Tag

Tagged: big data

Sponsored
8 months, 2 weeks ago

Optimising MedTechs’ People Operations for AI and Market Changes

HealthPad
Directory:
Medical Technology
Tags:
AI
big data
commentary
MedTech
people operations
  • Traditional MedTechs should swiftly upgrade their human capital if they wish to keep pace with rapidly advancing technologies and changing markets
  • Priority lies in aligning in-house capabilities with technology-driven strategies and the progression of healthcare systems
  • Emerging technologies like AI-driven big data solutions and services are set to transform MedTech offerings
  • Enterprises need to adjust to decentralised care models within evolving healthcare ecosystems 
  • To flourish in the next decade, MedTechs must cultivate a culture of continuous enhancement to bolster their innovation capabilities
 
Optimising MedTechs’ People Operations for AI and Market Changes
 
In today's dynamic healthcare landscape characterised by rapid technological advancements and shifting market trends, traditional MedTechs find themselves at a turning point. Maintaining competitiveness demands a proactive stance to manage change through strategic investment in human capital development. Prioritising the rejuvenation of a company’s workforce is important, as an organisation's future sustainability and success hinge on its ability to adapt and innovate. This need for transformation is driven by factors influencing healthcare, including the rise of disruptive technologies and the continuous evolution of market conditions.
 
In this Commentary

This Commentary stresses the need for traditional MedTech firms to modernise their people operations amid the growing influence of AI, automation, and market dynamics. It stresses aligning human capital capabilities with organisational strategies to effectively leverage technological advancements, market shifts, and evolving healthcare systems. By showcasing the transformative potential of AI-powered big data-driven solutions and services, it draws attention to the importance of empowering people to manage challenges and drive innovation that provide access to new revenue streams. Furthermore, it highlights the shift towards decentralised care, prioritising prevention, and patient-centricity, prompting enterprises to realign their internal capabilities accordingly. Addressing challenges posed by off-patent products, the Commentary advocates a proactive approach in equipping workforces with essential skills and a mindset conducive to excelling in an era of heightened automation and efficiency. Lastly, it underscores refocusing company operations on value creation while fostering a culture of continuous improvement and innovation, guiding MedTechs to maintain their competitive edge in the evolving healthcare ecosystem.
 
Technological Advancements and Market Dynamics
 
The healthcare industry is undergoing a transformation fuelled by rapid technological advancements and market changes. Emerging automation technologies are disrupting traditional workflows and processes, promising heightened efficiency, accuracy, and improved patient outcomes. Concurrently, there is a notable surge in the adoption of digital health solutions, preventive measures, diagnostics, and value-based care. Digital health platforms offer opportunities for remote patient monitoring, personalised interventions, and data-driven decision-making, while preventive healthcare, driven by wearable devices and predictive analytics, aims to anticipate and mitigate illnesses before they escalate, thus promoting wellbeing and alleviating strain on healthcare systems. Moreover, diagnostics are evolving with greater sophistication, incorporating technologies like genomics and molecular imaging to enable earlier detection and targeted treatment strategies. In this changing technological terrain, traditional MedTech companies must shift their people towards a tech-savvy, forward-thinking mindset. Employees must be adept at leveraging disruptive technologies to develop and deliver innovative solutions and services that align with the evolving needs of patients, thereby providing access to new revenue streams. Achieving this necessitates a concerted effort to upskill existing talent, recruit individuals with expertise in AI, data analytics, and digital health, and cultivate a culture of continuous learning and adaptation. While the allure of seeking external expertise from consulting firms may be strong, the most sustainable approach is to invest in enhancing in-house capabilities, empowering the workforce to adeptly navigate transitions and foster innovation and sustainable growth from within.
 
Changing Healthcare Systems

Healthcare worldwide is shifting towards decentralised care, preventive measures, and patient-centricity and is characterised by innovative care delivery models, heightened emphasis on patient outcomes, value, and stringent regulatory standards. Decentralised care models, such as telemedicine, home healthcare, and community-health, are gaining traction. Such models prioritise accessibility, convenience, and cost-effectiveness, necessitating companies to develop solutions and services tailored to support remote monitoring, virtual consultations, and effective data exchange between healthcare providers and patients.
 
The growing recognition of the importance of preventive healthcare in reducing disease burdens and rising healthcare costs is likely to oblige MedTechs to adapt by shifting some of their focus towards developing technologies that enable early detection, personalised interventions, and health promotion initiatives. This requires people equipped with the expertise to manage complex healthcare ecosystems, collaborate with diverse stakeholders, and leverage data analytics to drive actionable insights. Further, patient-centricity has emerged as a guiding principle shaping healthcare delivery and product development strategies. Traditional enterprises, mostly focused on health professionals in hospitals, must enhance their understanding of patient needs, preferences, and experiences to design offerings that empower individuals to actively participate in their care journeys. This demands a workforce with an understanding of individual-centred design principles, empathy, and the ability to co-create solutions with patients and caregivers. MedTechs must increase investments to bolster cross-functional collaboration, nurture entrepreneurial mindsets, and deepen comprehension of regulatory compliance, quality production, value-based care, and market dynamics. These efforts are crucial for businesses to position themselves as catalysts of innovation and value creation within evolving healthcare ecosystems.
 
Impact of Off-Patent Products

As we approach 2030, numerous corporations are on the verge of encountering patent expirations that currently safeguard revenues of a substantial portion of their product offerings, including pacemakers, implantable defibrillators, insulin pumps, and certain stents. This impending wave of expirations suggests an imminent surge in competition from generic and biosimilar alternatives, posing a challenge to the established dominance of traditional firms. These enterprises, often hesitant to invest in innovative R&D initiatives, now face a critical decision point where they must evolve or risk losing their competitive edge. To effectively manage this impending challenge, companies need to revamp their people operations and talent management strategies.
 
In the race to swiftly bring new products to market, speed is critical. Traditional firms that have been slow to adapt must streamline their processes, remove bureaucratic bottlenecks, and cultivate a culture of rapid prototyping and iteration. This necessitates a workforce characterised by adaptability, resilience, and a commitment to excellence. Individuals must be empowered to foster innovation, embrace ambiguity, and view failure as an aspect of the innovation journey. Essentially, the impact of off-patent products suggests a new era of heightened competition and significant challenges for some traditional businesses. To excel in this environment, they should consider restructuring their people operations to foster innovation, differentiation, and agility. Only through such a culture can MedTechs hope to maintain their leading position amidst the evolving healthcare landscape.
 
Enhanced Efficiency through Automation

Projections from the Organisation for Economic Co-operation and Development (OECD) paint a concerning picture of the transformative impact of technology on the global workforce, with the healthcare sector positioned at the forefront of this anticipated evolution. As technological advancements become more prevalent, traditional roles within healthcare are likely to undergo transformations. Repetitive tasks, which have historically defined many healthcare professions, are progressively being assigned to automated systems. This shift liberates professionals to focus on tasks that necessitate human expertise and empathy.
 
For conventional firms, embracing this shift is not just a suggestion but a necessity for survival and prosperity. They must proactively equip their people with the necessary skills and proficiencies. This goes beyond technical competence and requires a shift in mindset and approach. Human capital strategies should foster a culture of collaboration with intelligent systems, leveraging individual talents to fuel innovation and boost productivity. Traditional enterprises must enhance their operations and services through advanced technologies. By integrating smart solutions throughout manufacturing, supply chain management, and product development workflows, MedTechs can unlock significant degrees of efficiency, scalability, and adaptability. Moreover, this integration can enhance the performance and functionalities of services, delivering added value to healthcare providers and patients. However, the rise of intelligent systems presents both challenges and opportunities for corporations. Embracing these advancements and investing in the necessary skills and technologies allow organisations to broaden their horizons and generate additional value, which is essential for sustained growth.
 
Cost Pressures and Value-Based Care

The significant rise in global healthcare spending, now exceeding an annual sum of US$8trn, has catalysed a transformative shift towards value-based care. This innovative approach prioritises the improvement of patient outcomes together with efforts to contain costs, marking a departure from the traditional reimbursement model, which is based on the provision of medical services. Within the framework of value-based care, conventional measures of success, like procedure volumes or sales figures, give way to more comprehensive evaluations that encompass patient wellbeing, enhancements in quality of life, and the effective reduction of expenses.
 
