industry, which benefits from China being the second largest MedTech market in the world behind the US, with annual sales revenues of ~US$84bn in 2020. China now accounts for ~20% of the global medical device market, which is expected to continue an upward trajectory, supported by the nation’s quickly aging population, rising incomes, and the continued enhancement of health services.
 
With this foundation, Beijing is incentivising its domestic MedTech companies to expand internationally. Beijing’s 14th Medical Equipment 5-Year Plan (2021–25) sets a goal to have >6 Chinese MedTechs among the top 50 global industry corporations by 2025. The policy complements Made in China 2025, which is a macroeconomic strategy to reduce China’s reliance on imported foreign products including medical devices. So, while China’s domestic market is becoming more challenging for foreign MedTechs, Beijing is supporting the growth and expansion internationally of its local medical device companies to compete with their Western counterparts. For example, Mindray Medical International, China’s biggest medical device corporation by sales revenue, is the #4 ultrasound vendor in the world and over the next 5 years, expects to increase its overseas sales revenues from <50% today to ~70%.
 
Despite Beijing’s ‘for China’ policies, many Western MedTech leaders view China as a significant commercial opportunity, recall foreign corporations that have prospered in the nation over the past two decades and suggest that it is important to do business there if one of your company’s objectives is to grow its international franchise. But China has changed, and its regulatory and competitive ecosystems are tightening, which present headwinds for Western MedTechs that were not present a decade ago. Further, China has an ambition to become a self-reliant, world leading high tech nation in the not-too-distant future, which could have consequences for foreign companies participating in the Chinese market.
 
With ~400m chronic disease patients, a fast-aging society, vast and rapidly rising healthcare costs, and an economy that has slowed, China is resolute in developing a new model of digitally enabled, patient-centred integrated healthcare. This ambition is supported by significant resources and a deep-bench of capabilities positioned to enable China to achieve its goals, which include transforming its medical devices sector by supporting the development of world class, high tech, patient-centric, digital enterprises.
 
All these factors suggests a dilemma for Western MedTech leaders: China is too big to ignore, but Beijing is too powerful and unrelenting to misjudge.

 
In this Commentary

This Commentary has 3 sections. The first, entitled ‘Reducing care gaps with digital therapeutic innovations’, suggests that China, the US, and other developed nations share a common challenge of care gaps created-by a limited supply of health professionals and a large and increasing demand for care. China’s attempts to resolve these gaps differ from other nations in their scale and nature. They are nationwide innovations predicated upon digital AI strategies, which manifest themselves in digital platforms that directly address patients’ healthcare needs. We briefly describe a few examples of these and suggest that they are advantaged by China’s data policies and AI competencies. Section 2, entitled ‘Capabilities’, describes Beijing’s plans for China to become the world’s leader in AI technologies within the next decade and suggests that China has the capabilities to achieve this goal in the proposed timeframe. The final section entitled, ‘Understanding Beijing’, briefly describes the tightened regulatory and competitive environments and suggests how this impacts the business models of Western corporations seeking to enter the Chinese market or increasing their existing franchises. We posit that China and the Chinese are significantly different to Western democracies and Westerners and emphasize the Chinese Communist Party’s uncompromising ambition to become economically self-reliant, a world superpower and a global high-tech leader. Misjudging Beijing could be commercially damaging for foreign corporations.
 
 
1: Reducing care gaps with digital therapeutic innovations
 
China has similar structural healthcare challenges to the US and other developed economies, which manifest themselves in care gaps caused by a limited supply of overworked healthcare professionals and a vast and rapidly growing demand for care from aging populations. The Chinese population ≥65 years is ~140m, and this cohort is expected to grow to ~230m by 2030. By that time, the nation’s aging middle class will have grown from today’s ~0.3bn to ~0.7bn. High-risk behaviours like smoking, sedentary lifestyles, and alcohol consumption as well as environmental factors such as air pollution take a huge toll on health and increase the demand for care. According to Statista, a large portion of the Chinese population suffer from chronic lifestyle diseases, which account for >80% of the nation’s ~10m deaths each year; >0.5bn people are overweight or obese, while high blood pressure is a common illness among >0.4bn people. China’s healthcare expenditure is growing at >8% a year, and without reform, the nation’s health spending could increase to >US$2trn by 2030. Such factors, together with the nation’s economic slowdown motivate Beijing to prioritize the transformation of its healthcare system.
Significant differences in tackling care gaps

A significant difference between China and the US and other wealthy nations, whose healthcare systems are all in need of reform, is that China has been quicker to develop digital therapeutic technologies to reduce care gaps and relieve its large and rapidly growing burden on hospitals, care systems and families caring for the sick and elderly.
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Should MedTechs follow surgeons or patients?

In any healthcare system, people should be the priority, but because of a dearth of health professionals, overburdened hospitals, soaring health costs and overworked physicians, patients’ needs are often not prioritized. China has been no exception but expects to reverse this trend with the help of artificial intelligence (AI) enabled digital therapeutic solutions that put patients first. Examples include: WeDoctor, Alibaba Health, JD Health, DXY.cn. and Ping An Good Doctor. These, and other digital innovations, provide a range of health services including, online consultations, hospital referrals and appointments, health management, medication regimens, medical insurance, and wellness and prevention programmes. China’s early adoption of AI medical solutions has benefitted from Beijing’s “Healthy China 2030” policy, which, since its launch in 2016, has directed substantial funds to Chinese AI start-ups developing technological innovations to ease the burden of care gaps. According to Tracxn, one of the world’s largest tracking platforms, there are ~227 AI driven healthcare start-ups in China. Let us briefly describe three established ones: WeDoctor, DXY.cn and Ping An Good Doctor.
 
WeDoctor

Tencent-backed WeDoctor, founded in 2010 to provide people with physician appointments, is based in Hangzhou, a city of ~11m and the capital of China’s Zhejiang province. Since its inception, the company has grown into a multi-functional platform offering a range of medical services predicated upon a database of >2,000 Western treatment plans, online pharmacies, health insurance, cloud-based enterprise software for hospitals and other services. Today, WeDoctor hosts >270,000 doctors and ~222m registered patients. It has an impact on reducing care gaps and is one of the few online healthcare providers qualified to accept payments from China's public health insurance system, which covers >95% of the population. WeDoctor's services are especially valued in rural areas, where there are fewer physicians than the national average of 1.5 per 1,000 people.

In response to the COVID-19 crisis the company launched the WeDoctor Global Consultation and Prevention Center (GCPC),  which provided a free 24/7 global online health enquiry service, psychological support, prevention guidelines and real-time pandemic reports. Just before the pandemic, WeDoctor planned to float its medical and health service function on the Hong Kong stock exchange at a valuation ~US$7bn. However, it was pulled because of the Beijing-Hong Kong tensions. WeDoctor’s. other business functions, which include health insurance and health data services, were not included in its proposed flotation, and are likely to stay private to appease Chinese regulators.
 
DXY.cn
 
DXY.cn is an online healthcare community for doctors, patients, and healthcare organizations. It was founded in 2000 and is also based in Hangzhou. Over the past 2 decades it has evolved into the world’s largest community of physicians who use the platform to gain insights from colleagues, discuss new medical research, and report unusual clinical events. More recently, DXY has added a consumer-facing service that brings wellbeing advice and medical consultations to the public. DXY generates revenues from public-facing medical advertising and job recruitment for its life science clients, as well as clinics where patients can receive in-person medical care. According to TechCrunch, in 2021, DXY reached ~130m consumers, >9,000 medical organizations, and had a registered user base of ~20m.
 
Ping An Good Doctor

Ping An Insurance (Group), is one of the world’s largest financial services companies with >210m retail customers and ~560m internet users and is headquartered in Shenzhen, southeastern China. In 2014, it launched Ping An Good Doctor to provide end-to-end, AI-powered health services directly to patients. These include 24/7 online consultations, diagnoses, treatment planning, second opinions, and prescription management solutions. Today, Good Doctor has ~400m registered users and drives synergies across China’s healthcare ecosystem. The platform collaborates with >3,700 hospitals and is supported by an off-line healthcare network of >2,200 in-house medical staff and ~21,000 contracted experts to ensure quality and accuracy of its medical services. The company provides insurance coverage for both users and physicians, which helps to ease China’s healthcare payment pressures. Ping An Good Doctor’s technology also assists patients to manage their personal health records, treatment plans, and medical histories.
 
In 2019, the company launched the world's first AI-powered, un-manned healthcare service: the One-minute Clinic. This is a 3m2 booth, which patients walk into, enter their digitized medical history from their mobile phones, and add their symptoms. The clinic’s algorithms, which have been trained on data from >300m medical records, then make a diagnosis, prescribe drugs, and provide a treatment plan. Medications are purchased from an adjacent vending machine. Within a year of the start of the first clinic, Good Doctor rolled out ~1,000 units in shopping malls, airports and other public spaces throughout China providing onsite medical and pharmaceutical services 24/7. Today, the clinics provide accessible and affordable medical and health services to >3m users. Good Doctor believes that its AI-driven, un-manned clinics have a promising future helping to reduce China’s care gaps and has plans to expand its services into Southeast Asia. In December 2019, the company signed a strategic collaboration with Merck, an American pharmaceutical multinational to advance further intelligent healthcare in China.

 
Internet hospitals

Digital initiatives like those described above have led to the development and spread of internet hospitals, which are online medical platforms associated with offline access to traditional hospitals that provide a variety of services directly to patients. Today, internet hospitals are booming in China, driven jointly by government and market initiatives.
 
The first internet hospital was established in China’s Guangdong province in October 2014. It consisted of four clinics operated by doctors from the Second People's Hospital, an online platform operated by a medical technology company, and a network of medical consulting facilities based in rural villages, community health centres, and large pharmacy chain stores. Initially webcams were used for patients to communicate with physicians and share medical images of their conditions. A patient's vital signs were taken by on-site machines and uploaded onto the system. With all this information, physicians made a diagnosis and prescribed medications, which patients obtained from nearby pharmacies. According to the Lancet, two months after its launch, China’s first internet hospital “was dealing with ~200 patients and issuing ~120 prescriptions every day”. After six months, the number of patients had increased to >500 a day, ~60% of whom needed prescriptions. Soon afterwards, a network of consultation sites expanded to >1,000 facilities in 21 of Guangdong’s municipalities. In 2018, Beijing gave the legislative green light for internet hospitals, which prompted many Chinese digital health companies to start using internet-based AI solutions to meet the country’s medical and healthcare needs and contribute to the reduction of care gaps. By August 2021, >1,600 internet hospitals had been established in China. The public and physician acceptance of these and Beijing’s support for them suggests a new era in digital healthcare.

 
Internet + Healthcare” initiatives

Since 2018, a range of Internet + Healthcare” initiatives have consolidated and enhanced the position of digital healthcare innovations. The success and continual improvement of China’s digital health service platforms all benefit from Beijing’s policies to facilitate medical practice supported by digital tools. Laws and policies have been issued to support this digital transformation, including health data digitalization, data sharing, and interoperability across the whole of China’s healthcare ecosystem. After the outbreak of the COVID-19 pandemic, the government increased its “Internet + Healthcare” efforts to include telemedicine in state medical insurance coverage, and to lift barriers for prescribed drugs sold online.
 
Data advantage

Compared to the US and other Western democracies, China has significant data advantages to drive its digital healthcare initiatives. Eric Topol, a cardiologist, director of the Scripps Research Translational Institute, and author of Deep Medicine: How AI can make healthcare human again, argues that “China has a massive data advantage when it comes to medical AI research”. To put this in perspective, consider that Chinese patient healthcare data are drawn from the nation’s provinces, many of which have populations of >50m. By contrast, US AI research tends to be based on patient data often drawn from one hospital. China’s big data advantage allows machine learning algorithms to be more effectively trained to perform key functions in a range of clinical settings. Another comparative advantage of China is its large workforce of AI specialist, data scientists, and IT engineers, which can work on healthcare projects at comparatively low costs. This is partly the result of China’s emphasis over the past four decades to encourage science, technology, engineering, and mathematics (STEM subjects) in their schools and universities to fuel Beijing’s technological ambitions.

Not known for good data governance practices, but with intensions to expand internationally, China is now tightening its data protection regulations. For example, in November 2021 Beijing introduced the Personal Information Protection Law (PIPL), which is designed to prevent data hacks and other nefarious uses of sensitive personal information. Much like the EU’s General Data Protection Regulation (GDPR), the PIPL stipulates that an individual’s explicit consent must be obtained before their medical health data are collected, and it places the burden on medical AI companies to ensure that these data are secure.
 
2: Capabilities
 
Healthy China 2030

In October 2016, President Xi Jinping announced the nation’s Healthy China 2030 (HC 2030) blueprint, which put patient-centred healthcare at the core of Beijing’s healthcare plans, recognizing its ability to influence both social and economic development. The policy sets out China’s long-term approach to healthcare and shows the nation’s commitment to participate in global health governance, which Beijing recognises as necessary as it seeks to extend its international reach. By 2030, Beijing aims to reach health equity by embracing the United Nations’ Social Development Goal 3.8, which seeks to “Achieve universal health coverage, including financial risk protection, access to quality essential healthcare services and access to safe, effective, quality and affordable essential medicines and vaccines for all”. In 2019, Beijing announced an action plan to accelerate the delivery of Healthy China 2030. This puts patients first in an endeavour to build a healthy society by leveraging AI technologies to reduce the prevalence of lifestyle induced chronic disorders and subsequent care gaps. The World Health Organization (WHO) believes the policy “has the potential to reap huge benefits for the rest of the world”.
 
AI capabilities
 
As China’s economy has matured, its real GDP growth has slowed, from ~14% in 2007 to ~7% in 2018, and the International Monetary Fund (IMF) projects that growth will fall to ~5.5% by 2024. Beijing refers to the nation’s slower growth as the “new normal” and acknowledges the need to embrace a new economic model, which relies less on fixed investment and exporting, and more on private consumption, services, and innovation to drive economic growth. Such reforms are needed for China to avoid hitting what economists refer to as the “middle-income trap”. This is something many Western economies (and corporations) face: it is when countries achieve a certain economic level but then begin to experience diminishing economic growth rates because they are unable to effectively upgrade their economies with more advanced technologies. To avoid this scenario, for the past three decades, China has been investing in AI and systematically upgrading its economy.


