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A prescription for an AI inspired MedTech industry
Thinking beyond physical products and the growing significance of AI in MedTech markets
A wind of change is blowing through MedTech markets, which has prompted some key opinion leaders to think beyond physical products and begin to use artificial intelligence (AI) techniques to develop value added services that bolt-on to their existing physical offerings to improve clinical care and economic efficiencies while providing access to new revenue streams. Bryan Hanson, Zimmer-Biomet’s CEO, recently suggested that >70% of his company’s R&D spend is now being invested in data informatics and robotics. Not far behind is Stryker, another global orthopaedic corporation, which has implemented AI strategies to improve care and differentiate its offerings. Both are thinking beyond their physical products to create a suite of services derived from AI enhanced data collected from their existing devices. Such actions provide a template that can be copied by other enterprises. How long will it take for AI solutions to represent a significant percentage of MedTechs’ revenues? In this Commentary
This Commentary: (i) describes the growing significance of AI, (ii) explains the difference between data mining, AI, and machine learning, (iii) illustrates AI technologies that have become an accepted part of our everyday lives, (iv) highlights technical drivers of AI solutions, (v) describes obstacles to the development of AI systems, (vi) indicates how such obstacles may be reduced, (vii) describes Zimmer’s and Stryker’s AI driven data initiatives, (viii) suggests that the Zimmer-Stryker AI template has broad potential, (ix) suggests that AI systems can breathe life into 'dead data', (x) provides an example of a company at the intersection of medical information and AI techniques, (xi) describes the origins of the phrase, ‘wind of change’, and defines the ‘winds’ driving change in current MedTech markets, (xii) reports that ~80% of B2B sales in the economy generally are digitally driven, (xiii) provides some reasons for MedTechs’ slow adoption of AI systems, (xiv) floats the idea that the future for producers is to partner with tech savvy start-ups and (xv) describes how US AI supremacy is being challenged. AI: vast and fast growing
It is challenging for baby boomers and older millennials, who populate MedTechs’ C suites, to fully grasp the potential of AI. This is largely because their corporate careers were underway before the digital age started, and for three decades they have personally prospered from manufacturing physical devices without the help of AI. A person who understands the potential of AI is Sundar Pichai, the CEO of Alphabet, one of the world’s largest tech companies. In a recent BBC interview Pichai suggested, "AI is the most profound technology that humanity will ever develop and work on . . . If you think about fire or electricity or the Internet, it's like that, but even more profound". This suggests that Hanson is right to redirect Zimmer’s R&D spend towards AI-driven solutions. A February 2021 report from the International Data Corporation (IDC), a market intelligence firm, suggests that the current global AI market is growing at a compound annual growth rate (CAGR) of ~17% and is projected to reach ~US$554bn by 2024. Data mining, AI, machine learning and neural networks
Among MedTechs’ C suites there is some confusion about data strategies and AI solutions. Many enterprises use data mining techniques on existing large datasets to search for patterns and trends that cannot be found using simple analysis. They employ the outcomes to increase revenues, cut costs, improve customer relationships, reduce risks and more. Although data mining is commonly used when working on AI projects, in of itself, it is not AI. So, let us briefly clarify. AI is the science and engineering of developing intelligent computer programs to enable machines to provide requested information, supply analysis, or trigger events based on findings. AI creates machines that think, learn, and solve problems better and faster than humans. This is different to traditional computing, where coders provide computers with exact inputs, outputs, and logic. By contrast, AI systems can be “schooled” to carry out specific tasks without being programmed to do so. This is referred to as machine learning, which usually requires large amounts of data to train algorithms [mathematical rules to solve recurrent problems]. A critical element of machine learning’s success is neural networks, which is an AI technique modelled on the human brain that is capable of learning and improving over time. Neural networks are comprised of interconnected algorithms that share data and are trained by triaging those data: a process referred to as ‘back propagation’. In healthcare, machine learning outputs range from the ability to recognise images faster and more accurately than health professionals to making in vivo diagnoses. AI systems have become an accepted part of our everyday lives without us realising it