For traditional corporations, adapting to this new reality necessitates a reorientation of their people towards value creation. This goes beyond innovating products and requires a fresh approach that integrates considerations of efficacy, efficiency, and patient-centeredness into all operational facets. Employees must be empowered to transcend conventional boundaries and collaborate across functions to develop solutions that meet the needs of patients and healthcare providers. Additionally, MedTechs should invest in their human capital to enable all staff to illustrate the value proposition of the company’s products in tangible terms. This may involve employing data analytics to quantify the impact of products on patient outcomes, conducting real-world studies to validate effectiveness across various clinical settings, and adopting transparent pricing practices aligned with the value delivered. Moreover, fostering a culture of continuous improvement and innovation is important, where employees are encouraged to challenge conventions, experiment with new methods, and learn from both successes and setbacks. By embracing this mindset, companies are better positioned to drive sustained value creation, ensuring their relevance and competitiveness in an increasingly value-driven healthcare landscape.
 
Takeaways

With technological advancements and market shifts, the need for traditional MedTech companies to upgrade their capabilities cannot be emphasised enough. The convergence of automation technologies, evolving healthcare systems, patent expirations, and the transition to value-based care present both challenges and opportunities. Failure to adapt quickly to such shifts puts these companies at risk of being relegated to obscurity in an increasingly competitive market. The rapid pace of technological advancement, exemplified by emerging automation tools driven by AI and big data, requires people capable of harnessing these technologies to drive forward efficiencies and innovations. Furthermore, as healthcare systems evolve towards decentralised care, preventative measures, and patient-centric approaches, a deep understanding of new care paradigms and patient requirements becomes increasingly necessary. The expiration of patents emphasises the urgency for companies to cultivate innovation, differentiation, and adaptability. This entails empowering all employees to take ownership of change, think disruptively, and accelerate product development cycles. Moreover, the transition to value-based care necessitates a pivot towards outcome-driven, cost-effective, and patient-centric models. Traditional success metrics should be replaced with more nuanced measures of value, with people equipped with the necessary skills to demonstrate tangible value propositions. In essence, the transformation of traditional human capital policies is not just strategic, but a requirement for survival. By investing in people operations focused on innovation, collaboration, and value creation, enterprises can position themselves as leaders in the healthcare systems of tomorrow. Only by fully embracing this transformative journey can MedTechs succeed amidst the disruptive forces reshaping the industry.
view in full page
1 year, 2 months ago

Forging a path for digital excellence in the MedTech Industry

HealthPad
Directory:
Medical Technology
Tags:
AI
Artificial Intelligence
big data
commentary
cybersecurity
digitalization
Machine Learning
MedTech

 

  • The MedTech industry faces a pivotal moment as it confronts the challenge of adopting transformative technologies amidst a rapidly changing healthcare ecosystem
  • Despite progress in other sectors, MedTech has shown reluctance to fully integrate digitalization, potentially hindering its growth and competitiveness
  • There have been some notable exceptions such as Medtronic, Siemens Healthineers and Philips
  • Many large diversified MedTechs could unlock growth and value by capitalizing on the potential synergies between traditional medical devices and innovative digital solutions and services
  • The convergence of digital offerings with legacy medical devices provides opportunities for improved patient care, operational efficiency and R&D innovation
  • There is a pressing need for MedTechs to comprehensively embrace digitalization to avoid reduced competitiveness, limited growth, and diminished value enhancement
 
Forging a path for digital excellence in the MedTech Industry

In an era of rapid technological advancement, the medical technology (MedTech) industry is at a crossroads. While numerous other sectors have enthusiastically embraced digitalization and moved forward, the MedTech sector, barring a few notable exceptions, has been hesitant to embrace these transformative technologies. However, the time has come for large diversified MedTechs to recognize the opportunities that digitalization offers for growth and value creation. The convergence of traditional medical devices with digital solutions and services presents an opportunity for the industry to improve patient care, streamline operations, and drive innovation. Failing to fully integrate digitalization into their operations in a timely way may lead to unexpected consequences, including a shorter window of competitiveness and a struggle to enhance growth rates and augment value. The reluctance of many MedTechs to adapt now could translate into a significant handicap in the rapidly evolving landscape of healthcare technology.
 
In this Commentary

In this Commentary, we tackle four questions: (i) What is digitalization? (ii) Why is digitalization important for MedTechs? (iii) Which MedTechs have implemented successful digitalization strategies? and (iv) What defines an effective digitalization strategy? In addressing the fourth question, we present a strategy that encompasses 20 'essentials', which are not meant to follow a linear, sequential path. Instead, they are orchestrated by agile cross-functional teams, collaborating and pooling resources. Together, these teams oversee the execution of various elements of the strategy, while assuming responsibility for its overall effectiveness. This approach signals a departure from hierarchical departments and advocates a matrix-style organizational structure characterized by a web of interconnected reporting relationships. This structure goes beyond the confines of the conventional linear framework and incorporates specialized clusters, akin to "nests," each housing unique competencies, spanning multiple dimensions, and encompassing responsibility, authority, collaboration, and accountability.
 
1. What is digitalization?
 
Digitalization, also referred to as digital transformation, involves harnessing digital technologies to improve and refine business operations, processes, and services. By integrating digital tools across all facets of an organization, digitalization streamlines workflows, amplifies customer experiences, and achieves strategic goals. This includes automating tasks, utilizing data analytics for informed decision-making, and leveraging cloud computing for scalable and flexible operations. The Internet of Things (IoT) facilitates data exchange through connected devices, while artificial intelligence (AI), machine learning (ML) and large language models (LLM) empower computers to perform tasks requiring human-like intelligence. Virtual and augmented reality (VR/AR) enrich experiences, while cybersecurity measures are important to safeguard digital assets.
 
2. Why is digitalization important for MedTechs?
 
Digitalization is important for the MedTech industry since it acts as a driver for significant and positive change. By fully embracing this transformation, the industry develops the ability to use data and analytics to create innovative medical solutions and services. These are built on insights and predictions obtained from large amounts of information. Apart from these benefits, digitalization also affects the core of how clinical operations work. It makes workflows more efficient and frees-up healthcare professionals to focus more on taking care of patients. One significant development is the rise of collaborative telehealth platforms, which play a role in improving the quality and efficiency of healthcare delivery. Additionally, the power of technologies like AI, and ML becomes more evident. These advanced tools, driven by their ability to rapidly analyse vast data sets and make predictions, contribute to breakthroughs in care with the potential to improve patient outcomes while reducing costs.
You might also like:

MedTech must digitize to remain relevant



Is the digital transformation of MedTech companies a choice or a necessity?

 
The collaboration between smart devices and blockchain technology becomes important in a digital transformation, enhancing patient safety, and ensuring regulatory compliance. As the MedTech sector embraces digitalization, it enables companies to succeed in value-based healthcare environments, which results in quality care becoming more accessible and affordable. This is partly made possible through remote monitoring and proactive interventions that overcome distance. A distinctive aspect of digitalization is the ability to provide personalized care. Focusing on creating solutions and services tailored to individual needs helps to create an innovative environment within MedTechs, which can be leveraged to drive continuous growth and value creation. As digitalization becomes more influential, the MedTech industry should move closer to personalized health, which means care is centered around patients, innovation is continuous, and growth is more certain.
3. Which MedTechs have implemented successful digitalization strategies?
 
There are several large MedTechs that have successfully leveraged digitalization strategies to gain access to new revenue streams. Here we briefly describe just three. Philips is known for its diverse healthcare products and services, including imaging systems, patient monitoring, and home healthcare solutions and services. They have successfully utilized digitalization by creating a connected ecosystem of devices that capture and transmit patient data, enabling real-time monitoring and personalized care. Their strategy also includes software solutions for data analysis, predictive analytics, and telehealth, contributing to the creation of new revenue streams beyond traditional medical devices. Siemens Healthineers focuses on medical imaging, laboratory diagnostics, and advanced healthcare IT. Their digitalization strategy involves offering integrated solutions that connect medical devices, data analytics, and telemedicine platforms. For instance, their cloud-based platforms enable healthcare providers to store, share, and analyze medical images and patient data, resulting in streamlined workflows and new revenue opportunities through data-driven insights. Medtronic, a global leader in medical technology, offering a wide range of products and services in various medical specialties, has successfully embraced digitalization by incorporating smart technologies into their devices, such as pacemakers and insulin pumps, allowing remote monitoring and data collection. This has improved patient care and given the company access to new revenue streams through subscription-based services for data analytics and remote monitoring.
 
4. What defines an effective digitalization strategy?
 
In today’s business climate, developing an effective digital strategy has shifted from being a ‘nice to have’ to a necessity. As MedTechs navigate the dynamic technology landscape, digitalization has become a priority. In this section, we present a 20 'essentials' for crafting and implementing a digitalization strategy. These are not linear, but collectively constitute a path towards a digital transformation for a large diversified MedTech company.   