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Leaning-in on digital and AI


 
Today, China has a significant supply of innovative AI talent to deliver a Healthy China by 2030. Some of the world’s largest technology companies are Chinese and all are developing different aspects of AI applications. For example, Alibaba’s cloud division concentrates on using AI in healthcare and Baidu, which has numerous AI research laboratories in the US, is focussed on a range of AI innovations, which include “deep learning”, and “big data”. More recently, Baidu added a Business Intelligence Lab, which develops data analytics for emerging data-intensive applications, and a Robotics and Autonomous Driving Lab, which specializes in computer vision.
In 2017 China's State Council launched a 3-step plan to become a world leader in AI technologies by 2030, with a domestic AI industry valued ~US$150bn. Beijing completed step 1 in 2020 by establishing a “new generation” of AI technologies and technocrats and developing national standards, policies, and ethics for its emerging industry. Step 2 is anticipated to be completed by 2025, by which time China expects to achieve “major breakthroughs” in AI applications that will help the completion of upgrading the nation’s industrial sector and thereby avoiding the middle-income trap. The final step is anticipated to take place between 2025 and 2030, which, among other things, will project China internationally as the world leader in AI technologies.
 
3: Understanding Beijing
 
Regulatory changes

A decade ago, foreign MedTechs operated in China with relative ease. Chinese regulations were lighter than they are today, and companies were supported by a multi-layered network of small scale and localised sub-distributors. This fragmented structure resulted in higher prices and tended to encourage corruption, but the relatively high margins obtained from foreign products allowed medical device corporations to compensate the multiple distribution levels and still make a profit. In return, domestic Chinese distributors managed the market and foreign MedTechs did not engage directly with hospitals and physicians.
 
Volume-based procurement

Recent regulatory changes have disrupted this modus operandi for foreign MedTechs. One change positioned to have a significant impact on MedTech profits is volume-based procurement (VBP). This is aimed at lowering the price of medical consumables by tendering the market volume of cities, provinces, or the country to manufacturers with the lowest price. Following a successful pilot with pharmaceuticals, VBP was extended to medical devices in 2019, and since then it has had a significant effect on certain products. For example, the price of cardio stents and hip and knee implants have been reduced by ~70% to ~90%. China’s message is clear: Medtechs are either ‘in’ with significantly lower prices, or ‘out’. This suggests that companies wishing to enter or grow their franchise in the Chinese market will have to adapt their business models by accelerating their pre-launch registrations and post-launch commercialization strategies for new products as margins on legacy offerings are expected to be substantially reduced. However, review processes for new offerings have become longer, more bureaucratic, and more expensive than they were five years ago. For example, if a Class 2 device without clinical studies took ~9 months to register five years ago, today expect ~2 years. VBP has forced foreign MedTechs to consolidate their multi-layered distribution channels to improve economies of scale. 
 
More recently Beijing has introduced a two-invoice policy for the medical devices industry: (i) MedTech to a distributor, and (ii) distributor to a hospital. This will push small and less competitive distributors out of the market and shorten and consolidate supply chains. The likely effect of this is for Chinese distributors to concentrate more on logistics to “deliver product”, rather than managing the market. To the extent that this is the case, a larger share of customer engagement will become the responsibility of MedTechs.
 
This will mean that foreign corporations trading in China will need to reassess their capabilities and adjust their business models. Further, MedTechs operating in China should expect VBP to increase the significance of “value”. This is because the policy is likely to enhance the purchasing power of hospital administrators and reduce that of physicians.  As a result, companies might expect procurement conversations to focus less on clinical outcomes and more on the overall value of products and their potential to minimize costs. Many readjustments companies will be obliged to make to their business models may be achieved by having someone local on the product management team rather than engaging high-margin agencies to resolve critical, but relatively simple domestic challenges.
 
A narrow window of opportunity for foreign MedTechs

Beijing’s “in China for China” policy makes it a condition that foreign companies entering the Chinese market must share their technology and intellectual property (IP) with a domestic “partner”. Beijing has been using this condition to acquire valuable scientific knowhow, which has helped the country to develop a large domestic medical device industry. According to a 2021 research report from Deloitte, a consulting firm, “China now boasts over 26,000 medical device manufacturers”. Beijing’s policies render China a substantially more challenging market to enter and to grow in than it was five years ago. China’s market opportunities for foreign corporations are not only getting tighter; they are getting shorter, and their orientation is changing away from surgeons towards patients. Further, Beijing is on a relentless drive towards self-reliance and tolerates the presence of Western companies in its domestic markets only for as long as they contribute offerings that are useful to the Chinese Communist Party. If China is successful in delivering on its healthcare and high-tech development plans, the window of opportunity for many foreign MedTechs could be only ~10 years.
 
China’s different

China and the Chinese are unlike the West and Westerners. When Deng Xiaoping’s started China’s reforms in 1978 and opened the nation to the world’s trading economies, he created a socialist market economy, in which private capitalists and entrepreneurs co-existed with public and collective enterprise. This formed the foundations for China’s phenomenal economic growth, prosperity, reduction of poverty, massive infrastructure investment, and development as a world-class technology innovator. As a result, many Western business leaders and politicians believed that China had abandoned ideology in a similar way that former communist regimes of Eastern Europe did in the early 1990s after the fall of the Soviet Union. However, such a transformation did not happen in China, which remains a one-party authoritarian state, tightly governed by the Chinese Communist Party (CCP), whose constitution states that China is a “people’s democratic dictatorship”. The CCP has a mission to become the world’s leading technology economy by 2030. This is backed by substantial sovereign wealth and a supply of relevant high tech human capital and an impressive history of national achievements.
 
Scale and speed of transformation

The phenomenal politico-economic progress China has made in a relatively short time is an indication of the nation’s determination, and its ability to affect change, and contextualizes Beijing’s policies to make China a self-reliant economy in the not-too-distant future. A 2022 report jointly released by China’s Development Research Center and the World Bank highlights the nation’s transformation in just four decades, from a struggling agrarian society to a global superpower. The nation’s achievements include increased health insurance coverage to >95% of its 1.4bn population, lifting ~0.8bn people out of poverty, which accounts for ~75% of global poverty reduction in the same period, a burgeoning middle class, which by 2030, will have grown from today’s ~0.3bn to ~0.7bn. In 2010, China overtook Japan to become the world's second largest economic power after the US when measured by nominal GDP. According to the World Bank, in 1960, China's GDP was ~11% of the US, and in 2019, ~67%. Not only is China the world's second-largest economy it has a permanent seat at the United Nations Security Council, modernised armed forces, and an ambitious space programme. China’s growing international clout and economic leadership positions it well to replace the US as the greatest superpower.

Such factors provide a context for Western corporation with global pretentions wishing to engage with and learn from China. At the 13th Annual National People’s Congress in March 2022, Premier Li Keqiang called for “faster breakthroughs” in key technologies, and said the government would increase the tax rebate for small and medium-sized science and technology firms from 75% to 100% and grant tax breaks for basic research to encourage innovation. Significantly, the Congress also underscored self-reliance in China’s economic priorities amid warnings of trade headwinds and geopolitical complexities.

 
Takeaways
 
China is too big a commercial opportunity to ignore. In 2021, China accounted for >18% of the global economy, rising from ~11% in 2012, its GDP was ~US$18trn, and per capita GDP reached US$12,500, which is close to the threshold for high income economies. In recent times, the contribution of China's economic growth to the world economy has been ~30%, which makes China the largest growth engine for the global economy. However, the relationship between China and the rest of the world is changing. As China becomes more self-reliant, its exposure to the world has decreased. Add to this (i) international trade disputes, (ii) increasing geopolitical tensions between the US and China, (iii) the nation’s evolving new rules to evaluate technology flows, (iv) increase of protectionism and (v) its healthcare mission to pivot towards patients, and you have significantly changed trading conditions than a decade ago. Misjudging Beijing’s rapidly evolving commercial ecosystem could be costly for Western MedTechs.
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  • Neurosurgery is a discipline that diagnoses and treats a range of injuries and disorders of the brain and the central nervous system
  • For millennia the speciality was dominated by forms of craniotomies, which are procedures to remove portions of the skull to gain access to brain disorders
  • In the early and mid-20th century visual, guidance and radiation technologies disrupted the treatment of some brain disorders by introducing less- and non-invasive procedures to the discipline
  • At the beginning of the 21st century, a flurry of rapidly developing innovative technologies including, augmented reality, artificial intelligence (AI), robotics and genomic and cellular therapies, are accelerating the trajectory of neurosurgery towards a less- and non-invasive speciality
 
Brain disorders and the changing nature of neurosurgery
 
Populations throughout the world are growing and aging, the prevalence of age-related disabling neurological disorders is increasing, and healthcare systems are facing large and escalating demands for treatment, rehabilitation, and support services for such disorders. According to the most recent Global Burden of Disease (GBD) Study, neurological disorders are the leading cause of disability and the second leading cause of death in the world.
 
The total annual global burden of traumatic brain injury alone is ~US$400bn and in the US, ~16% of households are affected by brain impairment, with many individuals requiring 24-hour care. This suggests that often several family members are involved in the caregiving process, and some are juggling the responsibilities of caregiving, child rearing and employment simultaneously.
 
The scarcity of established modifiable risks for most of this vast and rapidly growing neurological burden suggests that innovations are required to develop efficacious prevention and treatment strategies. This Commentary describes some of these, especially those that have changed or have the potential to change neurosurgery, by making therapies less- and non-invasive, and hold out the prospect of improving patient outcomes and lowering healthcare costs.
 
Neurosurgery is a medical speciality concerned with diagnosing and treating a range of disorders and injuries of the brain and central nervous system (CNS) in patients of all ages. These include tumours of the brain and CNS, infections of the CNS, pituitary tumours and neuroendocrine disorders, traumatic brain injury, cerebral aneurysms and stroke, hydrocephalus and other conditions that affect the flow of cerebrospinal fluid, degenerative spine disorders, Parkinson’s disease, Alzheimer’s, epilepsy, spina bifida, and psychiatric disorders.

Treating brain conditions is complex and challenging. This is partly because the brain is one of the best protected organs of the human body. It is encased in the bones of the skull, covered by the meninges, which consist of three membranes and cushioned by cerebrospinal fluid (CSF). It is also protected by the blood-brain barrier (BBB), which is a network of blood vessels and tissue comprised of closely spaced cells, which shield the brain from toxic substances in the blood, supply brain tissue with nutrients, and filter harmful compounds from the brain back into the bloodstream. The BBB limits the ability of therapeutics to be effectively delivered to the brain and thereby complicates the treatment of CNS disorders. Further, the brain does not feel pain because there are no nociceptors (a sensory receptor for painful stimuli) located in its tissue, which often makes diagnosis of neuro disorders late when treatment becomes more challenging and costly, and survival less likely.

Such factors partly explain why neurology and neurosurgery have been slower than some other specialities to take advantage of new and evolving technologies. However, this is changing. Over the past five decades, progress in three-dimensional (3D) visualization, miniaturisation, digital technology, robotics, computer assisted manipulation, radiation therapy, early diagnosis of cancer, and precision medicine, have contributed to improvements in the diagnosis, prognosis, and prevention of some neurological conditions and started to transform neurosurgery towards less- and non-invasive procedures that efficaciously execute complex challenges, eliminate mechanistic errors, reduce operating times, and improve patient outcomes.
 
Further, the growing significance of applying artificial intelligence (AI) and machine learning techniques to pre-, intra- and post-operative clinical data introduces the possibility of a new suite of medical services that have the potential to enhance patient outcomes and reduce costs by improving diagnosis, planning and the rehabilitation of patients. And more recently, there are growing synergies between neurosurgery and gene and cellular therapies, which promise to accelerate personalized, non-invasive treatments for a range of neuro disorders.
 
In this Commentary
 
This Commentary is divided into 9 sections. Section 1 provides a brief history of neurosurgery, which has its genesis in ancient times when a form of craniotomy (surgical removal of a portion of the skull) was practiced and note the difference between craniotomy and craniectomy. Section 2 describes how, in the mid-20th century, neurosurgery took ~4 decades to pivot when Lars Leksell, a Swedish surgeon, introduced a stereotactic guided device that permitted the accurate positioning of probes to treat small targets in the brain, which were not amenable to conventional surgery. Shortly afterwards Leksell developed ‘stereotactic radiotherapy’, which formed the basis the Gamma Knife®, a device that provides non-invasive surgeries for a range of brain disorders. Section 3 details how advances in magnification, illumination, and the development of fibreoptics contributed to less-invasive endoscopic neurosurgeries, which facilitated a range of brain disorders to be treated through a small burr hole in the skull. Previously such procedures would have required a craniotomy. This section also notes the rapid development of endovascular neurosurgery, which uses tools that pass-through blood vessels to diagnose and treat diseases and conditions of the brain rather than using open surgery. Today, neuro-endovascular surgery is the most practiced therapeutic approach for a range of vascular conditions affecting the brain and spinal cord and is positioned to grow further over the next decade. Section 4 suggests howneurosurgery has benefitted from a range of rapidly developing 21st century technologies including: augmented reality, artificial intelligence (AI), robotics and genomic and cellular therapies. All help to increase less- and non-invasive neurosurgical procedures and contribute to advancing personalized therapies that improve patient outcomes and lower costs. Section 5 provides some insights into the life of a neurosurgeon through the lens of Henry Marsh, an English neurosurgeon who, between 2014 and 2022, published three candid memoirs, which chronicle his career, describe daily challenges and frustrations of the speciality and explain how neurosurgical units have changed the way they are organized and run. Sections 6 briefly mentions the increasing prevalence of dementias. Although outside the direct realm of neurosurgery, the scale and speed of their growth are likely to have an indirect impact on it. Section 7 introduces traumatic brain injury (TBI), a condition caused by a blow to the head and suffered by millions. The section describes the gold standard management of severe TBI and flags a pressing need to develop a non-invasive modality for managing the condition. Section 8 notes the frustration of neurosurgeons with the late diagnosis of brain tumours and describes well-resourced global endeavours to detect a wide range of cancers from a single blood test in asymptomatic people. Takeaways follow in Section 9 and suggest that a significant proportion of neurological disorders, which previously were treated with craniotomies, are now treated with either less- or non-invasive procedures. With the speed at which technology and biomedical science are developing, the only direction of travel for neurosurgery is towards non-invasive procedures.
 