Most people are aware of significant AI breakthroughs such as self-driving cars and IBM’s Watson computer winning the US quiz show Jeopardy by beating two of the best players the show had produced. Lesser known, is in 2012, AlexNet, a neural network learning system, won a large-scale visual recognition contest, which previously was thought too complex for any machine. In 2016, Google’s AlphaGo, a machine learning algorithm, defeated Lee Sedol, who was widely considered the world’s greatest ever player of the ancient Chinese game Go. Most observers believed it would be >10 years before an AI programme would defeat a seasoned Go champion. Although Go’s rules are simple, the game is deceptively complex, significantly more so than chess. It has a staggering 10170 possible moves, which is more than the number of atoms known in the universe. Significantly, machine learning algorithms embedded in AlphaGo, mastered the game without any prior knowledge and without any human input. More recently Google launched AlphaGo Zero, an AI system, which can play random games against itself and learn from it. During the decade of these breakthroughs, AI systems became an accepted part of our everyday lives without us realising it. Examples include, Google searches, GPS navigation, facial recognition, recommendations for products and services, bank loans we receive, insurance premiums we are charged, and chatbots, which organizations use to provide us with information. Technical drivers of AI systems
In addition to commercial drivers, AI techniques are driven by easy availability of data, an explosion in computing power and the increased use of clusters of graphic processing units (GPUs) to train machine-learning systems. These clusters, which are widely available as cloud services over the Internet, facilitate the training of more powerful machine-learning models. An example is Google's Tensor Processing Unit (TPU), which has the capability to carry out more than one hundred thousand trillion floating-point operations per second (100 petaflops). This has the potential to accelerate the rate at which machine-learning models can be trained. Further, the cloud has made data storage and recovery easier, which has motivated government agencies and healthcare institutions to build vast unstructured data sets that they make accessible to researchers throughout the world to stimulate innovation. Obstacles to the development of AI systems
So far, we have emphasised the benefits of AI, but there are concerns that machine intelligence will accelerate at an incomprehensible rate, surpass human intelligence, and transform our reality. This is referred to as “singularity”, which has generated concerns from key opinion leaders. Nearly a decade ago, Stephen Hawking, a pre-eminent British scientist, warned in a BBC interview, that singularity “could spell the end of the human race”. More recently, Hawking’s view has been echoed by Elon Musk, founder, and CEO of Tesla and SpaceX, who suggests that AI is, “more dangerous than nuclear warheads and poses a fundamental risk to the existence of human civilization". Musk has called for stronger regulatory oversight of AI, and more responsible research into mitigating its downsides. In 2015, he set up OpenAI, a non-profit research organization, with a mission to promote and develop AI systems that benefit society. |
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| Since we first published this Commentary just over a year ago it’s received over 10,000 views. We’re republishing it as colleagues have suggested that the digitization of MedTech is more relevant today because of the impact CoVID-19 has had on the industry. |
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- Prime editing devised by researchers at the Broad Institute led by David Liu is a significant advance of the original CRISPR gene editing tool discovered in 2012
- CRISPR can cut and edit your DNA to correct defects inside your body’s cells to prevent and heal a range of incurable diseases and has revolutionized biomedicine
- The original CRISPR is fraught with inaccuracies referred to as off target effects
- Prime editing substantially reduces CRISPR’s off target effects and has the potential to correct up to 89% of known disease-causing genetic variations
- CRISPR also has the capacity to edit genes in an embryo in such a way that the change is heritable
- In 2018 Chinese researcher He Jiankui “created” the world’s first CRISPR babies
- This triggered international criticism from scientists and bioethicists
- A principal concern is that CRISPR is easy-to-use, cheap, regularly used in thousands of laboratories throughout the world and there is no internationally agreed and enforceable regulatory framework for its use
For better or worse we all now live in CRISPR’s world
In 2012 the world of biomedicine changed when a revolutionary gene editing technology known as CRISPR-Cas9 (an acronym for Clustered Regularly Interspaced Short Palindromic Repeats) was discovered. The technology harnesses your body’s naturally occurring immune system that bacteria use to fight-off viruses and has the potential to forever change the fundamental nature of humanity. Since its discovery CRISPR has been developing at lightning speed primarily because it is simple and affordable and today is used in thousands of laboratories throughout the world.
In this Commentary
In this Commentary we describe prime editing, which is the latest advance of the CRISPR's tool box, devised bya team of researchers, led by Andrew Anzalone, a Jane Coffin Childs postdoctoral fellow from the Broad Institute of MIT and Harvard and published in the October 2019 edition of Nature. Prime editing is significant because it provides a means to eliminate the unintentional consequences of CRISPR and therefore bring the technique closer for use in clinics. But this is still a long way off.