1. Crafting a Cohesive Vision
Digitalization starts with an evaluation of a company's existing products, services, processes, and technologies. This forms the basis upon which a vision and strategic goals are constructed. The main objective here is to align a company's aspirations with the dynamic MedTech landscape, creating a basis for innovation. Digitalization entails more than the integration of peripheral technologies. It is a paradigm shift. The initiation of a digitalization vision depends upon sound long-term strategic objectives. This involves not only envisioning the transformative potential of digitalization within an organization but also projecting its impact, whether that be improved patient experiences, data-driven operational enhancements, or the exploration of new revenue streams. As this vision takes shape, often in the form of a story that everyone in an organization can buy-into, it should steer decisions and guide investments throughout the entire digital transformation process. Further, it provides tangible benchmarks against which progress can be gauged and strategies can be refined. It is important that digitalization goals are aligned to the evolving needs of healthcare. MedTechs should harness the power of digitalization to meet the expectations of patients and adapt to dynamic clinical practices. This requires reconciling digital innovations with a company’s core values. A comprehensive and forward-looking vision (story) functions to safeguard a company's strengths against potential challenges. This first step toward a digitalization strategy serves to position a company for sustainable growth and enduring value creation.
2. Leadership commitment
The significance of securing buy-in from senior leadership teams lies in its assurance of resources, funding, and support, which are vital for the success of such an initiative. The endorsement from executives, beyond being a signal of change, serves as a catalyst for the allocation of both financial and human resources and has a substantial impact on the direction and depth of a digitalization strategy. By wholeheartedly supporting such an initiative, leaders disseminate not only a positive message about the importance attached to digitalization, but they also foster employee engagement, subsequently paving the way for the potential integration of digitalization across an entire company.

You might also like:

Redefining Leadership In The Evolving Landscape Of MedTech
3. Cross-functional synergy
Creating cross-functional teams is central for driving change, and should span departments like IT, R&D, operations, marketing, and regulatory affairs. The nature of a MedTech's digitalization strategy requires diverse expertise to successfully release technology's full potential. IT professionals contribute technical knowhow, which ensures the implementation and integration into existing infrastructure. R&D members provide visionary insights, encouraging innovative solutions and services. Operations specialists optimize processes for digital efficiency. Marketers strategize effective communications of digital progress. Regulatory experts ensure compliance and ethical considerations. Each contribution plays a distinct yet interconnected role, fostering collaborative brainstorming, shared goals, and pooled talents within a developing culture of agility and innovative. This approach breaks down silos, and aims to create a unified, technology-optimized future. Cross-functional teams act as the driving force to transform digital potential into a tangible reality.

4. Informed market insight
Market and consumer research is an important element of the strategy, as it uncovers customer needs, preferences, and pain points in digital healthcare. Such insights form the basis for tailored technologies that cater to specific needs, increasing patient engagement and satisfaction. Additionally, a successful digitalization strategy needs to identify and adapt to evolving trends in the digital MedTech sector. This entails monitoring emerging technologies, shifts in consumer behaviour, and advances in medical practices. Equally important is analyzing the competitive landscape to benchmark offerings and drive innovation. When companies are aligned to market dynamics, they are more likely to become digital leaders, fostering continuous improvement and innovation.

5. Technology assessment
Assessing a company's existing technology infrastructure helps to gauge whether a strategy can effectively leverage current investments and assets. Simultaneously, the assessment should uncover gaps and shortcomings. Identifying these informs targeted resource allocation for new technologies that support digital goals. Thus, a technology assessment allows organizations to strike a balance between leveraging existing capabilities and making targeted investments, in pursuit of their digital transformations.
6. Effective digital solutions
An essential aspect of a digitalization strategy involves identifying effective solutions and services. This process entails exploring various facets of an organization to integrate innovations; from improving customer engagement to optimizing workflows. Equally crucial is deploying technologies that improve patient outcomes, diagnoses, treatments, and monitoring. This stage also identifies potential revenue streams derived from new digital solutions and services, like remote patient monitoring, telemedicine, data analytics, and AI diagnostics, which strengthen existing offerings.
7. Partnerships
Engaging in collaborations with technology companies, start-ups, and various stakeholders creates opportunities for synergistic growth. Such partnerships enable enterprises to tap into diverse expertise, gain fresh perspectives, and access specialized resources, all of which support the development and implementation of digital solutions and services. Collaboration facilitates knowledge and resource pooling, enhancing innovation cycles and ensuring a comprehensive transformation of healthcare services. Simultaneously, acquisitions can enhance in-house capabilities. Exploring the acquisition of companies possessing relevant digital competencies or disruptive technologies offers a potential competitive edge. Such moves can help with assimilating novel technologies and developing a culture of innovation. Acquisitions can assist companies to position themselves as key players, advancing their digital health agenda and solidifying their position in an evolving industry.

8. Data management and security
Enhancing data management entails developing and implementing robust protocols. This involves refining data collection procedures, enforcing privacy and security measures, and adhering to healthcare regulations like the US Health Insurance Portability and Accountability Act (HIPAA) and the EU General Data Protection Regulation (GDPR), which safeguard patient data from breaches or misuse. Such measures establish a foundation for data management and security and help to foster stakeholder trust. Compliance with regulations like HIPAA and GDPR should not simply be viewed a legal obligation, but also as a moral commitment when handling sensitive patient data. Such a proactive stance strengthens a company's reputation for data integrity and helps to avoid legal repercussions.

9. Technology roadmap
A technology roadmap is a blueprint charting a course toward enhanced efficiency, patient-centric care, and heightened competitiveness. Beyond action planning, it provides clarity and purpose in navigating technological advancements. It consolidates an enterprise's digitalization efforts by integrating initiatives with timelines and resources, thereby establishing a framework for goal setting and assessment. Such planning assists timely project execution and supports the rationale for digitalization with measurable benefits. With a well-structured roadmap, stakeholders can appreciate how digital initiatives improve operations, trigger innovation, and enhance patient outcomes.

10. Pilot programmes
Pilot programmes serve as incubators and evidence-based validators for innovations, offering a means to test and enhance digital solutions before they are fully implemented. Such initiatives provide tangible evidence to support an enterprise's commitment to a digitalization strategy. Pilots offer concrete proof of an enterprise’s commitment to its digitalization strategy. Each programme should concentrate on specific solutions and establish a controlled setting for gathering user feedback, which constitutes an on-going effort to refine functionality. Additionally, pilots demonstrate a commitment to user-centric offerings by proactively tackling challenges, thereby improving the chances of successful, large-scale digital deployments.

11. Scalability and integration
Establishing scalability and integration capabilities is important for MedTechs to realize their digital transformation. As healthcare technology landscapes evolve and organizational needs change, the ability of digital solutions to scale and integrate with existing structures increases in importance. Ensuring these attributes contributes to a digital transformation. Scalability emphasizes a company’s adaptability to evolving demands. A scalable digital solution that expands in scope without sacrificing functionality invokes confidence. Further, integrating novel solutions and services with existing systems signals operational intelligence, which adds credibility to the digital transition. When digital solutions merge with legacy structures, they reflect an alignment of traditional expertise and cutting-edge technology. Emphasising scalability and integration involves anticipating future requirements and aligning digital strategies with longer-term organizational objectives.

12. Change management
By supporting a mindset that views digital technologies as enablers rather than disruptors, companies demonstrate their commitment to progress and cultural change. Implementing change management acknowledges the importance of cultural shifts and affirms an intent to embrace digital technologies holistically and sustainably. It acts as the vehicle, which guides an enterprise through transformation, and ensures stakeholder support for technological evolution. Through communication, training, and engagement policies, enterprises lay the groundwork for digital adoption, and smooth technology integration. This strengthens the case for change and demonstrates an organization's commitment to fostering an innovation-receptive environment.

13. Training and skill development
Central to a successful digitalization strategy is an investment in training and skill development. This underlines an organization's commitment to harnessing and effectively utilizing the transformative potential of technology. By training, corporations equip their employees with capabilities required to support digital solutions and services. Training bridges the gap between skill shortages and technological advancements. Empowering employees with the capacity to navigate digital technologies positions an enterprise for a successful transition, by a process that reconciles change with employee growth. Training reinforces the notion that digitalization is not just an operational enhancement but also a means to cultivate a workforce with capabilities, which contribute to operational excellence and sustainable expansion.

14. Regulatory adherence
Regulatory compliance is an important feature of a digital shift, as it demonstrates a company's commitment to upholding the highest standards of patient care and industry excellence. It shows that transformation is about embracing the future with integrity by ensuring that an enterprise’s  innovations are synchronized with the values underpinning medical practice. Adherence to regulatory standards is a declaration of an organization's commitment to patient safety and industry integrity. By ensuring all digital solutions and services adhere to rigorous medical regulations, corporations strengthen their case for digitalization within ethical and legal boundaries. Demonstrating adherence to medical regulations and industry benchmarks reinforces a new digital strategy as a responsible and trustworthy pursuit and showcases an organization's commitment to delivering technologies that both innovate and enhance patients' therapeutic journeys while respecting established medical protocols.