Section 1
History
 
Neurosurgery has a long history with its genesis in Mayan civilizations ~1500 BCE, who practiced cranial deformations that included flattening frontal skull bones. During the Egyptian era, when mummification started to be practiced ~2,500 BCE, embalmers did not use a form of craniotomy to gain access to the brain. Instead, they used hooked instruments to remove the brain through the nose: a prototype of modern transsphenoidal surgery, which is a common procedure today for removing tumours of the pituitary gland. Rather than opening the skull with a traditional craniotomy, the physician reaches the tumour through the nasal passages and the sphenoid sinus.
 
In ancient Peru Inca surgeons practiced an early form of craniotomy referred to as trepanation, which used a scraping technique to penetrate the skull. Such procedures were performed on adult men to treat injuries suffered during combat. A version of this procedure called a trephination was also practiced in Egyptian and Roman times and performed on individuals who had experienced head traumas. The approach entails making a hole in the skull to relieve the build-up of intracranial pressure (ICP) caused by brain oedema (swelling) and is described by Hippocrates in the Greek era. The first known neurosurgery in Greece took place ~1900 BCE in Delphi when skull trephinations were probably performed for religious reasons. Later, the technique was recommended by Galen during the Roman period for people who had suffered a traumatic brain injury (TBI) in battle. From ~500 to ~1500 AD, the rise of religion and war resulted in many craniocerebral traumas, which contributed to the early development of neurosurgery as a distinct specialty.
 
Similar trephination procedures were performed during the American Revolutionary War, which secured American independence from Great Britain, and culminated in the Declaration of Independence on July 4, 1776. During the war soldiers suffered TBIs after being hit on the head with the butt of a rifle. Although the treatment for severe TBI is similar today, (see Section 7) the main difference is that the surgical instruments used in the 18th century were not powered. About 132 years later, in 1909, Theodore Kocher, a Swiss physician and Nobel Laureate in Medicine was the first person to systematically describe a decompressive craniectomy procedure for severe TBI patients. A craniectomy is different to a craniotomy. The latter is a surgical procedure in which a section of the skull is removed to expose the brain and is performed to treat various neurological conditions, or when an injury or infection has occurred in the brain. A craniectomy involves a different surgical technique and is used on people suffering severe TBI to relieve brain oedema. In such a procedure the bone fragment removed may not be replaced immediately and is either replaced during a subsequent surgery or discarded in favour of a future reconstruction using an artificial bone.

 
Section 2
Stereotactic surgery
 
For millennia, a form of craniotomy dominated what we now know as neurosurgery. During the 20th century advances in medical science paved the way for the introduction of less- and non-invasive modalities to treat brain disorders (see below). A landmark event occurred at the beginning of the 20th century with the introduction of stereotactic surgery, which makes use of three-dimensional (3D) coordinates to locate and treat lesions in the brain. The method was first reported in the May 1908 edition of Brain, by two British surgeons Victor Horsley, and Robert Clarke. The device they described became known as the Horsley-Clarke apparatus, and was used to study the cerebellum in animals by enabling accurate electrolytic lesioning to be made in the brain of a monkey. It took ~40 years before the technique was introduced to humans following the publication of a seminal paper by Ernest Spiegel and Henry Wycis,  in the October 1947 edition of Science. Spiegel was a Vienna trained neurologist who moved to Temple Medical School in Philadelphia, which in 2015 was renamed the Lewis Katz School of Medicine. Wycis was one of Spiegel’s students who became a neurosurgeon. By the time they published their 1947 paper, they had performed several neurosurgeries and there had been sufficient advances in neurophysiology, pneumoencephalography, radiology, and electrophysiology for them to design a device like the Horsley-Clarke apparatus, which was fixed to a patient’s head by means of a plaster cast and was accurate enough to be used in human stereotactic surgery. Spiegel’s and Wycis’s surgical innovations attracted attention from physicians internationally, but there were no commercial stereotactic frames and neurosurgeons were obliged to design and manufacture their own. A pivotal moment occurred in 1947, when Lars Leksell, a Swedish physician and Professor of Neurosurgery at the Karolinska Institute, in Stockholm, visited Wycis in Philadelphia and afterwards designed a lightweight titanium head frame to provide the basis for stereotactic surgery, which he described in a 1949 paper entitled, ‘A stereotaxic apparatus for intracerebral surgery’.
 

The Gamma Knife®   
In the early 1950s, Leksell and Börje Larsson, a biophysicist from the University of Uppsala, Sweden, were convinced that agents other than cannulas and electrodes could be used to eradicate pathologies in the brain, and combined a source of radiation with a stereotactic guiding device. This led to the development of a non-invasive device, which Leksell used to perform the first radio-neurosurgical procedure and discovered that a single dose of radiation could successfully destroy deep brain lesions. He called this technique “stereotactic radiosurgery”, which, in 1968, led to the first stereotactic Gamma Knife® that used a focused array of intersecting beams of gamma radiation to treat lesions within the brain. Its success encouraged Leksell to use the device over the ensuing decade in functional brain surgeries to treat intractable pain and movement disorders. Leksell’s radio surgical device used Cobalt-60 (a synthetic radioactive isotope) as a radiation source. The basic physics that drives stereotactic radiosurgery today is substantially the same. It focuses ~200 tiny beams of radiation on a target in the brain with submillimetre accuracy. Although each beam has little effect on the brain tissue it passes through, a strong dose of radiation is delivered to the place where the beams meet.
 
Over time, the Gamma Knife® has been refined and enhanced and its efficacy and safety have been well established. Today, the Gamma Knife® provides a non-invasive operative system for a range of brain disorders, including small to medium size tumours, vascular malformations, epilepsy, and nerve conditions that cause chronic pain. Before its introduction such disorders were treated by surgeries, which involved craniotomies. In 1987, the Gamma Knife® was introduced into the US and installed at the Universities of Pittsburgh and Virginia. Although it took decades to achieve regulatory approval and be widely used throughout the world, the Gamma Knife® represents a significant technological advance in neurosurgery. Unlike craniotomies the device provides painless procedures that do not require anaesthesia, treatments take just one session, and patients can return to normal activities almost immediately. The Gamma Knife® is ~90% successful in killing or shrinking brain tumours, and today, there are ~300 Gamma Knife® sites worldwide, which each year treat >60,000 patients.
 
Neurosurgeon Ranjeev Bhangoo, Clinical Director for neurosurgery at King’s College Hospital, London, UK likens the Gamma Knife® to, “an umbrella, that sits above the patient’s head, rather like the old-fashioned hair dryers in women’s hair salons, but much bigger and more complex”, and stresses that the procedure, “is not painful. Forget any notion of surgery: there’s no knife, there’s no operating theatre. It’s done with the patient awake: you walk in, have your treatment, and walk out.” See videos.

 

What is Gamma Knife Radiosurgery?
 

Is Gamma Knife Radiosurgery painful?

 
Section 3
Endoscopic and endovascular neurosurgery
 
Neuroendoscopy
Neurosurgery pivoted again in the 1990s when disorders that would normally require opening the skull began to be treated less invasively through a small burr hole. Improved magnification, miniaturization, and illumination of lenses and the development of fibre optics facilitated an endoscopic surgical procedure to treat hydrocephalus, a condition in which cerebrospinal fluid (CSF) abnormally accumulates in the brain. There is currently no prevention or cure for the condition, but it can be managed with surgery. The procedure includes creating an opening in the floor of the third ventricle using an endoscope (a thin, flexible, tube-like imaging instrument with a small video camera on the end) placed within the ventricular system through a burr hole in the skull. In the late 1990s, neuro-endoscopy expanded to treat lesions outside the ventricular system and the endoscopic endonasal approach was established as a technique that allowed surgeons to go through the nose to operate on areas at the front of the brain and top of the spine.

Since the early use of the endoscopic procedures for treating intrasellar pituitary adenomas, the approach has been expanded to treat a range of skull base lesions. Today, skull base surgery is undertaken to remove both noncancerous and cancerous growths, and abnormalities on the underside of the brain or the top few vertebrae of the spinal column. Because this is such a difficult area to see and reach, skull base surgery has been advantaged by endoscopic procedures where surgeons insert instruments through natural openings in the skull - the nose or mouth - or by making a small hole just above the eyebrow. This type of surgery requires a team of specialists that may include ear, nose, and throat (ENT) surgeons, maxillofacial surgeons, neurosurgeons, and radiologists. Before endoscopic skull base surgery was developed, the only way to remove growths in this area of the body was by making an opening in the skull. In some cases, today, this type of surgery may be still needed.

Recent advances in endoscope design have produced equipment that is smaller and more efficient, with improved resolution and brighter illumination, than earlier models. Such developments, combined with surgeon enthusiasm, have contributed to the expansion of neuro-endoscopy to treat a range of neuro disorders including intracranial cysts, intraventricular tumours, skull base tumours, craniosynostosis (a birth defect in which the bones in a baby's skull join too early), degenerative spine disease, hydrocephalus and a rare benign tumour called hypothalamic hamartoma.
 
Neuro-endoscopic surgery causes minimal damage to normal structures, carries a lower rate of complications, shortens hospital stays, minimizes cosmetic concerns associated with many neurosurgical conditions and improves patient outcomes. It is positioned to take advantage of further miniaturization of cameras and optical technology, innovations in surgical instrumentation design, and further innovation in navigation and robotics systems.
 

Endovascular neurosurgery
Another innovation that has developed over the past five decades is endovascular surgery. The term ‘endovascular’ means ‘inside a blood vessel’. Endovascular neurosurgery uses tools that pass-through blood vessels to diagnose and treat diseases and conditions of the brain rather than using open surgery. The genesis of endovascular neurosurgery is credited to Professor Alfred Luessenhop, an American physician at Georgetown University Hospital in Washington DC, who, in 1964, carried out the first embolization of a cranial arteriovenous malformation and the first intracranial arterial catheterization to occlude an aneurysm. Over the past 60 years, endovascular neurosurgery has developed and has become a subspeciality. Today, >50% of cerebral aneurysms are treated through this minimally invasive approach.
 
Neuro-endovascular surgery has become the most practiced therapeutic approach for the majority of vascular conditions affecting the brain and spinal cord. It is used more frequently than open surgery for the management of complex vascular conditions, with high rates of safety and efficacy. The expansion of endovascular techniques into the treatment of stroke, the third highest cause of death in the US, has provided meaningful benefits to large numbers of patients worldwide. Further, with populations throughout the world aging neuro-endovascular techniques are poised to become one of the most necessary and important treatment modalities within neurosurgery.
 
With age our brains shrink, which causes a space to develop between the surface of our brain and its outermost covering. This increases the possibility that a knock to the head of a person >60 will result in a brain blood vessel rupturing and bleeding: a subdural hematoma. Research suggests that, “significant numbers occur after no significant antecedent trauma”, and could be the result of “an inflammatory process occurring at the level of the dural border cell”. A chronic version of this disorder can manifest itself within weeks of the first bleeding in which blood accumulates. With aging populations, chronic subdural hematoma (cSDH), is a condition predicted to become one of the most common neurosurgical conditions in the near-term future and expected to be treated with neuro-endovascular techniques.
 
Further, minimally invasive neuro-endovascular procedures are now commonly used to repair cerebral aneurysms, which are weak or thin spots on arteries in the brain that balloon and fill with blood. A bulging aneurysm can put pressure on brain tissue, and may also burst or rupture, spilling blood into the surrounding tissue (brain haemorrhage). Today most brain aneurysms are treated minimally invasively with neuro-endovascular techniques, which means an incision in the skull is not required. Instead, the surgeon guides a catheter or thin metal wires through a large blood vessel in the patient’s groin to reach the brain, using contrast dye to identify the problematic blood vessel. The aneurysm is then sealed off from the main artery, which prevents it growing and rupturing. In the US ~6.5m people are living with an unruptured brain aneurysm. The annual rate of rupture is ~10 per 100,000: ~30,000 Americans suffer a brain aneurysm rupture each year. Ruptured cerebral aneurysms are fatal in ~50% of cases and those who survive, ~66% suffer some permanent neurological deficit. Each year, there are ~0.5m deaths worldwide caused by brain aneurysms and ~50% are <50years.

 
Section 4
Evolving technologies affecting neurosurgery

At the beginning of the 21st century scientific and technological advances are again changing the face of neurosurgery. This section briefly describes four such changes.
 

Neurosurgery and augmented reality
Neurosurgery relies on visualization and navigational technologies and makes liberal use of computed tomography (CT) and magnetic resonance imaging (MRI) scans during preoperative planning and intraoperative surgical navigation. More recently, augmented reality (AR) applications have been used to complement more conventional visualization and navigational technologies to enhance neurosurgery. AR can bring digital information into the real environment and is beginning to play an increasing role to help neurosurgeons train, as well as plan and perform complex surgical procedures. In June 2020, surgeons atJohns Hopkins University successfully carried out a spinal fusion surgery for the first time in the US using xvision™, an FDA approved AR device for spine surgery developed by Augmedics Inc., a Chicago based company, which went public in 2020 through a reverse merger with Malo Holdings. Xvision™ allows surgeons to “see” the patient's anatomy through skin and tissue as if they have X-ray vision, to accurately navigate instruments and implants during surgical spine procedures. Each year, there are ~1.62m instrumented spinal procedures performed in the US, the majority of which are undertaken using a freehand technique, which can lead to suboptimal results.  
 