We also review a case where an ambitious scientist “created” the first CRISPR babies. This immediately triggered international criticism and a call for tighter regulatory control of the technology. Scientists and bioethicists are concerned that CRISPR can easily be used to create heritable DNA changes, which ultimately could lead to ‘designer babies’.
These two accounts of CRISPR might seem “opposites” and not sit well together in a single Commentary. Notwithstanding, what prompted putting them together was John Travis, the News Managing Editor of the well-known scientific journal Science, who soon after CRISPR’s discovery in 2012 said, “For better or worse we all now live in CRISPR’s world”.
CRISPR and your DNA
CRISPR is different to traditional gene therapy, which uses viruses to insert new genes into cells to try and treat diseases and has caused some safety challenges. CRISPR, which avoids the use of viruses, was conceived in 2007 when a yogurt company identified an unexpected defence mechanism that its bacteria used to fight off viruses. Subsequent research made a surprising observation that bacteria could remember viruses. CRISPR has been likened to a pair of microscopic scissors that can cut and edit your DNA to correct defects inside your body’s cells to prevent and heal a range of intractable diseases. The standard picture of DNA is a double helix, which looks similar to a ladder that has been twisted. The steps in this twisted ladder are DNA base pairs. The fundamental building blocks of DNA are the four bases adenine (A), cytosine (C), guanine (G) and thymine (T). They are commonly known by their respective letters, A, C, G and T. Three billion of these letters form the complete manual for building and maintaining your body, but tiny errors can cause disease. For example, a mutation that turned one specific A into a T results in the most common form of sickle cell disease.
We also review a case where an ambitious scientist “created” the first CRISPR babies. This immediately triggered international criticism and a call for tighter regulatory control of the technology. Scientists and bioethicists are concerned that CRISPR can easily be used to create heritable DNA changes, which ultimately could lead to ‘designer babies’.
These two accounts of CRISPR might seem “opposites” and not sit well together in a single Commentary. Notwithstanding, what prompted putting them together was John Travis, the News Managing Editor of the well-known scientific journal Science, who soon after CRISPR’s discovery in 2012 said, “For better or worse we all now live in CRISPR’s world”.
CRISPR and your DNA
CRISPR is different to traditional gene therapy, which uses viruses to insert new genes into cells to try and treat diseases and has caused some safety challenges. CRISPR, which avoids the use of viruses, was conceived in 2007 when a yogurt company identified an unexpected defence mechanism that its bacteria used to fight off viruses. Subsequent research made a surprising observation that bacteria could remember viruses. CRISPR has been likened to a pair of microscopic scissors that can cut and edit your DNA to correct defects inside your body’s cells to prevent and heal a range of intractable diseases. The standard picture of DNA is a double helix, which looks similar to a ladder that has been twisted. The steps in this twisted ladder are DNA base pairs. The fundamental building blocks of DNA are the four bases adenine (A), cytosine (C), guanine (G) and thymine (T). They are commonly known by their respective letters, A, C, G and T. Three billion of these letters form the complete manual for building and maintaining your body, but tiny errors can cause disease. For example, a mutation that turned one specific A into a T results in the most common form of sickle cell disease.
The original CRISPR
The original CRISPR tool, which is the first and most popular gene editing system, uses a guide RNA (principally a messenger carrying instructions from your DNA for controlling the synthesis of proteins) to locate a mutated gene plus an enzyme, like Cas9, to cut the double-stranded gene helix and create space for functioning genes to be inserted. However, a concern about CRISPR is that the editing could go awry and cause unintended changes in DNA that could trigger health problems. Findings of a study published in the July 2018 edition of the journal Nature Biotechnology found that such inaccuracies, referred to as off-target effects, were substantially higher than originally reported and some were thought to silence genes that should be active and activate genes that should be silent. These off-target effects, such as random insertions, deletions, translocations, or other base-to-base conversions, pose significant challenges for developing policy associated with the technology.
Subsequently however, the paper was retracted, and an error correction was posted on a scientific website. Contrary to their original findings, the authors of the Nature Biotechnology paper restated that the CRISPR-Cas9 gene editing approach, "can precisely edit the genome at the organismal level and may not introduce numerous, unintended, off-target mutations".