15. Market communication
Crafting a communication strategy is important as it underlines an organization’s commitment to transformation. Employing a variety of smart communication methods to describe the benefits of new digital offerings enables MedTechs to garner support from stakeholders and thereby strengthen their market position. By aiming at healthcare professionals, investors, payers, patients, providers and other stakeholders, these messages inform and persuade by highlighting the tangible benefits they bring to patient care, operational efficiency, and industry progress.

16. Feedback loop and iteration
Stakeholder feedback can be used to enhance digital solutions and services. By engaging users and patients, healthcare technologies can be tailored to cater to specific needs and preferences, fostering a user-centric design ethos. This collaborative approach identifies bottlenecks, deficiencies, and possible enhancements, which contribute to efficacious digital solutions and services. Moreover, stakeholder involvement helps to ensure a company's technological endeavours support broader healthcare goals, enhancing the overall quality of care. Iteration should be synonymous with evolution. Regularly integrating feedback to enhance the functionality of digital offerings enables an enterprise to adapt to market challenges and healthcare advancements.
17. Performance measurement
Effective evaluation of a company's digitalization strategy demands the use of key performance indicators (KPIs). These serve as a compass to assess the impact of digital solutions across patient outcomes, operational efficiency, and business expansion. By selecting relevant KPIs, MedTechs can show stakeholders the tangible effects of their digitalization strategy. These quantifiable metrics offer a lens to observe enhanced patient care, rectify operational inefficiencies, and decipher trends in business growth.
18. Fostering a culture of continuous innovation
An effective digitalization strategy relies on fostering a culture of perpetual innovation, which is essential to maintain a market-leading position. Such an approach encourages the creation, implementation and refinement of smart technological solutions and services. It equips MedTechs with the agility to quickly embrace emerging trends, capitalize on novel prospects, and tackle unforeseen challenges. Further, a culture of continuous innovation encourages an executive mindset that perceives setbacks as opportunities and views technology as evolving tools to improve patient care and operational efficacy.
 
19. Adaptation to market changes
MedTechs must rapidly adjust their digital strategies to match prevailing technological trends, regulations, and market dynamics. These ever-changing elements emphasize the need for a proactive, flexible digitalization approach that can swiftly adapt. By staying ahead of shifting trends, businesses are better positioned to leverage emerging technologies and provide solutions for evolving market needs. Navigating regulatory changes is equally important. Balancing compliance with innovative solutions ensures the integration of digital offerings in a dynamic healthcare setting. Flexibility should extend to market fluctuations, aligning digitalization strategies with customer demands and competition. This not only helps a company to navigate volatile markets but also positions it as an agile player, primed for change and enduring growth.

20. Embracing longer-term sustainability
For MedTechs, it is important that their digital strategies align with their principal longer-term objectives. Instead of solely pursuing immediate gains, this strategy should support a company's core purpose and future aspirations, which are embedded within its day-to-day operations. Such an approach establishes an innovative, adaptable, and resilient framework and strengthens the potential for growth. When a digitalization strategy is aligned with a company’s longer-term goals, it assumes the role of a catalyst for growth by optimizing the utilization of resources, improving brand resilience, and securing a distinct competitive advantage. During constantly evolving technologies and markets, such an alignment provides the capacity for a company to effectively confront challenges and capitalize on emerging opportunities, thereby either moving into, or securing, a leadership position within the rapidly changing market landscape.
 
Takeaways 
 
In the face of rapid technological evolution, the MedTech industry finds itself at a crucial juncture. While other sectors have embraced digitalization, many large diversified MedTechs have been hesitant in adopting these transformative tools. Yet, the imperative is clear: for sizable companies, the present demands recognition of digitalization's potential to drive growth and cultivate value. The fusion of conventional medical devices with digital innovations not only augments patient care but also streamlines operations and encourages innovation. The consequences of delaying this integration are significant. Without prompt action, corporations risk narrowing their competitive horizons and struggling to accelerate growth and enhance value. Failure to adapt may result in a substantial disadvantage in the rapidly changing arena of healthcare technology. It is important for MedTechs that have not already done so, to pivot towards digitalization and transform their challenges into opportunities, ensuring a dynamic and thriving future in an increasingly interconnected world.
view in full page
1 year, 4 months ago

Unleashing MedTech's Competitive Edge through Transformational Technologies

HealthPad
Directory:
Medical Technology
Tags:
AI
Artificial Intelligence
big data
commentary
digitalization
MedTech
transformational technologies
  • Digitalization, big data, and artificial intelligence (AI) are transformational technologies poised to shape the future of MedTech companies over the next decade
  • Fully embracing these technologies and integrating them in all aspects of a business will likely lead to growth, and competitive advantage while treating them as peripheral add-ons will likely result in stagnation and decline
  • MedTech executives’ analogue mindsets and resource constraints prevent them from fully embracing transformational technologies
  • There are also potential pushbacks from employees, patients, providers and investors
  • Notwithstanding, there are unstoppable structural trends forcing governments and payers throughout the world to oblige healthcare systems to leverage digitalization, big data, and AI to help reduce their vast and escalating healthcare burdens
  • Western MedTechs are responding to the rapidly evolving healthcare landscape by adopting transformational technologies and attempting to increase their presence in emerging markets, particularly China
  • To date, MedTech adoption and integration of digitalization, big data, and AI have been patchy
  • To remain relevant and enhance their value, Western MedTechs need to learn from China and embed transformational technologies in every aspect of their businesses
 
Unleashing MedTech's Competitive Edge through Transformational Technologies
Digitalization, Big Data, and AI as Catalysts for MedTech Competitiveness and Success
 
 
In the rapidly evolving landscape of medical technology, the integration of digitalization, big data, and artificial intelligence (AI) [referred to in this Commentary as transformational technologies] has emerged as a pivotal force shaping the future of MedTech companies.  Such technologies are not mere add-ons or peripheral tools but will soon become the lifeblood that fuels competition and enhances the value of MedTechs. From research and development (R&D) to marketing, finance to internationalization, and regulation to patient outcomes, digitalization, big data, and AI must permeate every aspect of medical technology businesses if they are to deliver significant benefits for patients and investors. To thrive in this rapidly evolving high-tech ecosystem, companies will be obliged to adapt to this paradigm shift.
 
Gone are the days when traditional approaches would suffice in the face of escalating complexities and demands within the healthcare industry. The convergence of transformational technologies heralds a new era, where innovation and success are linked to the ability to harness the potential of digitalization, big data, and AI. MedTech companies that wish to maintain and enhance their competitiveness must recognize the imperative of integrating these technologies across all facets of their operations. From improving their R&D processes by utilizing advanced data analytics and predictive modeling, to optimizing internal processes through automation and machine learning algorithms. Embracing such technologies opens doors to enhanced marketing strategies, streamlined financial operations, efficacious legal and regulatory endeavours, seamless internationalization efforts, and the development of innovative offerings that cater to the evolving needs of patients, payers, and healthcare providers.
 
This Commentary aims to stimulate discussion among MedTech senior leadership teams as the industry's competitive landscape continues to rapidly evolve, and the fusion of digitalization, big data, and AI becomes not only a strategic advantage but a prerequisite for survival in an era defined by data-driven decision-making, personalized affordable healthcare, and a commitment to improving patient outcomes.
 