Neurosurgery and artificial intelligence
Such heavy use of advanced imaging and guidance technologies creates a vast amount of clinical data during a patient’s neurosurgical journey. It is not altogether clear how effectively pre-, intra-, and post-operative clinical patient data are collected and analyzed to enhance surgical procedures and patient outcomes. An article in the August 2021 edition of the journal Neuroscienceentitled, ‘Neurosurgery and Artificial Intelligence’, suggests that the collection and analysis of such data are beginning to happen. Over the past decade, AI techniques applied to data collected during patients’ neurosurgical journeys have enhanced diagnoses and prognostic outcomes and contributed to post operative care and the rehabilitation of patients. Being able to predict prognosis, identify potential postoperative complications, and track rehabilitation are enhanced with AI applications. The future suggests that the symbiotic relationship between AI and neurosurgery, which today is in its infancy, is positioned to grow. This will not only help AI to develop better and more robust algorithms but will provide opportunities for MedTechs to gain access to new revenue streams by providing enhanced patient services.
 
Robotics
Linked to medical imaging and navigation technologies is the increasing use of surgical robotics. However, neurosurgery has been slower than other specialties to incorporate robotics into routine practice owing to the anatomical complexity of the brain and the spatial limitations inherent in neurosurgical procedures. Notwithstanding, the first documented use of a robot-assisted surgical procedure was in neurosurgery. In 1985 Yik San Kwoh and colleagues, at the Memorial Medical Center in Long Beach, California, used an Unimation Programmable Universal Machine for Assembly (PUMA) 200 (which was originally designed for General Motors’ factories) to perform a CT-guided stereotactic biopsy of a brain lesion. Although discontinued, the PUMA 200 is considered the predecessor of current surgical robots.  There are now several robotic systems that have gained regulatory approval for cranial surgery. These include Zimmer Biomet’s ROSA ONE Brain, which obtained FDA approval in 2012 for intracranial applications, and Renishaw’s Neuromate robotic system, which was granted approval by the FDA in 2014. The former has been used extensively in the treatment for epilepsy, and the latter provides surgeons with five degrees of freedom for use in stereotactic applications. Robotics is a fast-moving discipline, which together with AI and machine learning, is positioned to impact neurosurgery in the near to medium term.
  

Neuro-pharmaceuticals and Trojan horses
There are growing synergies between neurosurgery, gene, and cellular therapies. However, the BBB, which plays a significant role in controlling the influx and efflux of biological substances essential for the brain to operated effectively, makes it extremely difficult to effectively deliver drugs to the brain. Over the past three decades, many biologics (medications developed from blood, proteins, viruses, or living organisms) have entered brain and CNS clinical studies. However, they have not gained FDA approval mainly because they did not have effective mechanisms to deliver neuro-pharmaceuticals across the BBB. Instead, the clinical trials were predicated upon a variety of BBB avoidance strategies. Cerebrospinal fluid (CSF) injections are the most widely practiced approach that delivers drugs to the brain by attempting to bypass the BBB. However, this results in limited drug penetration to the brain because of the rapid export of CSF from the brain back into the bloodstream. Future drug or gene-based neuro-pharmaceuticals will need to be accompanied by advances in BBB delivery vehicles.
 
Currently, there are numerous scientific endeavours to devise innovative and effective ways to deliver gene therapies across the BBB to the brain. Success in this regard will mean that genomic and cellular therapies will increasingly have the potential to work synergistically with neurology and neurosurgery to provide non-invasive, personalized care for a range of brain disorders including Alzheimer’s, Parkinson’s, spinal muscular atrophy, spinocerebellar ataxia, epilepsy, Huntington’s disease, stroke, and spinal cord injury. Endeavours are underway to re-engineer biologic drugs as brain-penetrating neuro-pharmaceuticals using BBB molecular Trojan horse technologies. This approach employs genetically engineered molecular Trojan horses (proteins), which carry genes across the BBB to have a therapeutic impact on brain disorders. The future development of neuro-pharmaceuticals linked to effective means to deliver these across the BBB are together positioned to reduce the need for interventional neuro therapies, but this may take some time.

 
Section 5
A perspective: life as a neurosurgeon
 
Three memoirs by Henry Marsh, an English neurosurgeon who treated a range of brain disorders over a 40-year career at a leading neurosurgical unit in London, provide insights into the human dramas that occur in a busy modern hospital. Marsh studied Politics, Philosophy and Economics (PPE) at Oxford University before starting medical school at the Royal Free Hospital in London. In 1984, he became a Fellow of the UK’s Royal College of Surgeons and in 1987, was appointed a consultant neurosurgeon at the Atkinson Morley Regional Neurosciences Centre at St George’s Hospital in London, where he spent his entire career.
 
Marsh’s first book is an unflinching memoir entitled, Do No Harm: Stories of Life, Death and Neurosurgery, which was published in 2014, and describes, with compassion and candour, challenging professional experiences filled with risk and imminent death. The book opens with the sentence, “I often have to cut into the brain and it's something I hate doing.” His first operation as a neurosurgeon was to treat a cerebral aneurysm. Forty years ago, this would have required opening the skull to access the brain. The procedure had a profound impact on Marsh, who commented, “What could be finer than to be a neurosurgeon. The operation involved the brain, the mysterious substrate of all thought and feeling, of all that was important in human life: a mystery, it seemed to me, as great as the stars at night and the universe around us.”
 
Marsh describes the difficult decisions, which neurosurgeons and patients regularly must make that change lives forever. He recalls moments of celebration and gratification when complex operations go well, and candidly recounts some of the more undesirable outcomes and slips of the hand that result in devastating outcomes. Marsh liked working with American neurosurgeons and came to “love their optimism, their faith that any problem can be solved if enough hard work and money is thrown at it, and the way in which success is admired and respected and not a cause for jealously”. He found the attitudes of American surgeons, “a refreshing contrast to the weary and knowing scepticism of the English”. However, after visiting hospitals in the US he expressed some scepticism about “the extremes to which treatments can sometimes be pushed” and wondered whether American physicians and patients “have yet to understand the famous American dictum that ‘death is optional’, was meant as a joke”. Tellingly, Marsh notes that “sometimes doctors admit their mistakes and ‘complications’ to each other, but are reluctant to do so in public, especially in countries that have commercial, competitive healthcare systems.” 
 
Marsh’s second memoir, Admissions: A Life in Brain Surgery, was published in 2017 two years after he retiredfrom his full-time job in England to work pro bono in Ukraine and Nepal. A documentary of his work in Ukraine, The English Surgeon, won an Emmy award. Marsh uses ‘Admissions’ to take an inventory of his life, which makes the book an even more introspective memoir than his first. He compares the challenges of working in troubled, impoverished countries like Nepal with his experience as a neurosurgeon in wealthy nations like the UK and US. The excesses of American medicine intrigued Marsh and he comments, “only in America have I seen so much treatment devoted to so many people with such little chance of making a useful recovery.” But he also expresses disillusionment with the administrative red tape in the English National Health System (NHS), which he maintains has eroded the authority and status of surgeons. In his final years working as a surgeon in St George’s Hospital in London he bemoans, “The feeling that there was something special about being a doctor had disappeared.” Marsh’s true love was patients and neurosurgery and at the end of his career, he was spending less time with patients and more time in meetings justifying his judgements and familiarizing himself with the latest UK government’s targets and edicts, which led him to say, “doctors need regulating, but they need to be trusted as well. It is a delicate balance, and it is clear to me that in England the government has got it terribly wrong”. 
 
Marsh suggests that patients’ fear encourages surgeons to exaggerate their competence and knowledge to “shield our patients from the frightening reality they often face”.  Over time, Marsh suggests, surgeons tend to believe the exaggerated versions of themselves. But the best un-learn their self-deception and come to accept their shortcomings and learn from their mistakes. “We always learn more from failure . . . . . . Success teaches us nothing,” Marsh writes.
 
Marsh’s third memoir,And Finally: Matters of Life and Death, was published in August 2022 and is very British, full of self-deprecation and dominated by the news that he is diagnosed with incurable prostate cancer. Marsh describes the sudden reversal of roles, from omniscient and omnipotent neurosurgeon to humble patient and provides descriptions of the ebbs and flows of his therapeutic journey, which gives valuable insights into how medicine in England works.
 
All three books bear witness to the fact that neurosurgery is a stressful and demanding profession, which requires extensive training, stamina, a high degree of manual dexterity, excellent hand-eye coordination, exquisite precision, extraordinary attention to detail, an ability to rapidly gather and process complex information to resolve challenging problems, compassion and empathy for patients, communication skills and teamwork. Unlike other surgical disciplines, a relatively small mistake can lead to “appalling disability”, coma, and death. According to research published in the October 2014 edition of Surgical Neurology International, ~25% of neurosurgical errors can be prevented or reduced with the increased use of evolving technologies, some of which are described in this Commentary.
 

Changes in the organization of neurosurgical units 
During Marsh’s 40-year career there were changes in the way neurosurgical units were organized and run; particularly the development of subspecialities among physicians and the use of multidisciplinary team approaches to clinical challenges. Much of Marsh’s career reflected a time when neurosurgeons worked in relative isolation and treated a wide range of neurosurgical conditions that presented in their clinics. Today, most neurosurgeons have a primary interest in a subspeciality such as epilepsy, neurovascular surgery, spinal surgery, the excision of tumours etc., and a secondary interest, which they share with colleagues. This tends to facilitate cross referral of patients among a team of physicians and improves patient care and the training of health professionals. In the operating room (OR) neurosurgeons work with other physicians, anaesthetists, trainee doctors, theatre nurses, and medical students. Outside the OR they collaborate with radiologists who use a range of diagnostic tools, including CT, MRI scans, and cerebral angiographies, which are used to detect abnormalities in blood vessels such as aneurysms, blockages, and bleeding. These neuroimaging technologies and neurosurgery have become inseparable. Neurosurgeons also work with neurologists, oncologists, ophthalmologists, and paediatricians. In 2017, Bob Carter, head of neurosurgery at the Massachusetts General Hospital, in the US, appreciated the interconnections between several clinical disciplines that care for people with neurological disorders and merged his neurosurgery department with the departments of neurology, psychiatry, and neuroradiology. While sub specialisms and teamwork have made an impact on the organization of neurosurgical units, new and emerging technologies have expanded the repertoire of neurosurgeons.
 

Awake brain procedures
Marsh specialised in operating on the brain while the patient is awake. This aspect of his work was the subject of a BBC documentary, Your Life in Their Hands. Awake brain procedures are usually performed when a lesion is located near the frontal lobes responsible for motor skills and speech. In the video below, Ranjeev Bhangoo describes the procedure, “It’s a technique where the patient is awake during the brain surgery. The patient is neither in pain nor suffering. When we make a cut in the skin and raise a trapdoor in the skull the patient is completely asleep. We wake them up after that point and the good news is the brain itself doesn’t feel pain. So, you can do this operation without the patient being in any distress or pain. It’s an unusual situation and the patient is prepared for it beforehand. The reason why you might want to do an awake craniotomy is because in some situations, tumours are close to critical structures of the brain that control speech or movement. While we have good maps of the brain and we have image guidance, they’re not precise enough. You want the patient to be talking to you and you want to be stimulating bits of the brain to see precisely where speech is so that you can avoid those areas and do the same with movement, you want to see the patient moving his or her arm or leg while you’re stimulating bits of their brain. So, we use an awake craniotomy when we’re operating near to what we call ‘eloquent’ areas of the brain that, if damaged, would produce a devastating deficit such as problems with speech or movement”. See video.
 

When and why is an awake craniotomy performed?

 
Section 6
The increasing burden of dementias on healthcare systems and economies
 
As populations age and live longer so dementia conditions increase. Alzheimer's, which effects parts of the brain that control thought, memory, and language, is the most common dementia in Western societies. It is a progressive disorder that begins with mild memory loss and leads to a loss of the ability to carry on a conversation and respond to your environment. In the three decades between 1990 and 2019, the global incidence of Alzheimer’s and other dementias increased by ~148%. In 2022, there were >6.5m Americans living with the condition: ~73% >65 and ~66% of these women, but this simply may be due to women living longer. By 2050, it is projected that ~13m Americans will suffer from dementia, which is expected to kill 1 in 3 seniors; that is more than breast and prostate cancers combined.
 
According to the World Health Organization (WHO), there are ~55m people with dementia globally, and >60% are living in low- and middle-income countries (LMIC). Age is the most significant risk factor: the likelihood of Alzheimer’s doubles every 5 years after you reach 65. But also, dementias appear to be increased by conditions that damage the heart and blood vessels, which include heart disease, diabetes, stroke, high blood pressure and high levels of cholesterol. As the proportion of older people in populations increase in nearly every country, people living with dementias are expected to rise to ~78m by 2030 and 139m in 2050. There is no cure for Alzheimer's, and treatments tend to fall to neurologists.  Drug therapies include galantamine, rivastigmine, and donepezil, which are cholinesterase inhibitors (also known as anti-cholinesterase, are chemicals that prevent the breakdown of the neurotransmitter acetylcholine) that are prescribed for mild to moderate Alzheimer's symptoms and may help reduce or control some cognitive and behavioural symptoms. Also, there are non-drug options.  Although outside the direct realm of neurosurgery, the scale and speed of the growth of Alzheimer’s and other dementias are likely to indirectly impact neurosurgery by increasing the burden on over-stretched healthcare systems. Under such circumstances, it seems reasonable to assume that there will be increased pressure on neurosurgery to become less resource intense, which means less invasive and less costly while improving patient outcomes.
 
Section 7
Traumatic brain injury

On Thursday 29th September 2022, Tua Tagovailoa, the Miami Dolphins’ quarterback received a head injury during a match against the Cincinnati Bengals and was stretchered off. Four days earlier he left the field after receiving another head injury while playing against the Buffalo Bills. He was then checked for a concussion and cleared and came back onto the field in the third quarter. Subsequently, the NFL Players Association exercised its right to remove the independent neurological expert who was involved in the decision to clear Tagovailoa to return to the Buffalo Bills game after being evaluated for a traumatic brain injury (TBI). This raises the significance of injuries to the brain and the challenges of accurately assessing their severity and adequately treating them.
 