Notwithstanding, researchers remained concerned about CRISPR’s off target effects and several devised a technique, referred to as base editing, to reduce these. Base editing is described in three research papers published in 2017: one in the November edition of the journal ‘Protein and Cell’, another in the October edition of ‘Science’ the and a third by researchers from the Broad Institute, in the October edition of the journal ‘Nature’. Base editing takes the original CRISPR-Cas9 and fuses it to proteins that can make four precise DNA changes: it can change the letters C-to-T, T-to-C, A-to-G and G-to-A. The technique genetically transforms base pairs at a target position in the genome of living cells with more than 50% efficiency and virtually no detectable off-target effects. Despite its success, there remained other types of point mutations that scientists wanted to target for diseases.
Subsequently however, the paper was retracted, and an error correction was posted on a scientific website. Contrary to their original findings, the authors of the Nature Biotechnology paper restated that the CRISPR-Cas9 gene editing approach, "can precisely edit the genome at the organismal level and may not introduce numerous, unintended, off-target mutations".
Base editing
Notwithstanding, researchers remained concerned about CRISPR’s off target effects and several devised a technique, referred to as base editing, to reduce these. Base editing is described in three research papers published in 2017: one in the November edition of the journal ‘Protein and Cell’, another in the October edition of ‘Science’ the and a third by researchers from the Broad Institute, in the October edition of the journal ‘Nature’. Base editing takes the original CRISPR-Cas9 and fuses it to proteins that can make four precise DNA changes: it can change the letters C-to-T, T-to-C, A-to-G and G-to-A. The technique genetically transforms base pairs at a target position in the genome of living cells with more than 50% efficiency and virtually no detectable off-target effects. Despite its success, there remained other types of point mutations that scientists wanted to target for diseases.
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- Over the past decade MedTech valuations have outperformed the market without changing its business model
- The healthcare ecosystem is rapidly changing and MedTech is facing significant headwinds which require change
- MedTech’s future growth and value will be derived from data and smart analytics rather than manufacturing
- MedTech leaders will be required to leverage both physical and digital assets
Increasing MedTech’s future growth and value
Over the past decade, the medical device (MedTech) industry has enjoyed relatively high valuations and outperformed broader market indices without changing its manufacturing business model. Some MedTech leaders suggest that because the industry’s product offerings are essential, demand for them is increasing as populations grow and age, so unlike other industries, MedTech is immune to market swings and its asset value will continue to increase. As a consequence of this mindset, MedTech has been reluctant to change and slow to develop digitization strategies. Notwithstanding, digitization is an in-coming tide and positioned to impose a step-change on the industry. Future MedTech leaders will need to derive increased growth and value from digitization and emerging markets while improving the efficiency of their legacy manufacturing business and meeting quarterly earnings’ targets.
According to a 2018 report by the consulting firm Ernst & Young,“Stagnant R&D investment, low revenue growth and slow adoption of digital and data technologies suggest that entrenched MedTech companies are overly focused on short-term growth, even as the threat of large tech conglomerates entering the space grows larger, which, in addition to the changing global healthcare ecosystem, threatens future revenue growth".
According to a 2018 report by the consulting firm Ernst & Young,“Stagnant R&D investment, low revenue growth and slow adoption of digital and data technologies suggest that entrenched MedTech companies are overly focused on short-term growth, even as the threat of large tech conglomerates entering the space grows larger, which, in addition to the changing global healthcare ecosystem, threatens future revenue growth".
In this Commentary
This Commentary suggests that to create future growth and value, MedTech will have to (i) leverage data generated by medical devices, patients, payers and healthcare providers to develop clinical insights and trend analysis, which are expected to significantly improve patient outcomes and reduce costs, and (ii) substantially increase its share of the large and rapidly growing emerging markets. We suggest that there is a significant relationship between MedTech’s digital capacity and competences and its ability to increase its share of emerging Asian markets. But first we briefly describe the MedTech industry and its traditional markets and draw attention to some concerns, which include the relative low rates of top-line growth, stagnant R&D and share buybacks, M&A slowdown, giant tech companies entering the healthcare market, and challenges to recruit and retain millennials with natural digital skills and abilities.