In this Commentary

This Commentary explores digitalization, big data, and AI in the MedTech industry. It presents two scenarios: one is to fully embrace these technologies and integrate them into all aspects of your business and the other is to perceive them as peripheral add-ons. The former will lead to growth and competitive advantage, while the latter will result in stagnation and decline. We explain why many MedTechs do not fully embrace transformational technologies and suggest this is partly due to executives’ mindsets, resource constraints and resistance from employees, patients, and investors. Despite these pushbacks, the global healthcare ecosystem is undergoing an unstoppable transformation, driven by aging populations and significant increases in the prevalence of costly to treat lifetime chronic conditions. Western MedTechs are responding to structural shifts by adopting transformational technologies and increasing their footprints in emerging markets, particularly China. To date, company acceptance of AI-driven strategies has been patchy. We suggest that MedTechs can learn from China and emphasize the need for organizational and cultural change to facilitate the comprehensive integration of transformational technologies. Integrating these technologies into all aspects of a business is no longer a choice but a necessity for companies to stay competitive in the future.
You might also like:
 
Transformational technologies in MedTech

Digitalization in the MedTech industry involves adopting and integrating digital technologies to improve healthcare delivery, patient care, and operational efficiency. It transforms manual and paper-based processes into digital formats, enabling electronic health records, connected medical devices, telemedicine, and other digital tools. This allows for seamless data exchange and storage, improving clinical processes, decision-making, and patient empowerment. Big data in the MedTech industry refers to the vast amount of healthcare-related information collected from various sources. It includes structured and unstructured data such as patient demographics, clinical notes, diagnostic images, and treatment outcomes. Big data analysis identifies patterns, correlations, and trends that traditional methods may miss. They aid medical research, drug discovery, personalized medicine, clinical decision support, evidence-based care, population health management, and public health initiatives. Data privacy, security, and ethical use are crucial considerations. Artificial Intelligence (AI) in the MedTech industry uses computer algorithms to simulate human intelligence. AI analyzes medical data to identify patterns, make predictions, and improve diagnoses, treatment plans, and patient outcomes. It assists in medical imaging interpretation, personalized medicine, and patient engagement. In R&D, AI accelerates the development of devices and the discovery of new therapies and has the capacity to analyze scientific literature and molecular data. The technology serves as a tool to augment healthcare professionals' expertise and support decision-making.
With the proliferation of large language AI models (LLM) and to borrow from a recent essay by Marc Andreeseen - an American software engineer, co-author of Mosaic, [one of the first widely used web browsers] and founder of multiple $bn companies - everyone involved with medical technology, including R&D, finance, marketing, manufacturing, regulation, law, international etc., “will have an AI assistant/collaborator/partner that will greatly expand their scope and achievement. Anything that people do with their natural intelligence today can be done much better with AI, and we will be able to take on new challenges that have been impossible to tackle without AI, including curing all diseases.”

Two scenarios

We suggest there are only two scenarios for MedTechs: a company that fully embraces transformational technologies and one that does not. The former, will benefit from strengthened operational efficiencies, improved patient outcomes, and enhanced innovations, which will lead to increased market share and investor confidence. By leveraging digital technologies, such as remote monitoring devices, telemedicine platforms, LLMs, and machine learning, a company will be able to offer more personalized, effective and affordable healthcare services and solutions. An enterprise that integrates these technologies into their strategies and business models will, over time, experience improved growth prospects, increased revenues, and potentially higher profitability. These factors will contribute to a positive perception in the market, leading to an increase in company value. MedTechs that fail to fully embrace digitalization, big data, and AI will face challenges in adapting to the rapidly evolving healthcare landscape. They will struggle to remain competitive and relevant in a market that increasingly values transformational technologies and data-driven approaches. As a result, such companies will experience slower growth, lower market share, and limited investor interest, which will lead to a stagnation or decline in their value.
 
The analogue era's influence on MedTechs

If the choice is so stark, why are many MedTechs not grabbing the opportunities that transformational technologies offer? To answer this question let us briefly remind ourselves that the industry took shape in an analogue era, which had a significant effect on how MedTech companies evolved and established themselves. During the high growth decades of the 1980s, 1990s, and early 2000s, the medical technology industry operated with limited access to the technologies that have since radically changed healthcare. The 1980s marked a period of advancements, which included the widespread adoption of medical imaging such as computed tomography (CT) scans and magnetic resonance imaging (MRI). These modalities provided detailed visualizations of the human body, supporting more accurate diagnoses. Medical devices like pacemakers, defibrillators, and implantable cardioverter-defibrillators (ICDs) were developed and improved the treatment of heart conditions. The 1990s witnessed further advancements, with a focus on minimally invasive procedures. Laparoscopic surgeries gained popularity, allowing surgeons to perform operations through small incisions, resulting in reduced patient trauma and faster recovery times. The development of laser technologies enabled more precise surgical interventions. The decade also saw the rise of biotechnology, with the successful completion of the Human Genome Project and increased emphasis on genetic research. The early 2000s saw the emergence of digital transformation in some quarters of the medical technology industry. Electronic medical records (EMRs) began to replace paper-based systems, increase data accessibility and upgrade patient management. Telemedicine, although still in its nascent stages, started connecting healthcare providers and patients remotely, overcoming geographical barriers. Robotics and robotic-assisted surgeries gained traction, enabling more precise and less invasive procedures. During these formative decades, the medical technology industry focused on enhancing diagnostic capabilities, improving treatment methods, and streamlining healthcare processes. The industry had yet to witness the transformational impact of digitalization, big data and AI that would emerge in subsequent years, enabling more advanced analytics, personalized medicine, and interconnected healthcare systems.
 
From analogue to digital

During these formative analogue years, MedTechs experienced significant growth and expansion, where innovative medical technologies changed healthcare practices and improved patient outcomes. Companies thrived by leveraging their expertise in engineering, biology, and clinical research and developed medical devices, diagnostic tools, and life-saving treatments. For MedTechs to experience similar growth and expansion in a digital era, they must fully harness the potential of transformational technologies, and to achieve this, there must be a receptive mindset at the top of the organization.
 
According to a recent study by Korn Ferry, a global consulting and search firm, the average age of CEOs in the technology sector is 57, and the average age for a C-suite member is 56. Thus, as our brief history suggests, many MedTech executives advanced their careers in a predominantly analogue age, prior to the proliferation of technologies that are transforming the industry today. Thus, it seems reasonable to suggest that this disparity in experience and exposure colours the mindsets of many MedTech executives, which can lead to them underestimating and under preparing for the significant technological changes that are set to reshape the healthcare industry over the next decade. Senior leadership teams play a pivotal role in developing the strategic direction of companies and driving their success. Without a proactive mindset shift, these executives may struggle to fully comprehend the extent of the potential disruptions and opportunities that digitalization, big data, and AI bring.
 
By embracing such a mindset shift, senior leadership teams could foster a culture of innovation and agility. But they must recognize the urgency of preparing for a future fueled by significantly different technologies from those they might be more comfortable with. Such urgency is demonstrated by a March 2023 Statista report, which found that in 2021, the global AI in healthcare market was worth ~US$11bn, but forecasted to reach ~US$188bn by 2030, increasing at a compound annual growth rate  (CAGR) of ~37%. As these and other facts (see below) suggest, the integration of digitalization, big data, and AI has already begun to redefine healthcare delivery, patient engagement, and operational efficiency and is positioned to accelerate in the next decade. To remain competitive and relevant in this rapidly evolving high-tech world, MedTechs must foster a culture of openness to change and innovation. Leaders should encourage collaboration, both internally and externally, and create cross-functional teams that bring together expertise from various domains, including AI and data analytics. This multidisciplinary approach facilitates the integration of transformational technologies into all aspects of the business, ensuring that the organization remains at the forefront of the evolving industry.
 
Implementation and utilization

Limited resources, such as budgets and IT infrastructure, can hinder the adoption and utilization of digitalization, big data, and AI, especially for smaller companies. Compliance with healthcare regulations like HIPAA and GDPR adds complexity and can slow down technology implementation. Resistance to change from employees, healthcare providers, and patients also poses challenges. Fragmented and unstandardized healthcare data limit the effectiveness of AI-driven strategies. The expertise gap can be bridged through collaboration with academic institutions and technology companies. Demonstrating the tangible benefits of digitalization, big data and AI is essential to address concerns about return on investments (ROI). Strategic planning, resource investment, collaboration, and cultural change are necessary for the successful implementation and utilization of transformational technologies in MedTech companies. 
 
Organizational and cultural changes

MedTechs must embrace agility and innovation to harness the potential benefits from transformational technologies. This requires fostering a culture that encourages risk-taking and challenges conventional practices. Creating cross-functional teams and promoting collaboration nurtures creativity and innovative solutions. Transitioning to data-driven decision-making involves establishing governance frameworks, ensuring data quality, and leveraging analytics and insights from big data. Talent development and upskilling are crucial, necessitating training programmes to improve digital literacy and add analytics skills. Collaboration and partnerships with external stakeholders facilitate access to cutting-edge technologies. Enhancing patient experiences through user-friendly interfaces and personalized solutions is essential. Investing in agile technology infrastructure, including cloud computing and robust cybersecurity measures is necessary. MedTechs must navigate complex regulatory environments while upholding ethical considerations, transparency, and patient consent to gain credibility and support successful technology adoption.
 
Investors

A further potential inhibitor to change is MedTech investors who may harbour conservative expectations that tend to discourage companies from taking risks, such as fully embracing and integrating digitalization, big data, and AI across their entire businesses. This mindset also can be traced back to the formative analogue decades on the 1980s, 1990s, and early 2000s when investors became accustomed to growing company valuations. During that time, most MedTechs catered to an underserved, rapidly expanding market largely focussed on acute and essential clinical services in affluent regions like the US and Europe, where well-resourced healthcare systems and medical insurance compensated activity rather than patient outcomes. However, the landscape has since undergone a radical change. Aging populations with rising rates of chronic diseases have significantly increased the demands on over-stretched healthcare systems, which have turned to digitalization, big data, and AI in attempts to reduce their mounting burdens. These shifting dynamics now demand a more forward-thinking approach, but investor expectations often remain fixed on a past traditional model, which impedes the adoption and full integration of transformational technologies into MedTech enterprises.