TBI is as an alteration in brain function pathology by a sudden trauma, causing damage to the brain. Each year, the condition affects ~69m individuals worldwide. Symptoms can be mild, moderate, or severe, depending on the extent of the damage: annually ~5.5m severe cases are recorded globally. The epidemiology of the disorder is challenging because, in low-resourced regions of the world, where the prevalence of TBI is believed to be high, data are poor. According to the World Health Organization (WHO), ~90% of deaths due to head injuries occur in low- and middle-income countries (LMICs), where ~85% of the global population live and where the standards of care are patchy. TBI not only causes health loss and disability for individuals and their families, but also represents a costly burden to healthcare systems and economies through lost productivity and high healthcare costs. The total annual global burden of TBI is ~US$400bn.
 
Since the beginning of the 20th century, our knowledge and understanding of the pathophysiology of brain oedema (swelling) in head trauma patients has increased and today decompressive craniectomy is a recognised procedure for severe TBI to mitigate intracranial hypertension and its impact on clinical outcomes. One of the largest clinical studies, which sought to determine the efficacy of decompressive craniectomies for TBI patients, was the RESCUEicp trial: findings of which were published in the September 2016 edition of the New England Journal of Medicine. The study was carried out over a 10-year period, between 2004 and 2014, on 408 randomly assigned patients, 10 to 65 years of age, and concluded that, “At 6 months, decompressive craniectomy in patients with traumatic brain injury and refractory intracranial hypertension resulted in lower mortality and higher rates of vegetative state, lower severe disability, and upper severe disability than medical care”. 
 
In the US, TBI is a leading cause of death and disability. Each year, ~1.5m Americans sustain a TBI, ~50,000 die from the insult, ~230,000 are hospitalized and survive, and ~90,000 experience the onset of long-term disability. According to the US Centers for Disease Control and Prevention, ~5.3m Americans (~2% of the population) are living with disability as a result of a TBI. In 2010, the economic impact of TBI in the US was estimated to be ~US$77bn in direct and indirect costs. Each year in the UK ∼1.4m patients attend hospital following head injury and TBI is the most common cause of death for people in the UK <40 years.
  
Gold standard monitoring of intracranial pressure
There is no cure for severe TBI, and the gold standard management is to monitor intracranial pressure (ICP), caused by brain oedema (swelling). Current clinical guidelines for raised ICP levels suggest thresholds, usually between 20 and 25 millimetres of mercury (mmHg), at which treatment is recommended to either prevent or reduce further damage to the brain. The device used to monitor ICP is an intraventricular catheter system that requires drilling a burr hole in the skull to insert a catheter and placing it in a cavity (ventricle) in the brain, which is filled with cerebrospinal fluid (CSF). This is then connected to an extra-ventricular drain (EVD) that measures ICP. Such systems are accurate and reliable, but also, they are health-resource-intensive modalities, which run a risk of haemorrhage and infection.

Challenges with gold standard monitoring
According to research findings published in the January 2017 edition of the Journal of Neurosurgery, haemorrhage is a common complication of an EVD placement. Among the cases in which patients underwent imaging after a placement procedure, haemorrhage was found in 94 (21.6%). Another study, of 246 EVDs placed in 218 patients over a 30-month period and published in the November 2014 edition of Interdisciplinary Perspectives on Infectious Diseases, reported the cumulative incidence of EVD-related infections to be 8.3%. Further, because of the dearth of qualified neurosurgeons in under-resourced regions of the world, EVD systems are not widely available in LMIC, where the incidence rates of TBI are understood to be high and increasing.

Non-invasive ICP monitoring
Numerous alternatives to invasive gold standard ICP monitoring are in development, but none have established a valid place within a daily clinical setting. A review paper published in the December 2020 edition of the journal Neurotrauma, entitled “Non-Invasive Techniques for Multimodal Monitoring in Traumatic Brain Injury: Systematic Review and Meta-Analysis”, stresses the significance of monitoring ICP and brain oxygenation continuously in severe TBI patients, and suggests that the “two most prominent and widely used technologies for non-invasive monitoring in TBI are near-infrared spectroscopy [a form of photoplethysmography (PPG)] and transcranial Doppler”. Researchers conclude that, “both techniques could be considered for the future development of a single non-invasive and continuous multimodal monitoring device for TBI”.

Transcranial Doppler (TCD) ultrasonography is a non-invasive, painless ultrasound technique that uses high-frequency sound waves to measure cerebral blood flow velocity that may correlate with ICP. Research suggests that in ~15% of cases the ultrasound waves are unable to penetrate the patients’ skulls, and measurement is prone to intra- and inter- observer variability and accuracy. As the TCD system for measuring ICP non-invasively is encountering challenges, so near infra-red spectroscopy is gaining significance. This is a form of PPG technology, which is an uncomplicated, inexpensive, non-invasive, and convenient optical measurement that has the potential of being used at the site of injuries to quickly assess the severity of the head trauma. In the recent case of Tagovailoa, such a non-invasive ICP measurement device could have been applied on the playing field. Over the next decade, expect PPG technology to impact neurosurgery by potentially providing more accurate triaging and further disrupting the gold standard of care for severe TBI patients.
 
Section 8
Brain cancer and early diagnostics

We mentioned the Gamma Knife’s® ability to treat some brain tumours and suggested that patients have benefitted significantly from its use. The first successful modern brain tumour excision was performed in 1878 by William Macewen, a pioneering Scottish surgeon, at the Glasgow Royal Infirmary. At the beginning of the 20th century, contributions by Americans started with Harvey Cushing, who is generally recognised as the father of modern neurosurgery. Working at the John’s Hopkins Hospital in Baltimore, Cushing introduced meticulous documentation of the clinical and pathological details of cerebral tumours and devised several surgical techniques for operating on the brain that became the foundation of neurosurgery as an autonomous surgical discipline. In 1912, he discovered an endocrinological syndrome caused by a malfunction of the pituitary gland, which is named after him: Cushing’s disease.
 
The prognosis for a brain tumour is dependent upon its type, location, size and time of diagnosis, growth and how much can be surgically removed or treated. Factors including age and general wellbeing as well as some recognised genetic factors also influence prognosis. Poor prognosis for brain cancers is perpetuated by the lack of cost-effective, accurate tests that can be used in a primary care setting to diagnose the conditions. This means that a large proportion of brain cancers are diagnosed too late for current treatments to be effective. However, in recent years there have been advances made in detecting brain cancers early and this is expected to significantly improve prognosis.
 
Although there are >120 different types of brain tumours, lesions and cysts, your chances of developing brain cancer is <1%. Brain tumours account for ~90% of all primary central nervous system (CNS) tumours. In 2020, >0.3m people worldwide were diagnosed with a primary brain or spinal cord tumour. According to the Annual Report of the US Central Brain Tumor Registry, >84,000 Americans were diagnosed with a primary brain tumour in 2021. The US National Cancer Institute, suggests ~0.6% of Americans will develop brain cancer in their lifetime and the 5-year survival rate for those that do is only ~33%. This year, >4,000 Americans <15, are expected to be diagnosed with a brain or CNS tumour. In the UK, each year ~16,000 people are diagnosed with a brain tumour and ~ 60,000 people are living with a brain tumour.
 
The causes of brain tumours are not fully understood and occur because of an abnormal growth of brain cells or cells in the brain’s supporting tissues, which can damage the brain, threaten its function and result in death. Some tumours may occur around the edge of the brain and press on certain parts of it, while others can be more diffuse and grow among healthy tissue. In the video below, neurosurgeon Christopher Chandler, who leads the Paediatric and Adolescent Neurosurgical Service at King’s College Hospital, London explains that, “A brain tumour is an uncontrolled growth of a bunch of cells where the ‘off’ switch is missing. This means that there’s nothing telling these cells to stop growing, so they grow and divide. As this uncontrolled mass, or tumour, grows it displaces brain tissue and causes pressure on the surrounding brain. If you don’t remove the tumour or stop it from growing, it will grow so large that it causes critical pressure on the surrounding structures of the brain, which eventually, if untreated, can kill the patient.” See video.  

 
What is a brain tumour?
 
The Holy Grail
Neurosurgeons are frustrated by the fact that brain cancers are often diagnosed late. This is because brain tumours often present with non-specific symptoms and are therefore challenging to diagnose. In the video below, neurosurgeon Ranjeev Bhangoo explains the reasons for a brain tumour to be diagnosed late. “Firstly, the symptoms are non-specific: tiredness, headache, poor concentration - maybe not finding your keys as well as you use to – the sort of thing that can happen to any of us when we’re tired. The classic thing of having a fit or collapsing occur, but they’re unusual. Your GP is only likely to see just one or two brain tumour cases in his or her whole career. . . . Now, if you do get a scan, the chances of you having a brain tumour are incredibly rare. So, just because a neurologist has organized a scan, you mustn’t get worried because it’s very unlikely that you’ll have a brain tumour. But ultimately, through some path or other, you have a scan, usually a CT scan, which is a form of X-ray, which is quick and safe and if there is a tumour it will show. At that point, what will normally happen is that your doctor will refer you to a neurosurgeon”.    
 
How are brain tumors diagnosed?
 
Technologies positioned to reduce neurosurgeons’ frustration with late diagnosis of brain cancers are quick, easy-to-use, and inexpensive blood tests that can diagnose cancer early. Such tests fall into four general categories: (i) complete blood count used to evaluate your overall health and detect a wide range of disorders, (ii) biomarkers, which are molecules found in your blood and other body fluids that can indicate specific cancers, (iii) blood protein testing that measures the amount of protein in your blood to diagnose cancer, and (iv) circulating tumour cell tests, which look for tumour cells that are shed from a tumour and are now circulating through your bloodstream.
 

Detecting brain cancers early
Two recent examples of simple diagnostic blood tests are reported in the August 2022 edition of Clinical Cancer Research and the October 2019 edition of Nature Communications. In the former paper, scientists at Massachusetts General Hospital (MGH) report findings of a study, which detected the presence of brain cancers early by identifying pieces of tumour cells’ genetic material - mRNA - that circulate in your blood. The test, which has a sensitivity of 72.8% and a specificity of 97.7% can characterize brain tumours and monitor their status after treatment. According to Leonora Balaj, a co-senior author, and assistant professor of Neurosurgery at Harvard Medical School, “There is a real need to make brain tumor diagnosis less invasive than the current technique of tissue biopsy. This research demonstrates that it is now feasible to diagnose a brain tumor via a blood test for one of the most common mutations detected in brain tumors”. Findings of the latter paper suggest that certain brain cancers may be detected early from a simple blood test using PPG technology, which has been used in hospital settings since the 1980s to monitor heart rate and relative blood volume. Today, the technology is used in a wide range of commercially available medical devices, as well as smartwatches (the Apple version is an FDA approved medical device) and fitness trackers, for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and detecting peripheral vascular disease. Previously we described how PPG technology is positioned to provide a non-invasive means to monitor ICP in TBI patients.

The 2019 Nature paper describes how PPG easily, cheaply, and accurately identified asymptomatic people with suspected brain cancer. In the first instance, the technology was used on a retrospective cohort of 724 people, which included those with primary and secondary cancers as well as control participants without cancer. PPG was employed to identify biomarkers from patients’ blood samples and a machine learning algorithm was trained to identify specific biomarkers with cancer present. The algorithm was then used on a sample of 104 random participants and brain cancer was detected in 12. The PPG test revealed a sensitivity of 83.3% and a specificity of 87%. According to Matthew Baker, from the University of Strathclyde, Scotland, the paper’s lead author, “This is the first publication of data from our clinical feasibility study, and it’s the first demonstration that our blood test works in the clinic.
 

A global endeavour
These two studies are part of a well-resourced global endeavour to develop an affordable, simple, point-of-care, blood test, which detects cancer before any symptoms occur. Today, biomedical advances move at a much faster pace than medical technology did in the 1950s and 60s when Lars Leksell was developing minimally invasive stereotactic radiosurgery procedures to accurately locate and remove brain tumours. For example, in ~7 years since its foundation in 2015, GRAIL, a US biomedical start-up backed by Jeff Bezos and Bill Gates, has become a global leader in a ground-breaking multi-cancer, early detection, blood test, Galleri®, which has the potential to detect >50 types of cancers before they are symptomatic. This is achieved by looking for abnormal DNA shed from cancer cells in the blood, called cell-free DNA (cfDNA). The Galleri® test uses genetic sequencing technology and artificial intelligence (AI) to scan for patterns of chemical changes in the cfDNA that come from cancer cells but are not found in healthy cells. If validated, the GRAIL test will provide a simple, cheap, non-invasive means to identify a range of cancers in asymptomatic people when they are more likely to respond positively to therapy.
 

Large UK clinical study
In May 2019, the GRAIL Galleri ® blood test was granted US FDA Breakthrough Device designation. The test is only available commercially in the US but is rapidly gaining provenance in other regions of the world. For example, in September 2021, NHS England launched a massive clinical study for Galleri® and set up ~150 mobile clinics in convenient locations across the country to recruit ~140,000 participants. In July 2022, participants were invited to attend two further appointments spaced ~12 months apart. Findings from the study are expected to confirm the accuracy of the test in asymptomatic participants and lead to its regulatory approval. Although Galleri® is the first of its kind to be trialled on such a scale in the UK, it is not the only player and cfDNA is not the only technology.
 

Guardant Health
Another US biotech developing capabilities to detect a range of cancers early from a simple blood test is Guardant Health. Founded in 2011, the company is now ~US$6bn Nasdaq traded global enterprise with annual revenues ~US$110m. In April 2022, Guardant presented new data at the American Association for Cancer Research Annual Meeting. Findings suggested that the company’s investigational next-generation Guardant SHIELD™ assay has the capacity to analyse ~20,000 epigenomic biomarkers that help to detect a broad range of solid tumours using a single blood test. Guardant’s co-CEO, Amir Ali Talasaz said: “These positive results show that the next-generation Guardant SHIELD multi-cancer assay provides sensitive detection of early-stage cancers with the ability to identify the tumor tissue of origin with high accuracy”.
 