The medical device industry
Concern # 1: Reduced growth rates
Population growth and aging
Concern # 2: Stagnate R&D spend and share buybacks
The medical device industry
The MedTech industry designs, manufactures and markets more than 0.5m different products to diagnose, monitor and treat patients. These include wearable devices such as insulin pumps and blood glucose monitors, implanted devices such as pacemakers and metal plates, and stationary devices that range from instruments to sophisticated scanning machines. Medical devices can be instrumental in helping healthcare providers achieve enhanced patient outcomes, reduced healthcare costs, improved efficiency and new ways of engaging and empowering patients. The principal business model employed by the industry is to manufacture innovative products relatively cheaply and sell them expensively in wealthy developed regions of the world; predominantly North America, Europe and Japan; which although representing only 13% of the world’s population account for 86% of the global MedTech market share. This premium pricing model is predicated upon doctors’ and health providers’ belief that MedTech products are of superior quality and safety. Notwithstanding, as eye-watering healthcare costs escalate, providers and regulators demand better evidence of clinical and economic value to justify the pricing and use of MedTech products. Over the next five years, the global MedTech industry is expected to grow at a compound annual growth rate of between 4% and 5.6% and reach global sales of some US$595bn by 2024.
Concern # 1: Reduced growth rates
Since the worse post-war recession ended in 2009, MedTech asset valuations have outperformed the market. Notwithstanding, of increasing concern is the slowdown of the industry’s revenue growth rates to single digits. The industry's aggregate revenue grew to US$379bn in 2017, an annual average industry growth rate of 4%, which now appears to be the new normal, and is significantly lower than the average annual growth rate of 15%, which the industry enjoyed between 2000-2007. The reduction in top-line growth rates is largely attributed to the world’s growing and aging population and the consequent growth in the incidence rates of chronic conditions, which increases the burden on overstretched healthcare budgets and intensifies pressure on MedTech’s to reduce their prices.
Population growth and aging
The aging population is driven by improvements in life expectancy. People are living longer and reaching older ages as fertility decreases and quality healthcare increases. People are having fewer children later in life. Some 8.5% of the global population (617m) have ages 65 and over. This is projected to rise to nearly 17% by 2050 (1.6bn). The number of Americans aged 65 and older is projected to more than double from 46m today to over 98m by 2060 – from 15% to 24% of the total US population. Around 18% of the UK population were aged 65 years or over in 2017, compared with 16% in 2007. This is projected to grow to 21% by 2027.
Concern # 2: Stagnate R&D spend and share buybacks
In addition to relatively low revenue growth rates, MedTech R&D spend has stagnated over the past decade despite the need for companies to develop new and innovative product offerings, which drive top-line sales. Over the same period, MedTech returned more cash to shareholders in the form of share buybacks and dividends (US$16.4bn) than it spent on R&D.
To the extent that share buybacks extract, rather than create value why are they popular? One suggestion is that because share incentive plans represent a significant portion of executive compensation, share buybacks make it easier for executives to meet earning-per-share (eps) targets by reducing the number of shares, in the 1970s, share buybacks were effectively banned in the US amid concerns that executives might use them to manipulate share prices. However, in 1982 the US Securities and Exchange Commission (SEC) lightened its definition of stock manipulation, and share buybacks became popular again.
To the extent that share buybacks extract, rather than create value why are they popular? One suggestion is that because share incentive plans represent a significant portion of executive compensation, share buybacks make it easier for executives to meet earning-per-share (eps) targets by reducing the number of shares, in the 1970s, share buybacks were effectively banned in the US amid concerns that executives might use them to manipulate share prices. However, in 1982 the US Securities and Exchange Commission (SEC) lightened its definition of stock manipulation, and share buybacks became popular again.
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- People are living longer, the prevalence of age-related degenerative disc disease is increasing and sufferers are more and more turning to spinal implant surgery as a solution
- As this significantly raises the burden on over-stretched healthcare systems, so is spine surgery increasingly becoming a key target for cost reduction within healthcare systems
- This intensifies the pressure on manufacturers to innovate and make spinal implants more cost effective
Can 3D printing and the use of new alloys reduce the high costs of producing and marketing spinal implants?