To overcome investor conservatism and reluctance to embrace transformational technologies requires a concerted effort by MedTechs to demonstrate the tangible benefits of these technologies on the industry. Companies can focus on providing evidence of improved patient outcomes, increased efficiency, cost savings, and competitive advantages gained through the integration of digitalization, big data, and AI. Engaging in open and transparent communications with investors, showcasing successful case studies, and highlighting the long-term potential and sustainability of a technology-driven approach can help shift investor expectations and encourage a more receptive attitude towards risk-taking and innovation.
Global structural drivers of change

For decades, Western MedTechs have derived comfort from the fact that North America and Europe hold 68% of the global MedTech market share. These wealthy regions have well-resourced healthcare systems, which, as we have suggested, for decades rewarded clinical activity rather than patient outcomes, and MedTech’s benefitted by high profit margins on their devices, which contributed to rapid growth, and enhanced enterprise values. Today, the healthcare landscape is significantly different. North America and Europe are experiencing aging populations, and large and rapidly rising incidence rates of chronic diseases in older adults. Such trends are expected to continue for the next three decades and have forced governments and private payers to abandon compensating clinical activity and adopt systems that reward patient outcomes while reducing costs. This shift has put pressure on healthcare systems to adopt transformational technologies to help them cut costs, increase access, and improve patient journeys. MedTech companies operating in this ecosystem have no alternative but to adapt. Their ticket for increasing their growth and competitiveness is to adopt and integrate digitalization, big data, and AI into every aspect of their business, which will help them to become more efficient and remain relevant.
You might also like:
 
 
Most developed economies are experiencing aging populations, which affect everything from economic and financial performance to the shape of cities and the nature of healthcare systems. Let us illustrate this with reference to the US. According to the US National Council on Aging, ~56m Americans are ≥65 and this cohort is projected to reach ~95m by 2060. On average, a person ≥65 is expected to live another 17 years. Older adult Americans are disproportionately affected by costly to treat lifetime chronic conditions such as cancer, heart disease, diabetes, respiratory disorders, and arthritis. ~95% of this older adult cohort have at least one chronic disease, and ~80% have two or more. Multiple chronic disorders account for ~66% of all US healthcare costs and ~93% of Medicare spending.

According to a May 2023, Statista report, the US spends more on healthcare than any other country. In 2021, annual health expenditures stood at US$4.2trn, ~18% of the nation’s Gross Domestic Product (GDP). The demographic trends we described in the US are mirrored in all the principal global MedTech markets. Many of which, particularly Japan, are also experiencing shrinking working age populations resulting from a decline in fertility rates, and curbs on immigration. This shrinkage further impacts a nation’s labour force, labour markets, and tax receipts; all critical for resourcing and paying for healthcare services.
 
MedTechs’ response to structural changes

Western MedTechs’ response to these structural challenges have been twofold: (i) the adoption of transformational technologies, which contribute to lowering healthcare costs, improving innovation, and developing affordable patient-centric services and solutions and (ii) targeting emerging markets as potential areas for growth and development. As we have discussed the first point, let us consider briefly the second. Decades ago, giant MedTechs like Johnson and Johnson (J&J), Abbott Laboratories and Medtronic established manufacturing and R&D centres in emerging economies like Brazil, China, and India, where markets were growing three-to-four times faster than in developed countries. Notwithstanding, many MedTechs, were content to continue serving wealthy developed regions - the US and Europe - and either did not enter, or were slow to enter, emerging markets. More recently, as a response to the trends we have described, many MedTechs are either just beginning or accelerating their international expansions. However, such initiatives might be too late to reap the potential commercial benefits they anticipate. Establishing or expanding a footprint in emerging economies is significantly more challenging today than it was two decades ago. 

For instance, two decades ago, China lacked medical technology knowhow and experience and welcomed foreign companies’ participation in its economy. Today, the country has evolved, enhanced its technological capacity and capabilities, and is well positioned to become the world’s leading technology nation by 2030. No longer so dependent on foreign technology companies, the Chinese Communist Party (CCP) raised barriers to their entry. In 2017, government leaders announced the nation's intention to become a global leader in AI by putting political muscle behind growing investment by Chinese domestic technology companies, whose products, services and solutions were used to improve the country's healthcare systems. Over decades, the CCP committed significant resources to developing domestic STEM skills, and research to achieve “major technological breakthroughs” by 2025, and to make the nation a world leader in technology by 2030, overtaking its closest rival, the US. According to a 2023 AI Report from the Stanford Institute for Human-Centered Artificial Intelligence, in 2021, China produced ~33% of both AI journal research papers and AI citations worldwide. In economic investment, the country accounted for ~20% of global private investment funding in 2021, attracting US$17bn for AI start-ups. The nation’s AI in the healthcare market is fueled by the large and rising demand for healthcare services and solutions from its ~1.4bn population, a large and rapidly growing middle class, and a robust start-up and innovation ecosystem, which is projected to grow from ~US$0.5bn in 2022 to ~US$12bn by 2030, registering a CAGR of >46%. 

>4 years ago, a HealthPad Commentary described how a Chinese internet healthcare start-up, WeDoctor, founded in 2010, bundles AI and big data driven medical services into smart devices to help unclog China’s fragmented and complex healthcare ecosystem and increase citizens’ access to affordable quality healthcare. The company has grown into a multi-functional platform offering medical services, online pharmacies, cloud-based enterprise software for hospitals and other services. Today, WeDoctor owns 27 internet hospitals, [a healthcare platform combining online and offline access for medical institutions to provide a variety of telehealth services directly to patients], has linked its appointment-making system to another 7,800 hospitals across China (including 95% of the top-tier public hospitals) and hosts >270,000 doctors and ~222m registered patients. It is also one of the few online healthcare providers qualified to accept payments from China's vast public health insurance system, which covers >95% of its population. WeDoctor, like other Chinese MedTechs, has expanded its franchise outside of China and has global ambitions to become the “Amazon of healthcare”. China’s investment in developing and increasing its domestic transformational technologies and upskilling its workforce has made the nation close to technological self-sufficiency and has significantly raised the entry bar for Western MedTechs wishing to establish or extend their presence in the country.

China's progress in AI and digital healthcare underscores the urgent need for Western MedTechs to adopt and implement these technologies. To remain relevant and survive in a rapidly changing global healthcare ecosystem, Western MedTechs might do well to learn from China's endeavours in leveraging AI, big data, and digitalization to drive innovation, enhance competitiveness, and ultimately contribute to the transformation of the global healthcare landscape. Notwithstanding, be minded of the ethical concerns Western nations have regarding China’s utilization of big data and AI in its healthcare system and its potential to compromise privacy and individual rights due to the CCP's extensive collection and analysis of personal health data.
 
Takeaways

Digitalization, big data, and AI are transformational technologies that have the power to influence the shape of MedTech companies over the coming decade, and their potential impact should not be underestimated. Fully embracing these technologies and integrating them into every aspect of a business is necessary for growth and competitive advantage. On the other hand, treating them as peripheral add-ons will likely lead to stagnation and decline. However, the path towards their full integration in companies is not without its challenges. MedTech executives, hindered by their analogue mindsets and resource constraints, often struggle to fully embrace the potential of digitalization, big data, and AI. Moreover, there may be pushbacks from various stakeholders including employees, patients, healthcare providers, and investors. These concerns and resistances can impede the progress of transformation within the industry. Nonetheless, governments and payers across the globe are being compelled by unstoppable structural trends to enforce the utilization of digitalization, big data, and AI within healthcare systems. The large and escalating healthcare burdens facing economies throughout the world leave them with little choice but to leverage these technologies to reduce costs, improve patient access and outcomes. In response to the rapidly evolving healthcare landscape, Western MedTechs are making efforts to adopt transformational technologies and expand their presence in emerging markets, particularly China. They recognize the need to stay ahead of the curve and adapt to the changing demands of the industry. However, the adoption and integration of digitalization, big data, and AI by companies thus far have been inconsistent and patchy. To remain relevant and enhance their value, Western MedTechs, while being mindful of ethical concerns about China’s use of AI-driven big data healthcare strategies, might take cues from their Chinese counterparts and embed these transformational technologies in every aspect of their businesses. The transformative impact of digitalization, big data, and AI on MedTech companies cannot be overstated. While challenges and resistance may arise, the inexorable drive towards leveraging these technologies is unstoppable. MedTech companies should shed their analogue mindsets and resource constraints and fully embrace the potential of these transformational technologies.
view in full page
1 year, 8 months ago