Section 9
Takeaways

For millennia neurosurgery, which has its roots in ancient civilizations, was dominated with forms of craniotomies, which opened the skull to access cerebral disorders. In the 20th century the speciality pivoted and introduced less- and non-invasive procedures to deal with a range of brain and CNS conditions. However, the introduction of these were slowed by the fact that the brain is such a well-protected organ and they took nearly half a century to gain regulatory approval and enter the clinic. At the beginning of the 21st century biomedical research is advancing at such a pace and it positioned to significantly transform neurosurgery towards a less- and non-invasive modality. Further, in the next two decades expect gene and cell therapies to substantially increase their influence as treatments for neurodisoders. Over the past three decades novel neuro-pharmaceuticals have been constantly in clinical trials but failed to receive regulatory approval because they did not have an efficatious mechanism to deliver the therapeutics across the BBB. Today, there are a myriad of novel vehicles under development, which are expected to effectively smuggle 21st century pharmaceuticals across the BBB. These are being advanced in parallel to the drugs, and together are positioned to significantly disrupt traditional neurosurgical procedures over the next two decades.  
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  • China is the world’s second largest economy after the US
  • Its MedTech sector is the world’s second largest after the US and accounts for 20% of the global market
  • The size of China’s market is attractive to Western MedTechs but its regulatory and competitive environments are changing, which makes it more challenging for foreign corporations to enter or grow their franchises in China
  • China’s healthcare system has similar structural challenges as those of the US and other wealthy nations: the demand for care is increasing and overwhelming health professionals, which creates care gaps
  • China is ahead of the US and other nations in attempting to reduce such gaps with patient-centric innovative digital therapeutic solutions, which is supported by a deep bench of capabilities
  • Western MedTechs have a lot to learn from Chinese digital health innovations
  • However, Beijing is engaged in an unprecedented mission to become a self-reliant, high-tech economy and a world superpower within the not-too-distant future
  • Misjudging Beijing can have significant commercial consequences
 
Learn from the Chinese, but don’t misjudge Beijing


An earlier Commentary ended by posing the question whether Western MedTechs can compete with China’s large and rapidly growing domestic medical device industry, which benefits from China being the second largest MedTech market in the world behind the US, with annual sales revenues of ~US$84bn in 2020. China now accounts for ~20% of the global medical device market, which is expected to continue an upward trajectory, supported by the nation’s quickly aging population, rising incomes, and the continued enhancement of health services.
 
With this foundation, Beijing is incentivising its domestic MedTech companies to expand internationally. Beijing’s 14th Medical Equipment 5-Year Plan (2021–25) sets a goal to have >6 Chinese MedTechs among the top 50 global industry corporations by 2025. The policy complements Made in China 2025, which is a macroeconomic strategy to reduce China’s reliance on imported foreign products including medical devices. So, while China’s domestic market is becoming more challenging for foreign MedTechs, Beijing is supporting the growth and expansion internationally of its local medical device companies to compete with their Western counterparts. For example, Mindray Medical International, China’s biggest medical device corporation by sales revenue, is the #4 ultrasound vendor in the world and over the next 5 years, expects to increase its overseas sales revenues from <50% today to ~70%.
 
Despite Beijing’s ‘for China’ policies, many Western MedTech leaders view China as a significant commercial opportunity, recall foreign corporations that have prospered in the nation over the past two decades and suggest that it is important to do business there if one of your company’s objectives is to grow its international franchise. But China has changed, and its regulatory and competitive ecosystems are tightening, which present headwinds for Western MedTechs that were not present a decade ago. Further, China has an ambition to become a self-reliant, world leading high tech nation in the not-too-distant future, which could have consequences for foreign companies participating in the Chinese market.
 
With ~400m chronic disease patients, a fast-aging society, vast and rapidly rising healthcare costs, and an economy that has slowed, China is resolute in developing a new model of digitally enabled, patient-centred integrated healthcare. This ambition is supported by significant resources and a deep-bench of capabilities positioned to enable China to achieve its goals, which include transforming its medical devices sector by supporting the development of world class, high tech, patient-centric, digital enterprises.
 
All these factors suggests a dilemma for Western MedTech leaders: China is too big to ignore, but Beijing is too powerful and unrelenting to misjudge.

 
In this Commentary

This Commentary has 3 sections. The first, entitled ‘Reducing care gaps with digital therapeutic innovations’, suggests that China, the US, and other developed nations share a common challenge of care gaps created-by a limited supply of health professionals and a large and increasing demand for care. China’s attempts to resolve these gaps differ from other nations in their scale and nature. They are nationwide innovations predicated upon digital AI strategies, which manifest themselves in digital platforms that directly address patients’ healthcare needs. We briefly describe a few examples of these and suggest that they are advantaged by China’s data policies and AI competencies. Section 2, entitled ‘Capabilities’, describes Beijing’s plans for China to become the world’s leader in AI technologies within the next decade and suggests that China has the capabilities to achieve this goal in the proposed timeframe. The final section entitled, ‘Understanding Beijing’, briefly describes the tightened regulatory and competitive environments and suggests how this impacts the business models of Western corporations seeking to enter the Chinese market or increasing their existing franchises. We posit that China and the Chinese are significantly different to Western democracies and Westerners and emphasize the Chinese Communist Party’s uncompromising ambition to become economically self-reliant, a world superpower and a global high-tech leader. Misjudging Beijing could be commercially damaging for foreign corporations.
 
 
1: Reducing care gaps with digital therapeutic innovations
 
China has similar structural healthcare challenges to the US and other developed economies, which manifest themselves in care gaps caused by a limited supply of overworked healthcare professionals and a vast and rapidly growing demand for care from aging populations. The Chinese population ≥65 years is ~140m, and this cohort is expected to grow to ~230m by 2030. By that time, the nation’s aging middle class will have grown from today’s ~0.3bn to ~0.7bn. High-risk behaviours like smoking, sedentary lifestyles, and alcohol consumption as well as environmental factors such as air pollution take a huge toll on health and increase the demand for care. According to Statista, a large portion of the Chinese population suffer from chronic lifestyle diseases, which account for >80% of the nation’s ~10m deaths each year; >0.5bn people are overweight or obese, while high blood pressure is a common illness among >0.4bn people. China’s healthcare expenditure is growing at >8% a year, and without reform, the nation’s health spending could increase to >US$2trn by 2030. Such factors, together with the nation’s economic slowdown motivate Beijing to prioritize the transformation of its healthcare system.
Significant differences in tackling care gaps

A significant difference between China and the US and other wealthy nations, whose healthcare systems are all in need of reform, is that China has been quicker to develop digital therapeutic technologies to reduce care gaps and relieve its large and rapidly growing burden on hospitals, care systems and families caring for the sick and elderly.
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Should MedTechs follow surgeons or patients?

In any healthcare system, people should be the priority, but because of a dearth of health professionals, overburdened hospitals, soaring health costs and overworked physicians, patients’ needs are often not prioritized. China has been no exception but expects to reverse this trend with the help of artificial intelligence (AI) enabled digital therapeutic solutions that put patients first. Examples include: WeDoctor, Alibaba Health, JD Health, DXY.cn. and Ping An Good Doctor. These, and other digital innovations, provide a range of health services including, online consultations, hospital referrals and appointments, health management, medication regimens, medical insurance, and wellness and prevention programmes. China’s early adoption of AI medical solutions has benefitted from Beijing’s “Healthy China 2030” policy, which, since its launch in 2016, has directed substantial funds to Chinese AI start-ups developing technological innovations to ease the burden of care gaps. According to Tracxn, one of the world’s largest tracking platforms, there are ~227 AI driven healthcare start-ups in China. Let us briefly describe three established ones: WeDoctor, DXY.cn and Ping An Good Doctor.
 
WeDoctor

Tencent-backed WeDoctor, founded in 2010 to provide people with physician appointments, is based in Hangzhou, a city of ~11m and the capital of China’s Zhejiang province. Since its inception, the company has grown into a multi-functional platform offering a range of medical services predicated upon a database of >2,000 Western treatment plans, online pharmacies, health insurance, cloud-based enterprise software for hospitals and other services. Today, WeDoctor hosts >270,000 doctors and ~222m registered patients. It has an impact on reducing care gaps and is one of the few online healthcare providers qualified to accept payments from China's public health insurance system, which covers >95% of the population. WeDoctor's services are especially valued in rural areas, where there are fewer physicians than the national average of 1.5 per 1,000 people.

In response to the COVID-19 crisis the company launched the WeDoctor Global Consultation and Prevention Center (GCPC),  which provided a free 24/7 global online health enquiry service, psychological support, prevention guidelines and real-time pandemic reports. Just before the pandemic, WeDoctor planned to float its medical and health service function on the Hong Kong stock exchange at a valuation ~US$7bn. However, it was pulled because of the Beijing-Hong Kong tensions. WeDoctor’s. other business functions, which include health insurance and health data services, were not included in its proposed flotation, and are likely to stay private to appease Chinese regulators.
 
DXY.cn
 
DXY.cn is an online healthcare community for doctors, patients, and healthcare organizations. It was founded in 2000 and is also based in Hangzhou. Over the past 2 decades it has evolved into the world’s largest community of physicians who use the platform to gain insights from colleagues, discuss new medical research, and report unusual clinical events. More recently, DXY has added a consumer-facing service that brings wellbeing advice and medical consultations to the public. DXY generates revenues from public-facing medical advertising and job recruitment for its life science clients, as well as clinics where patients can receive in-person medical care. According to TechCrunch, in 2021, DXY reached ~130m consumers, >9,000 medical organizations, and had a registered user base of ~20m.
 
Ping An Good Doctor

Ping An Insurance (Group), is one of the world’s largest financial services companies with >210m retail customers and ~560m internet users and is headquartered in Shenzhen, southeastern China. In 2014, it launched Ping An Good Doctor to provide end-to-end, AI-powered health services directly to patients. These include 24/7 online consultations, diagnoses, treatment planning, second opinions, and prescription management solutions. Today, Good Doctor has ~400m registered users and drives synergies across China’s healthcare ecosystem. The platform collaborates with >3,700 hospitals and is supported by an off-line healthcare network of >2,200 in-house medical staff and ~21,000 contracted experts to ensure quality and accuracy of its medical services. The company provides insurance coverage for both users and physicians, which helps to ease China’s healthcare payment pressures. Ping An Good Doctor’s technology also assists patients to manage their personal health records, treatment plans, and medical histories.
 
In 2019, the company launched the world's first AI-powered, un-manned healthcare service: the One-minute Clinic. This is a 3m2 booth, which patients walk into, enter their digitized medical history from their mobile phones, and add their symptoms. The clinic’s algorithms, which have been trained on data from >300m medical records, then make a diagnosis, prescribe drugs, and provide a treatment plan. Medications are purchased from an adjacent vending machine. Within a year of the start of the first clinic, Good Doctor rolled out ~1,000 units in shopping malls, airports and other public spaces throughout China providing onsite medical and pharmaceutical services 24/7. Today, the clinics provide accessible and affordable medical and health services to >3m users. Good Doctor believes that its AI-driven, un-manned clinics have a promising future helping to reduce China’s care gaps and has plans to expand its services into Southeast Asia. In December 2019, the company signed a strategic collaboration with Merck, an American pharmaceutical multinational to advance further intelligent healthcare in China.

 
Internet hospitals

Digital initiatives like those described above have led to the development and spread of internet hospitals, which are online medical platforms associated with offline access to traditional hospitals that provide a variety of services directly to patients. Today, internet hospitals are booming in China, driven jointly by government and market initiatives.
 
The first internet hospital was established in China’s Guangdong province in October 2014. It consisted of four clinics operated by doctors from the Second People's Hospital, an online platform operated by a medical technology company, and a network of medical consulting facilities based in rural villages, community health centres, and large pharmacy chain stores. Initially webcams were used for patients to communicate with physicians and share medical images of their conditions. A patient's vital signs were taken by on-site machines and uploaded onto the system. With all this information, physicians made a diagnosis and prescribed medications, which patients obtained from nearby pharmacies. According to the Lancet, two months after its launch, China’s first internet hospital “was dealing with ~200 patients and issuing ~120 prescriptions every day”. After six months, the number of patients had increased to >500 a day, ~60% of whom needed prescriptions. Soon afterwards, a network of consultation sites expanded to >1,000 facilities in 21 of Guangdong’s municipalities. In 2018, Beijing gave the legislative green light for internet hospitals, which prompted many Chinese digital health companies to start using internet-based AI solutions to meet the country’s medical and healthcare needs and contribute to the reduction of care gaps. By August 2021, >1,600 internet hospitals had been established in China. The public and physician acceptance of these and Beijing’s support for them suggests a new era in digital healthcare.

 
Internet + Healthcare” initiatives

Since 2018, a range of Internet + Healthcare” initiatives have consolidated and enhanced the position of digital healthcare innovations. The success and continual improvement of China’s digital health service platforms all benefit from Beijing’s policies to facilitate medical practice supported by digital tools. Laws and policies have been issued to support this digital transformation, including health data digitalization, data sharing, and interoperability across the whole of China’s healthcare ecosystem. After the outbreak of the COVID-19 pandemic, the government increased its “Internet + Healthcare” efforts to include telemedicine in state medical insurance coverage, and to lift barriers for prescribed drugs sold online.
 
Data advantage

Compared to the US and other Western democracies, China has significant data advantages to drive its digital healthcare initiatives. Eric Topol, a cardiologist, director of the Scripps Research Translational Institute, and author of Deep Medicine: How AI can make healthcare human again, argues that “China has a massive data advantage when it comes to medical AI research”. To put this in perspective, consider that Chinese patient healthcare data are drawn from the nation’s provinces, many of which have populations of >50m. By contrast, US AI research tends to be based on patient data often drawn from one hospital. China’s big data advantage allows machine learning algorithms to be more effectively trained to perform key functions in a range of clinical settings. Another comparative advantage of China is its large workforce of AI specialist, data scientists, and IT engineers, which can work on healthcare projects at comparatively low costs. This is partly the result of China’s emphasis over the past four decades to encourage science, technology, engineering, and mathematics (STEM subjects) in their schools and universities to fuel Beijing’s technological ambitions.