On January 8th 2019 surgeons at Joseph Spine, a specialist surgery centre based in Tampa Bay Florida, were the first in the US to implant a 3D printed interbody fusion device, which was produced by Osseus Fusion Systems. The company uses its proprietary 3D printing technology, also known as additive manufacturing, to build spinal implants from titanium material that is optimized for bone fusion and biological fixation. In August 2018, a suite of Osseus’s devices received clearance from the US Food and Drug Administration (FDA) for a range of heights and lordotic (inward spinal curvature) angles, which make them adaptable for a variety of patient anatomies. The interbody fusion devices work by being packed with biomaterials and bone grafts and inserted in between two vertebrae, where they fuse with the spine and work to prevent back pain.
In this Commentary
This Commentary explores whether 3D printing and the use of new alloys could be an appropriate strategy to help spine companies reduce their production and sales costs and enhance their market positions. Our suggestions here complement a strategy, described in a previous Commentary, for MedTech companies to develop and implement digital strategies to enhance their go-to-market activities, strengthen the value propositions of products and services and streamline internal processes. The reasons spine companies might consider both strategies are because spinal implant markets, which are segmented by type of surgery, product and geography, are experiencing significant competitive, regulatory, pricing and technological challenges as well as mounting consumer pressure for improved outcomes; and the business model, which served as an accelerator of their financial success over the past decade is unlikely to be effective over the next decade.
3D printing
3D printing is a process, which creates a three-dimensional (3D) object by building successive layers of raw material. Each new layer is attached to the previous one until the object is complete. In the healthcare industry, 3D printing is used in a wide range of applications, such as producing dental crowns and bridges; developing prototypes; and manufacturing surgical guides and hearing aid devices. Increasingly, 3D printing is being used for the production of spinal implants.
Spine surgery increasing significantly
An estimated US$90bn is spent each year in the US on the diagnosis and management of low back pain (LBP). LBP, caused by age related degenerative disc disease, is one of the most common and widespread public health challenges facing the industrialized world. It is estimated that the condition affects over 80% of the global population and inflicts a heavy and escalating burden on healthcare systems. Also, LBP affects economies more generally in terms of lost production due to absenteeism, early retirement and the psychosocial impact caused by the withdrawal of otherwise active people from their daily activities. According to the American Association of Neurological Surgeons, more than 65m Americans suffer from LBP annually and the Chicago Institute of Neurosurgery and Neuroresearch suggests that by the age of fifty, 85% of the US population is likely to show evidence of disc degeneration. It is estimated that 10% of all cases of LBP will develop chronic back pain, which is one of the main reasons for people to seek surgical solutions and this significantly raises the burden on over-stretched healthcare systems.
Findings of a study published in the March 2019 edition of Spine, entitled, “Trends in Lumbar Fusion Procedure Rates and Associated Hospital Costs for Degenerative Spinal Diseases in the United States 2004 to 2015”, report that the rate of elective lumbar fusion surgeries in the US has increased substantially over the past decade. Such trends are indicative of most advanced industrial societies, which are changing and ageing, primarily driven by improvements in life expectancy and by a decrease in fertility. This results in people living longer, reaching older ages and having fewer children later in life. Over the next decade, these market drivers are expected to make spine surgery a key target for cost reduction within healthcare systems and this, in turn, is likely to increase pressure on manufacturers of spinal implants to make spine surgery more cost effective.
Findings of a study published in the March 2019 edition of Spine, entitled, “Trends in Lumbar Fusion Procedure Rates and Associated Hospital Costs for Degenerative Spinal Diseases in the United States 2004 to 2015”, report that the rate of elective lumbar fusion surgeries in the US has increased substantially over the past decade. Such trends are indicative of most advanced industrial societies, which are changing and ageing, primarily driven by improvements in life expectancy and by a decrease in fertility. This results in people living longer, reaching older ages and having fewer children later in life. Over the next decade, these market drivers are expected to make spine surgery a key target for cost reduction within healthcare systems and this, in turn, is likely to increase pressure on manufacturers of spinal implants to make spine surgery more cost effective.