Re-imagining healthcare

HealthPad
Directory:
Medical Technology
Tags:
Artificial Intelligence
big data
commentary
Machine Learning
  • Recently, Peter Arduini, CEO of GE Healthcare, proclaimed that the software development business “is central to our growth strategy”
  • Although AI is in its infancy, AI technology has become embedded in all aspects of care journeys: from diagnosis to recuperation at home; from prevention to improved lifestyles
  • Notwithstanding, many established MedTech leaders still advocate the production of physical devices for episodic surgical interventions marketed by B2B business models in wealthy regions of the world
  • Jenson Huang, a key opinion leader from the AI industry recently stressed how rapidly AI technologies have advanced over the past decade and predicts that AI “will revolutionize all industries” over the next decade
  • If Huang is right and more MedTech leaders bet their future growth on innovative AI driven strategies, healthcare systems will be soon re-imagined

Re-imagining healthcare
 
On 16 February 2023, a Wall Street Journal article announced, “GE Healthcare Makes Push into Artificial Intelligence”. The company, spun-out of General Electric (GE) in January 2023, is now an independent enterprise traded on Nasdaq, and Peter Arduini, its Chief Executive, says that the software development business “is central to our growth strategy”. In the first instance, GE Healthcare is planning to apply artificial intelligence (AI) and machine learning (ML) techniques to masses of disparate data generated by hospitals during patients’ therapeutic journeys, to enhance hospital services, improve patient outcomes and reduce healthcare costs.
 
Arduini is right. However, to fully appreciate the future potential impact of AI technologies on the medical technology industry and healthcare systems, we need to engage with key opinion leaders (KOL) from the AI industry. One such leader is Jenson Huang, a Taiwanese-American electrical engineer, founder, president and CEO of Nvidia, a semiconductor company launched in 1993. Today, it is a world leading, Nasdaq traded AI technology enterprise with a market cap of ~US$509bn, annual revenues of ~US$27bn and >26,000 employees. To put this into a perspective: if AI was the mid-19th century gold rush in the US, then Nvidia would be the producer of pickaxes for the hundreds of thousands of prospectors drawn to Sutter's Mill in Coloma, California. But before engaging with Huang, let us get a better understanding of the state of healthcare systems, AI and ML.
 
In this Commentary

This Commentary discusses Arduini’s proposition that AI big-data driven software strategies, which aim to enhance patient outcomes and reduce healthcare costs, are key to the growth of medical technology companies. This raises a question whether traditional MedTechs, producing physical devices, and marketing them with B2B business models will create sufficient growth and value over the next decade to satisfy their investors. Although AI technologies are in their infancy, they have already entered many areas of healthcare and are well positioned to play a significant role in future, re-imagined healthcare systems. The Commentary describes AI and ML, provides a brief history of AI, outlines its recent uptake in healthcare and notes how AI technologies have been used by both agile start-ups and giant techs to develop ‘big ideas’ with the potential to disrupt the medical technology market. We briefly describe six start-ups that have leveraged AI to enter the MedTech market and by doing so, increased the competitive pressure on traditional enterprises. Although AI technologies have only recently been introduced to healthcare systems, they are embraced by the FDA and feature in many aspects of patients’ therapeutic journeys: from diagnosis and treatment to recovery and rehabilitation at home. The Commentary takeaways suggest that the actions of industry leaders like Peter Arduini will have a significant impact of the shape on healthcare systems over the next decade.
 
Healthcare in crisis

Healthcare systems throughout the world are in crisis and experiencing large and rapidly growing care gaps,which we have described in previous Commentaries. These are created by growing shortages of health professionals and a vast and rapidly growing demand for care from aging populations; a significant proportion of which present with chronic lifetime diseases, such as heart disorders, diabetes, and cancer, that require frequent physician visits and more resources to treat. Such care gaps result in millions of people having difficulties gaining prompt access to health services, which delay diagnosis, worsen patient outcomes, and increase treatment costs. 

Addressing such issues requires re-imagining healthcare systems. Commercial enterprises have a role to play. Like GE Healthcare, agile start-ups and giant techs have embraced new and evolving AI technologies to create innovative offerings that provide solutions to care gaps predicated upon patient-centric, AI big-data strategies. However, many traditional medical technology companies have not developed software offerings and continue to focus on the production of physical devices, and B2B business models to support episodic hospital-based surgical interventions.  
 
Brief history of AI

AI refers to the development of computer systems that can perform tasks, which typically require human intelligence, such as decision making and natural language processing. The technology is based on the premise that machines can learn from data, identify patterns, and make recommendations with minimal human intervention. ML algorithms [instructions carried out in a specific order to perform a particular task] build mathematical models based on sample data, referred to as "training data", to make predictions or decisions without being explicitly programmed to do so.
 
AI has been around since the 1950s. The term was coined by computer scientist John McCarthy in 1956 at the Dartmouth Workshop in Hanover, New Hampshire, USA. In the early days of AI, scientists focused on building computers that could think, reason, and solve problems like humans. In the 1960s and 1970s, AI research concentrated on developing more advanced algorithms and techniques for programming computers to solve tasks. This resulted in expert systems, which used knowledge-based decision making to solve complex problems. In the 1980s, AI shifted towards ML, which allowed computers to learn from experience by enabling them to recognize patterns and make decisions based on data. In the 1990s, AI developed methods for robots to interact with their environment and learn from experience. This led to autonomous robots that can navigate and perform tasks in the real world. Today, AI research is focused on creating more intelligent and autonomous systems and is used in a wide range of applications, and increasingly in healthcare.
 
AI and healthcare

AI’s use in healthcare can be traced back to the 1970s, when researchers developed expert systems that could diagnose and treat certain medical conditions. Early AI healthcare applications were limited by the availability of data and the dearth of computer power. In the 1990s, as computing power increased and the internet became more widely available, AI began to be used more extensively in healthcare. One of the early applications was in radiology, where it was used to interpret medical images. Other applications included decision support systems for medical diagnoses and treatments, and natural language processing systems for medical documentation. In the 2000s, the use of AI continued to expand, with the development of ML algorithms that could analyze large datasets to identify patterns and make predictions. These were used in a variety of healthcare applications, including personalized medicine, drug discovery and medical imaging.
 
Today, AI benefits a wide range of healthcare applications from faster diagnosis to the prediction of pandemics, from clinical decision support to digital therapeutics. The aspiration of AI driven solutions and services in healthcare is super-human performance, free from errors and inconsistencies, and scalable to provide expert-level care across entire health systems. AI technologies have the potential to provide services that improve the accuracy and speed of medical diagnoses and treatments, monitor conditions, assist with recovery, support medicine regimens, facilitate personalized healthcare and reduce costs for providers. These functions are relevant in the context of attempts to narrow care gaps, but they require vast amounts of computing power, which most companies do not have in-house.
 
This is where cloud computing, and Nvidia's new solution come in. Dubbed "DGX Cloud", Nvidia’s offering is an AI supercomputer accessible via a web browser. The company has partnered with various cloud providers, including Microsoft, Google, and Oracle to develop the service, which provides enterprises easy access to the world’s most advanced AI platform and allows them to run large, demanding ML and deep learning workloads on graphic processing units (GPUs) to generate and implement ‘big ideas’.
 
Big ideas

New entrants to the medical technology market - agile start-ups and giant techs - often have ‘big ideas’; innovations with the potential to inspire stakeholders and disrupt the industry. By contrast, traditional MedTechs who do not employ AI strategies tend to have a dearth of big ideas and mainly focus their R&D spend on incremental improvements to their legacy devices. By contrast, new entrants have accelerated the use of AI, ML, and data analytics to help diagnose diseases earlier and monitor patients remotely. Further, they have championed wearable devices like Fitbits and Apple Watches that help people track their health metrics and allows them to make smarter decisions about their wellbeing. This is helping to transform the modality of healthcare from ‘diagnosis and treatment’ to ‘prevention and lifestyle’. 
 
Start-ups with big ideas
 
There are hundreds of healthcare start-ups with big ideas predicated upon innovative AI technology. To provide a flavour of these we briefly describe six.
 
Biofourmis
Boston based Biofourmis was founded in 2015. Its Biovitals™ Analytic Engine brings patient-specific data and ML together to provide the right care, to the right patients, at the right time. Advanced analytics process continuous and episodic data, notify clinicians of changes in patients’ conditions, and enable early intervention. With digital medicine, modular treatment algorithms (based on a patient’s disorder) enable the delivery of optimal medication.
 