Not known for good data governance practices, but with intensions to expand internationally, China is now tightening its data protection regulations. For example, in November 2021 Beijing introduced the Personal Information Protection Law (PIPL), which is designed to prevent data hacks and other nefarious uses of sensitive personal information. Much like the EU’s General Data Protection Regulation (GDPR), the PIPL stipulates that an individual’s explicit consent must be obtained before their medical health data are collected, and it places the burden on medical AI companies to ensure that these data are secure.
 
2: Capabilities
 
Healthy China 2030

In October 2016, President Xi Jinping announced the nation’s Healthy China 2030 (HC 2030) blueprint, which put patient-centred healthcare at the core of Beijing’s healthcare plans, recognizing its ability to influence both social and economic development. The policy sets out China’s long-term approach to healthcare and shows the nation’s commitment to participate in global health governance, which Beijing recognises as necessary as it seeks to extend its international reach. By 2030, Beijing aims to reach health equity by embracing the United Nations’ Social Development Goal 3.8, which seeks to “Achieve universal health coverage, including financial risk protection, access to quality essential healthcare services and access to safe, effective, quality and affordable essential medicines and vaccines for all”. In 2019, Beijing announced an action plan to accelerate the delivery of Healthy China 2030. This puts patients first in an endeavour to build a healthy society by leveraging AI technologies to reduce the prevalence of lifestyle induced chronic disorders and subsequent care gaps. The World Health Organization (WHO) believes the policy “has the potential to reap huge benefits for the rest of the world”.
 
AI capabilities
 
As China’s economy has matured, its real GDP growth has slowed, from ~14% in 2007 to ~7% in 2018, and the International Monetary Fund (IMF) projects that growth will fall to ~5.5% by 2024. Beijing refers to the nation’s slower growth as the “new normal” and acknowledges the need to embrace a new economic model, which relies less on fixed investment and exporting, and more on private consumption, services, and innovation to drive economic growth. Such reforms are needed for China to avoid hitting what economists refer to as the “middle-income trap”. This is something many Western economies (and corporations) face: it is when countries achieve a certain economic level but then begin to experience diminishing economic growth rates because they are unable to effectively upgrade their economies with more advanced technologies. To avoid this scenario, for the past three decades, China has been investing in AI and systematically upgrading its economy.


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Today, China has a significant supply of innovative AI talent to deliver a Healthy China by 2030. Some of the world’s largest technology companies are Chinese and all are developing different aspects of AI applications. For example, Alibaba’s cloud division concentrates on using AI in healthcare and Baidu, which has numerous AI research laboratories in the US, is focussed on a range of AI innovations, which include “deep learning”, and “big data”. More recently, Baidu added a Business Intelligence Lab, which develops data analytics for emerging data-intensive applications, and a Robotics and Autonomous Driving Lab, which specializes in computer vision.
In 2017 China's State Council launched a 3-step plan to become a world leader in AI technologies by 2030, with a domestic AI industry valued ~US$150bn. Beijing completed step 1 in 2020 by establishing a “new generation” of AI technologies and technocrats and developing national standards, policies, and ethics for its emerging industry. Step 2 is anticipated to be completed by 2025, by which time China expects to achieve “major breakthroughs” in AI applications that will help the completion of upgrading the nation’s industrial sector and thereby avoiding the middle-income trap. The final step is anticipated to take place between 2025 and 2030, which, among other things, will project China internationally as the world leader in AI technologies.
 
3: Understanding Beijing
 
Regulatory changes

A decade ago, foreign MedTechs operated in China with relative ease. Chinese regulations were lighter than they are today, and companies were supported by a multi-layered network of small scale and localised sub-distributors. This fragmented structure resulted in higher prices and tended to encourage corruption, but the relatively high margins obtained from foreign products allowed medical device corporations to compensate the multiple distribution levels and still make a profit. In return, domestic Chinese distributors managed the market and foreign MedTechs did not engage directly with hospitals and physicians.
 
Volume-based procurement

Recent regulatory changes have disrupted this modus operandi for foreign MedTechs. One change positioned to have a significant impact on MedTech profits is volume-based procurement (VBP). This is aimed at lowering the price of medical consumables by tendering the market volume of cities, provinces, or the country to manufacturers with the lowest price. Following a successful pilot with pharmaceuticals, VBP was extended to medical devices in 2019, and since then it has had a significant effect on certain products. For example, the price of cardio stents and hip and knee implants have been reduced by ~70% to ~90%. China’s message is clear: Medtechs are either ‘in’ with significantly lower prices, or ‘out’. This suggests that companies wishing to enter or grow their franchise in the Chinese market will have to adapt their business models by accelerating their pre-launch registrations and post-launch commercialization strategies for new products as margins on legacy offerings are expected to be substantially reduced. However, review processes for new offerings have become longer, more bureaucratic, and more expensive than they were five years ago. For example, if a Class 2 device without clinical studies took ~9 months to register five years ago, today expect ~2 years. VBP has forced foreign MedTechs to consolidate their multi-layered distribution channels to improve economies of scale. 
 
More recently Beijing has introduced a two-invoice policy for the medical devices industry: (i) MedTech to a distributor, and (ii) distributor to a hospital. This will push small and less competitive distributors out of the market and shorten and consolidate supply chains. The likely effect of this is for Chinese distributors to concentrate more on logistics to “deliver product”, rather than managing the market. To the extent that this is the case, a larger share of customer engagement will become the responsibility of MedTechs.
 
This will mean that foreign corporations trading in China will need to reassess their capabilities and adjust their business models. Further, MedTechs operating in China should expect VBP to increase the significance of “value”. This is because the policy is likely to enhance the purchasing power of hospital administrators and reduce that of physicians.  As a result, companies might expect procurement conversations to focus less on clinical outcomes and more on the overall value of products and their potential to minimize costs. Many readjustments companies will be obliged to make to their business models may be achieved by having someone local on the product management team rather than engaging high-margin agencies to resolve critical, but relatively simple domestic challenges.
 
A narrow window of opportunity for foreign MedTechs

Beijing’s “in China for China” policy makes it a condition that foreign companies entering the Chinese market must share their technology and intellectual property (IP) with a domestic “partner”. Beijing has been using this condition to acquire valuable scientific knowhow, which has helped the country to develop a large domestic medical device industry. According to a 2021 research report from Deloitte, a consulting firm, “China now boasts over 26,000 medical device manufacturers”. Beijing’s policies render China a substantially more challenging market to enter and to grow in than it was five years ago. China’s market opportunities for foreign corporations are not only getting tighter; they are getting shorter, and their orientation is changing away from surgeons towards patients. Further, Beijing is on a relentless drive towards self-reliance and tolerates the presence of Western companies in its domestic markets only for as long as they contribute offerings that are useful to the Chinese Communist Party. If China is successful in delivering on its healthcare and high-tech development plans, the window of opportunity for many foreign MedTechs could be only ~10 years.
 
China’s different

China and the Chinese are unlike the West and Westerners. When Deng Xiaoping’s started China’s reforms in 1978 and opened the nation to the world’s trading economies, he created a socialist market economy, in which private capitalists and entrepreneurs co-existed with public and collective enterprise. This formed the foundations for China’s phenomenal economic growth, prosperity, reduction of poverty, massive infrastructure investment, and development as a world-class technology innovator. As a result, many Western business leaders and politicians believed that China had abandoned ideology in a similar way that former communist regimes of Eastern Europe did in the early 1990s after the fall of the Soviet Union. However, such a transformation did not happen in China, which remains a one-party authoritarian state, tightly governed by the Chinese Communist Party (CCP), whose constitution states that China is a “people’s democratic dictatorship”. The CCP has a mission to become the world’s leading technology economy by 2030. This is backed by substantial sovereign wealth and a supply of relevant high tech human capital and an impressive history of national achievements.
 
Scale and speed of transformation

The phenomenal politico-economic progress China has made in a relatively short time is an indication of the nation’s determination, and its ability to affect change, and contextualizes Beijing’s policies to make China a self-reliant economy in the not-too-distant future. A 2022 report jointly released by China’s Development Research Center and the World Bank highlights the nation’s transformation in just four decades, from a struggling agrarian society to a global superpower. The nation’s achievements include increased health insurance coverage to >95% of its 1.4bn population, lifting ~0.8bn people out of poverty, which accounts for ~75% of global poverty reduction in the same period, a burgeoning middle class, which by 2030, will have grown from today’s ~0.3bn to ~0.7bn. In 2010, China overtook Japan to become the world's second largest economic power after the US when measured by nominal GDP. According to the World Bank, in 1960, China's GDP was ~11% of the US, and in 2019, ~67%. Not only is China the world's second-largest economy it has a permanent seat at the United Nations Security Council, modernised armed forces, and an ambitious space programme. China’s growing international clout and economic leadership positions it well to replace the US as the greatest superpower.

Such factors provide a context for Western corporation with global pretentions wishing to engage with and learn from China. At the 13th Annual National People’s Congress in March 2022, Premier Li Keqiang called for “faster breakthroughs” in key technologies, and said the government would increase the tax rebate for small and medium-sized science and technology firms from 75% to 100% and grant tax breaks for basic research to encourage innovation. Significantly, the Congress also underscored self-reliance in China’s economic priorities amid warnings of trade headwinds and geopolitical complexities.

 
Takeaways
 
China is too big a commercial opportunity to ignore. In 2021, China accounted for >18% of the global economy, rising from ~11% in 2012, its GDP was ~US$18trn, and per capita GDP reached US$12,500, which is close to the threshold for high income economies. In recent times, the contribution of China's economic growth to the world economy has been ~30%, which makes China the largest growth engine for the global economy. However, the relationship between China and the rest of the world is changing. As China becomes more self-reliant, its exposure to the world has decreased. Add to this (i) international trade disputes, (ii) increasing geopolitical tensions between the US and China, (iii) the nation’s evolving new rules to evaluate technology flows, (iv) increase of protectionism and (v) its healthcare mission to pivot towards patients, and you have significantly changed trading conditions than a decade ago. Misjudging Beijing’s rapidly evolving commercial ecosystem could be costly for Western MedTechs.
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  • The traditional strategy of the medical devices industry has been to maximise the experience of the surgeon
  • This has resulted in paying little attention to the demands of patients
  • Surgeon populations are shrinking while the general population is growing, aging, becoming ill and demanding care
  • This creates care gaps, which are challenging to reconcile, prolong unnecessary suffering and cause unnecessary deaths
  • Reconciling the shrinking supply of health professionals with the increasing healthcare demands has given more weight to patient demands
  • MedTechs will be obliged to recalibrate their approach to patients principally because regulators are involving them in the approval process of medical devices
  • Patient centric digital therapeutic solutions help to reduce care gaps
  • However, developing such digital therapeutics and involving patients will not come easy to traditional MedTechs because of their lack of capabilities and organizational culture
  • Notwithstanding, to be relevant in the future, MedTechs will need to continue to improve their ties with surgeons while increasing their focus on the large and rapidly growing patient demands
 
Should MedTechs follow surgeons or patients?
 
 
Traditional MedTech business models are overwhelmingly focussed on manufacturing physical devices for surgeons to use in episodic, hospital-based, interventions. Over decades, a symbiotic relationship between surgeons and medical device manufactures has been established and led to significant commercial success for both parties. This has meant that MedTechs have not paid the attention they should have to the growing demands of patients, which include primary prevention and screening through diagnosis and staging to treatment, rehabilitation, and the subsequent management of a condition. Should medical device companies double-down on their business models to follow surgeons, or should they change approach and follow patients?
 
In this Commentary

This Commentary has 2 sections: (i) Follow surgeons, and (ii) Follow patients. Section1 suggests that medical device companies will need to continue their mutually beneficial relationships with physicians but tighten their governance ties. Further, leaders might consider some aspects of surgeon populations, which could impact their business model. These include: (i) the increasing shortages and aging of surgical populations, (ii) burnout among surgeons that prompts early retirement, and (iii) the prevalence of unnecessary surgeries. Section 2 considers the business model of MedTechs following patients and suggests that this is likely to become more relevant in the future as regulators are encouraging patient participation in the approval process for medical devices. Further, patient demands are supported by advancing technologies and smart platforms such as PatientsLikeMe. Patient centric solutions tend to be digital therapeutics, based on software rather than hardware. Solutions that address patient care pathways require scarce digital, data management and artificial intelligence (AI) capabilities, which MedTechs tend not to have. To stand a chance of attracting these, MedTechs will need to develop non-hierarchical, agile working cultures with the capacity to innovate at speed. The significance of business models that improve patients’ care pathways is illustrated by two recent, transformative MedTech deals. Takeaways suggest MedTechs should continue following surgeons, albeit under enhanced governance principles and involve patients in the development of devices and increase their capabilities to provide patient centric digital solutions.
 
 
SECTION 1
Follow surgeons
 
The medical devices industry is “big business”. In 2021, the US devoted ~US$199bn (~5.2%) of annual national health expenditures to medical devices. Over the past four decades mutually beneficial relationships between surgeons and medical device companies have been built, and this forms the basis of a dominant industry business model to “follow surgeons”.
 
Surgeons play a crucial role in the conceptualization, development, and enhancement of medical devices; they influence hospital purchasing decisions, and are compensated for providing these services. Further, they are remunerated for representing MedTechs at conferences, giving speeches on behalf of corporations, and playing a critical role in training physicians to use devices because their efficacy is often associated with a specific use technique that needs to be taught. Further, surgeons may receive research grants from MedTechs and be promoted because of their association with a successful innovation. More recently, with the rise of medical device start-ups, the financial incentives to surgeons have included equity stakes in lieu of cash for various contributions. This means that significant financial ties between medical device companies and surgeons are relatively common, which can be the basis for potential conflicts of interest.
 