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- Two Boston Consulting Group studies say MedTech innovation productivity is in decline
- A history of strong growth and healthy margins render MedTechs slow to change their outdated business model
- The MedTech sector is rapidly shifting from production to solutions
- The dynamics of MedTechs' customer supply chain is changing significantly and MedTech manufacturers are no longer in control
- Consolidation among buyers - hospitals and group purchasing organisations (GPO) - adds downward pressure on prices
- Independent distributors have assumed marketing, customer support and education roles
- GPOs have raised their fees and are struggling to change their model based on aggregate volume
- Digitally savvy new entrants are reinventing how healthcare providers and suppliers work together
- Amazon’s B2B Health Services is positioned to disrupt MedTechs, GPOs and distributors
- MedTech manufacturers need to enhance their digitization strategies to remain relevant
MedTech must digitize to remain relevant
MedTech companies need to accelerate their digital strategies and integrate digital solutions into their principal business plans if they are to maintain and enhance their position in an increasingly solution orientated healthcare ecosystem. With growing focus on healthcare value and outcomes and continued cost pressures, MedTechs need to get the most from their current portfolios to drive profitability. An area where significant improvements might be made in the short term is in MedTechs' customer facing supply chains. To achieve this, manufacturing companies need to make digitization and advanced analytics a central plank of their strategies.
In this Commentary
This Commentary describes the necessity for MedTechs to enhance their digitization strategies, which are increasingly relevant, as MedTech companies shift from production to solution orientated entities. In a previous Commentary we argued that MedTechs history of strong growth and healthy margins make them slow to change and implement digital strategies. Here we suggest that the business model, which served to accelerate MedTechs' financial success over the past decade is becoming less effective and device manufacturers need not only to generate value from the sale of their product offerings, but also from data their devices produce so they can create high quality affordable healthcare solutions. This we argue will require MedTechs developing innovative strategies associated with significantly increasing their use of digital technology to enhance go-to-market activities, strengthen value propositions of products and services and streamline internal processes.
MedTechs operate with an outdated commercial model
Our discussion of digitization draws on two international benchmarking studies undertaken by the Boston Consulting Group (BCG). The first, published in July 2013 and entitled, “Fixing the MedTech Commercial Model: Still Deploying ‘Milkmen’ in a Megastore World” suggests that the high gross margins that MedTech companies enjoy, particularly in the US, hide unsustainable high costs and underdeveloped commercial skills. According to BCG the average MedTech company’s selling, general and administrative (SG&A) expenses - measured as a percentage of the cost of goods sold - is 3.5 times higher than the average comparable technology company. The study concludes that MedTechs' outdated business model, dubbed the “milkman”, will have to change for companies to survive.
BCG’s follow-up 2017 study
In 2017 BCG published a follow-up study entitled, “Moving Beyond the ‘Milkman’ Model in MedTech”, which surveyed some 6,000 employees and benchmarked financial and organizational data from 100 MedTech companies worldwide, including nine of the 10 largest companies in the sector. The study suggested that although there continued to be downward pressure on device prices, changes in buying processes and shrinking gross margins, few MedTech companies “have taken the bold moves required to create a leaner commercial model”.
According to the BCG’s 2017 study, “Overall, innovation productivity [in the MedTech sector] is in decline. In some product categories, low-cost competitors - including those from emerging markets - have grown rapidly and taken market share from established competitors. At the same time, purchasers are becoming more insistent on real-world evidence that premium medical devices create value by improving patient outcomes and reducing the total costs of care”. The growth and spread of value-based healthcare has shifted the basis of competition beyond products, “toward more comprehensive value propositions and solutions that address the entire patient pathway”. In this environment, MedTechs have no choice but to use data to deliver improved outcomes and a better customer experience for patients, healthcare providers and payers.
According to the BCG’s 2017 study, “Overall, innovation productivity [in the MedTech sector] is in decline. In some product categories, low-cost competitors - including those from emerging markets - have grown rapidly and taken market share from established competitors. At the same time, purchasers are becoming more insistent on real-world evidence that premium medical devices create value by improving patient outcomes and reducing the total costs of care”. The growth and spread of value-based healthcare has shifted the basis of competition beyond products, “toward more comprehensive value propositions and solutions that address the entire patient pathway”. In this environment, MedTechs have no choice but to use data to deliver improved outcomes and a better customer experience for patients, healthcare providers and payers.
MedTech distributors increasing their market power and influence
Although supply chain costs tend to be MedTechs' second-highest expense after labour, companies have been reluctant to employ digital strategies to reduce expenses and increase efficiencies. As a consequence, their customer supply chains tend to be labour intensive relationship driven with little effective sharing of data between different territories and sales teams. Customer relations are disaggregated with only modest attention paid to patients and payors and insufficient emphasis on systematically collecting, storing and analysing data to support value outcomes.
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