MedTechs code of conduct

AdvaMed, a US medical device trade association, based in Washington, DC, is aware of such conflicts and suggests that physicians should be compensated at fair market rates for work they perform. The Association is against equity compensation and says that there should be no link between the commercial success of a medical device and a physician. AdvaMed encourages voluntary, ethical interactions and advises member organizations and physicians to disclose all potential conflicts of interest, which include consulting arrangements, training, support of third-party educational conferences, participation in sales and promotional meetings, gifts, grants, and charitable donations.
 
Despite AdvaMed’s best efforts its suggested code of conduct does not appear to work. A bibliometric analysis of 100 clinicians receiving compensation from 10 large MedTechs and published in the November 2018 edition of JAMA Surgery found that conflicts of interest were not declared in 63% of 225 research projects that resulted in publications. Given the increasing significance of environmental, social, and governance (ESG) criteria among socially conscious investors to screen potential investments, it seems reasonable to suggest that MedTechs might consider regularly disclosing all their financial ties with surgeons and health professionals.
More issues to consider

In addition to the increasing significance of ESG issues, there are some further questions associated with MedTech business models that follow surgeons, which corporate leaders might wish to reflect upon. These include: (i) the surgeon population is aging and shrinking, (ii) surgeons have a higher propensity to burnout than other medical specialities, and (iii) surgeons are responsible for a substantial number of unnecessary operations. Let us describe these in a little more detail.
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Shrinking surgeon populations

Throughout the world, populations of surgeons and health professionals are shrinking. Findings of a 2016 US Department of Health and Human Services report suggest that by 2025, there will be shortages in 9 out of 10 surgical specialties in America, with the greatest reduction in ophthalmology, orthopaedics, urology, and general surgery. Research prepared for the Association of American Medical Colleges (AAMC) by the healthcare consulting firm IHS Markit and published in June 2020, suggests that, by 2032, the US could lack ~23,000 surgeons. Although the US has a higher number of total hospital employees than most countries, nearly half of that workforce is comprised of non-clinical staff who are not directly involved in delivering care. For instance, compared to Italy and Spain, America has fewer practicing physicians per capita: 2.6 per 1,000 inhabitants, compared to 4 in Italy and 3.9 in Spain. According to the World Health Organization (WHO), the global shortage of health workers is projected to reach 13m by 2033.
 
Care gaps

One reason for this projected shrinkage is that a large percentage of surgeons are nearing traditional retirement age. For instance, more than 2 in 5 currently active American doctors will be ≥65 years within the next decade. Further, people are living longer, and a substantial percentage are not staying healthy and need care. According to the US Census Bureau the number of Americans ≥65 is expected to reach ~84m by 2050, which is ~2X the 2012 level of 43m. Among this older population there is a large and growing prevalence of chronic lifetime diseases such as cancer, diabetes, heart conditions, respiratory diseases, and mental illness. In the US there are ~150m people with such conditions and ~40% of these are living with ≥2 chronic diseases. According to the US Centers for Disease Control and Prevention, ~90% of the US$4.1trn annual medical spend (~20% of the country's GDP) is attributable to chronic disorders. Such trends magnify the vast and growing pressure on a shrinking pool of health professionals, and this creates challenging care gaps.
 
Digital therapeutics

Care gaps will not be reduced by medical schools training more physicians and nurses. This takes too long to have an impact on the size of the problem. The UK has attempted to reduce care gaps by importing physicians: ~190,000 of the 1.35m NHS staff in England report a non-British nationality, and ~27% of NHS staff in London report a nationality other than British. This policy raises some ethical issues as most are imported from developing economies with underdeveloped healthcare systems and a scarcity of health professionals. The option to import physicians is not open to the US because its immigration policies make it difficult for international health professionals to work in America. Recently, many advanced industrial economies have sought to reduce their care gaps by developing digital therapeutic solutions for patients, which extend the reach of physicians by overcoming time, place and personal constraints that limit care delivery.
 
Surgeon burnout

Findings of a research study published in the June 2018 edition of the Journal of the American College of Surgeons suggest that the prevalence of burnout among surgeons has increased over time. The research references the 2015 Medscape Physician Lifestyle Report, which argues that burnout among surgeons is on the rise and documents burnout rates among various specialisms ranging ~37% to ~53%, with general surgeons nearing the top of the list at 50%. Research on the impact of the COVID-19 crisis on healthcare professionals published in the December 2021 edition of the Mayo Clinic Proceedings, found that ~1 in 3 US physicians expressed a clear intention to reduce their work hours, and ~1 in 4 intended to leave their practice altogether. Such trends are concerning considering the aging of the US population and the subsequent increased pressure this puts on healthcare systems.
 
Many factors contribute to surgeon burnout. Common causes among American surgeons include long work hours, delayed gratification, challenges with work-home balance, and issues associated with patient care in a changing healthcare ecosystem. According to the WHO’s International Classification of Diseases, (ICD-11) burnout results from “chronic workplace stress that has not been successfully managed”. It is characterised by being emotionally exhausted, feelings of cynicism and loss of empathy and a sense of low personal accomplishment with respect to one’s work. A meta-analysis of the prevalence of burnout published in the March 2019 edition of the International Journal of Environmental Research and Public Health  suggests that surgeons experience elevated rates of depression and psychiatric distress and posits that burnout among junior surgeons is at an epidemic level, which affects patient safety, quality of care and patient satisfaction.
 
Unnecessary surgeries

Another issue for medical device leaders to consider is the incidence rates of unnecessary surgeries. These are any intervention, which is not needed, not indicated, or not in the patient’s best interest when weighed against other available options.  Unnecessary surgeries are not a recent phenomenon: they are a significant reality that continue to expose patients to unjustified surgical risks. In 1976, the American Medical Association (AMA) called for a congressional hearing to address the issue, claiming that each year there are “2.4m unnecessary operations performed on Americans at a cost of US$3.9bn and that 11,900 patients had died from unneeded operations”.  Across the US, the phenomenon is patchy. A cross-sectional study of five US metropolitan areas and published in the January 2022 edition of the Journal of the American Medical Association found significant differences in physician treatment recommendations across a range of specialisms.

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Most common unnecessary surgeries

The incidence rates of unnecessary surgeries appear more prevalent in spinal, gynaecological and some orthopaedic procedures. Clinical trials have shown that a significant percentage of spinal fusions for back pain do not lead to improved long-term patient outcomes when compared to non-operative treatment modalities, including physical therapy and core strengthening exercises. Despite these findings, spinal fusion rates continue to increase significantly in the US.
Further, women are at high risk of unnecessary hysterectomies and caesarean sections. Although these rates are moderating, a study for the American College of Obstetricians and Gynecologists, suggested that hysterectomies were improperly recommended in ~70% of cases, even though there were non-surgical alternatives. Hysterectomies can lead to bladder and bowel dysfunction, prolapse, and incontinence,  as well as a 4-fold increased risk of pelvic organ fistula surgery. A study in Health Affairs found that caesarean rates varied significantly (from 2.4% to 36.5%) in hospitals across the US, even among those with low-risk pregnancies.
 
Another study published in Health Affairs suggests that after patients received information on alternatives to joint replacement surgeries, ~26% had fewer hip replacements and ~38% had fewer knee replacements. Each year in the US, >1m total hip and total knee replacement procedures are performed.
 

 
SECTION 2
Follow patients
 
It is not uncommon for MedTech leaders to say that they put “patients first” when developing devices. However, although things are changing, which we describe below, this is more rhetorical that factual. MedTech R&D teams tend to be relatively remote, inwardly focussed, and, particularly in the US, patient voices are generally ignored and not perceived as an integral part of the process.
 
However, the healthcare ecosystem is changing and “following surgeons” cannot constitute an entire strategy for MedTechs. In the future, MedTech business models that follow patients will be driven by patients’ knowledge and their increasing demands to participate in their healthcare decisions, the movement towards personalized care, and regulators’ mandates to incorporate patient perspectives into the development of medical devices and approval processes (see below). Earlier, we suggested that, when surgeons engage with medical device corporations there are competing interests, which often are not disclosed. By contrast, patients are primarily driven by their own safety and wellbeing, which, contrary to surgeons, are grounds for promoting mutual accountability and understanding with healthcare providers.
 
To remain relevant, MedTechs will need to incorporate patient perspectives and patient data into their business models, not least because patients are co-producers of their health and represent a consistent factor, probably the only consistent factor, throughout the care pathway. Further, patients, empowered by digital therapeutics and health information from wearables, hold invaluable personal data, which are often critical to improving care pathways, and outcomes.

 
PatientsLikeMe
 
Patient voices were loud and influential long before MedTechs recognised the significance of engaging patients in development processes. Consider PatientsLikeMea digital platform founded in 2004, with a mission to improve the lives of patients by sharing knowledge, experiences, and outcomes. The company quickly grew to become the world’s largest integrated community, health management, and real-world data platform. Via the site, users can document and share their experiences, track their conditions, and communicate with others living with similar disease states. Data generated by patients who use the site are systemically collected and quantified by the company, while providing users with an environment for peer support and learning. Today, PatientsLikeMe has >0.8bn users representing >2,900 conditions. The company makes money by selling the information patients share in de-identified, aggregated, and individual formats. In 2019, the platform was acquired by the UnitedHealth Group, an American multinational healthcare and insurance company, after former President Trump’s administration forced it to seek a buyer because its majority owner was China-based iCarbonX.
 
Increasing patient input in approval processes for medical devices

What will make MedTechs wake up to the significance of patient perspectives in the development of medical devices are initiatives and demands made by regulators. For the past decade, European regulators through the European Medicine’s Agency (EMA). have solicited patient inputs into their approval process for medical devices. In 2014, the FDA and the EMA created a joint working group to share knowledge and information on patient engagements. In 2007, the Clinical Trials Transformation Initiative (CTTI), a public-private partnership was co-founded by the US Food and Drug Administration (FDA) and Duke University and modelled on the EMA Patients’ and Consumers’ Working Party. CTTI’s mission is to develop and drive patient involvement in the development and approval of devices, which is expected to increase the quality and efficiency of clinical trials. Since its foundation, the CTTI has become a leader in evolving and advancing clinical trials, making them more efficient, and patient focused.
 
In December 2017, a nationwide request in the US was made for patients and patient advocate groups to join the CTTI and become more involved in healthcare product development and in the FDA product reviews. This call came ~1 year after the 21st Century Cures Act became law in December 2016. The Act’s intention is to expedite the process by which new medical devices and drugs are approved by easing the requirements put on companies seeking FDA approval for new products and indications. Under Section 3001 of the Act, the FDA is required to report any patient experience data that were used to support an approval process and to publicly provide aggregate reports on agency use of those data at five-year intervals. This suggests that MedTechs wanting new FDA approvals will need to provide patient-driven data.
 
These initiatives are driven by an ever-improving consumer-controlled social and health data ecosystem, advancements in personal genetic understanding, and increased healthcare cost-sharing. Patient-driven changes are systematically beginning to inject more than token patient participation and viewpoints into all stages of device and drug development.

 
A cultural shift

Improving patient engagement in the development process of medical devices will be challenging for MedTechs that have focussed their business models mainly on manufacturing physical devices and building relationships with surgeons, rather than developing digital assets for patients. The latter requires scarce data management and AI capabilities, which do not thrive in conservative hierarchical organizations. Rather, they require a culture, which promotes innovation at speed and agile ways of working. A recent survey of European executives by The Economist Intelligence Unit, found that poor collaboration between a company’s IT function and its business units slows progress in a firms’ digital objectives. MedTechs that are slow to develop digital capabilities that address patient needs and integrate these into their business models risk not being a party to decisions shaping the emerging healthcare ecosystem.
 
The increasing significance of scarce AI talent

Digital therapeutics predicated upon AI techniques, which are growing in significance with healthcare systems, require large amounts of data collected from electronic health records (EHR), medical images, and information from patients’ wearables. Key areas where AI techniques can improve the delivery of care include: (i) diagnoses, (ii) managing patient journeys, and (iii) improving patient engagement. Streamlining these three areas can ease administrative burdens on healthcare systems, optimize physicians’ time, improve patient outcomes, and lower costs. However, a significant challenge for MedTechs is the scarcity of essential capabilities to develop digital strategies. A 2020 research report by Deloitte Insights suggested that there are significant shortages of “AI developers and engineers, AI researchers, and data scientists”. Corporate leaders might consider bolstering their chances of attracting digital and AI talent by: (i) leveraging their company’s unique value and purpose, (ii) prioritizing and offering best-in-class training over recruiting, (ii) prioritizing diversity, and (iv) engaging with universities.
 
Transformative MedTech deals
 
The significant shift in MedTech strategies towards patients is demonstrated by two recent transformative deals: Teledoc’s 2020 acquisition of Livongo and Siemens Healthineers AG’s 2021 acquisition of Varian Medical Systems Inc. Both combinations emphasise the significance of digitalization and demonstrate the strategic shift towards patients. 
 
The US telehealth giant Teledoc’s acquisition of Livongo for US$18.5bn was the largest digital healthcare deal in history, which valued the combined company at US$38bn. Livongo, founded in 2014, provides digital therapeutic solutions to improve patient health outcomes for a range of chronic conditions including diabetes, and hypertension. The other transformative MedTech digitalization deal was the German health imaging giant Siemens Healthineers AG’s acquisition of cancer device and software specialist Varian in April 2021 for US$16.4bn. Siemens Healthineers is the leading supplier of medical imaging solutions used to support the planning and delivery of radiotherapy. Varian was the leading supplier of radiotherapy solutions. Both deals were substantially larger than Amazon’s US$0.75bn 2019 acquisition of PillPack, and Google’s US$2.1bn 2021 acquisition of Fitbit, and they signal a new and permanent path for MedTech companies towards a digital-first future.
 
Takeaways

To remain relevant MedTechs will need to continue their symbiotic relationships with surgeons albeit in a modified form, while becoming significantly more patient centric and digitally savvy. However, a bigger challenge Western MedTechs will have to face in the next five years is whether they can develop digital therapeutic solutions for patients fast enough to compete with the looming threat from China’s large and rapidly growing capacity to develop and market medical robotics for surgeons and innovative digital therapeutics for patients. This will be the subject of a forthcoming Commentary.
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