You might also like: 
TytoCare
TytoCare is a New York-based medical technology start-up, founded in 2012, which aims to transform primary care by enabling people to have 24-7 medical examinations with a physician from the comfort of their home. The company has developed a suite of easy-to-use medical devices with built-in guidance technology and ML algorithms to ensure accuracy, which replicate face-to-face clinician visits. The devices include a hand-held modular tool for examining the lungs, throat, heart, skin, ears, and body temperature, and a health platform link to the cloud for storing, analysing, and sharing health data derived from the examinations.
 
Doctolib
Doctolib is a French digital health company founded in 2013. Its main product is a software-as-a-service platform for health professionals, which allows patients to book in-person and video consultations with healthcare providers. In January 2021, Doctolib acquired Tanker, a French start-up that developed the world’s first end-to-end encryption platform in the cloud, which Doctolib had been using since 2019. The Tanker platform is designed to be used by developers with no cryptographic skills and enables online businesses to easily encrypt their user’s sensitive data at the source: directly on end-users' devices. In October 2021, Doctolib acquired Dottori, an Italian online medical appointment scheduling service. The company is currently valued at >US$6bn, and  is used by ~300,000 healthcare professionals and ~70m patients in Europe.
 
CMR Surgical
CMR Surgical develops equipment and systems that aid in minimal access surgeries. During its establishment in 2014 in Cambridge, UK, the company’s founders asked, “why are so many people not receiving minimal access surgery and how can we change this?”. CMR’s main product is “Versius”, an EUMDR compliant device developed for high precision operations. During surgical procedures it can continuously collect data, which are stored and analysed to support surgeon training, and enhance the performance of future surgeries.
 
Healthy.io
Healthy.io is an Israeli start-up established in 2013. Its founders saw an opportunity to increase access to healthcare by leveraging the continuous improvement in smartphone cameras, which they transformed into at-home medical devices. As smartphone camera capabilities grew, Healthy.io’s range of clinical grade services expanded. With the company’s app and kits, users can undertake unitary tract infection (UTI) testing, prenatal monitoring, open wound assessments, and more, all in their homes. Health.io has partnered with healthcare systems throughout the world to provide clinical results at critical moments.
 
Proov
Proov, a US femtech start-up based in Boulder, Colorado, whose flagship offering is a rapid response progesterone test strip invented by Amy Beckley, a pharmacologist, with expertise in hormone signaling. It is the only FDA-cleared (March 2020) urine progesterone (PdG) test to confirm successful ovulation at home. Lack of, or insufficient ovulatory events, is the primary cause of infertility worldwide. In the US, ~12% of couples are diagnosed with infertility each year.  Thus, being able to confirm ovulation is an essential component of infertility evaluations in women.  Gold standards for confirming ovulation include transvaginal ultrasounds and serum progesterone blood draws. Both techniques are invasive, expensive, and/or inaccessible to most women. Proov’s offering is a non-invasive, inexpensive, home-based testing system.
 
A new era for AI in healthcare
 
Such start-ups with AI driven offerings suggest a new era for healthcare, which also is signalled in the introduction to a 2021, FDA action plan for AI/ML-based software medical devices. The plan describes how traditional B2B MedTech strategies are being complemented with B2C digital solutions and services that support entire patient journeys. According to the FDA’s action plan, “Artificial intelligence (AI) and machine learning (ML) technologies have the potential to transform healthcare by deriving new and important insights from the vast amount of data generated during the delivery of healthcare every day. Medical device manufacturers are using these technologies to innovate their products to better assist healthcare providers and improve patient care. One of the greatest benefits of AI/ML in software resides in its ability to learn from real-world use and experience, and its capability to improve its performance. FDA’s vision is that, with appropriately tailored total product lifecycle-based regulatory oversight, AI/ML-based Software as a Medical Device (SaMD) will deliver safe and effective software functionality that improves the quality of care that patients receive”. The agency currently has several ongoing projects designed to develop and update regulatory frameworks specific to AI. As of early 2023, there have been >500 FDA approved AI/ML-algorithms as medical devices.
 
Al and healthcare systems

Although AI is in its infancy and has only relatively recently begun to be used in healthcare systems, it has already taken root in many healthcare applications, including data analysis, diagnoses, monitoring, personalized apps, robotics, wearables, and virtual health assistance. This suggests a new era and the re-imagination of healthcare. Ambulances have become smart platforms, equipped with AI-based systems connected to hospitals, which can be used to diagnose medical conditions and provide real-time treatment recommendations. A&E departments use AI driven automated triage and diagnosis systems to assess incoming patients and prioritize those with the most serious conditions quickly and accurately. AI is also used to automate the dispensing of medications. Hospitals employ AI-based systems to analyze medical images such as X-rays and CT scans, which help medical personnel to quickly identify any abnormalities and make more accurate diagnoses. Surgery employs AI-enabled systems to assist with planning procedures, automating the delivery of anesthesia, and performing complex and delicate surgical interventions. Virtual recovery coaches use AI technology to create personalized plans for individuals recovering. Smart systems collect real time patient data and provide advice and support to help patients stay on track from their homes. AI-powered medication management systems help patients to track and manage their medications and send alerts to healthcare providers if there are any issues.
You might also like:

Have diversified medical technology companies blown their competitive advantage?
 
The cusp of a new era

According to Huang, a new era of AI has been triggered by a technology most people have become familiar with over the past few months: ChatGPT. Developed by OpenAI and built on top of its family of generative, large language processing models, which have been fine-tuned using both supervised and reinforcement learning techniques.
Huang views ChatGPT, as “one of the greatest things that have been done in computing”. Generative AI models [algorithms that generate new outputs based on the data they have been trained on] have >100bn parameters and are the most advanced neural networks in today's world.  In no computing era has one computing platform (ChatCPT) reached ~150m people in ~60 days. In commercial terms this means, “a torrent of new companies and new applications . . . Nvidia is working with ~10,000 AI start-ups throughout the world in almost every industry”, says Huang. In a February 2023 earnings call to analysts Huang said that ChatGPT has incentivized businesses of all sizes to purchase Nvidia’s chips to develop ML software. Following the call, Nvidia’s market cap rose by US$79bn.
 
The democratization of AI programming

Huang’s enthusiasm for ChatGPT is partly because he perceives it as “democratising programming” by making human language a perfectly good computer programming language. The platform has the capacity to understand human-explained requests, generate coherent answers, translate texts, write code, and more. It has excited enterprises throughout the world and can be used for copywriting, translation, search, customer support, and other applications. While ChatGPT has many advantages, PyTorch and TensorFlow, two free and open-source software libraries have arguably done more to democratise programming by making it relatively easy to develop sophisticated ML applications without extensive programming skills. Notwithstanding, Huang is right to stress the significant leaps forward made by AI in the recent past and right to suggest that “AI is at a watershed moment for the world”.
 
Edge computing

Over the next decade, Huang predicts there will be a proliferation of edge-computing made possible by the spread of the Internet of Things (IoT). Edge computing is a connectivity paradigm that focusses on placing processing near to the source of data. This suggests that fewer activities will be executed using cloud computing. Instead tasks will be relocated to a user’s PC, cell phone or IoT devices. Huang refers to these as ‘AI factories’, which are positioned to have a significant impact on healthcare. By 2025, the global market for Internet of Medical Things (IoMT) is estimated to reach >US$500bn. This signals a significant change because currently most healthcare computing takes place in on-premises networks or, in the cloud. However, processing healthcare data from afar can be limited by infrastructures that cannot manage them quickly, securely, or cost-effectively. To address these issues, healthcare companies are implementing edge computing, which facilitates data being analysed and acted upon at the site of collection. This reduces end-to-end congestion and the constraints of limited connectivity and data broadband connections across vast distances by lowering transmission time, while also reducing risks to privacy and data protection. 

According to Huang, “AI processing performance has been boosted by a factor of no less than one million in the last 10 years”. Over the course of the next decade Huang predicts there will be, “new chips, new interconnections, new systems, new operating systems, new distributed computing algorithms and new AI algorithms (which will) accelerate AI by another million times."
 
Takeaways

Our discussion suggests that Peter Arduini, CEO of GE Healthcare, is right: software development is central to the growth potential of medical technology companies. Over the past two decades AI, ML and big-data strategies have substantially extended the horizons of industry players by giving them the means to provide software solutions and services to support entire patient journeys. This has introduced B2C MedTech business models, which complement conventional B2B models, and have the potential to provide access to new revenue streams while improving patient outcomes and reducing healthcare costs. If software initiatives like Arduini’s and others spread, healthcare systems are likely to be re-imagined. The fundamental technology of MedTech leaders is intelligence. But as Huang suggests, “We’re in the process of automating intelligence”, which can only empower industry executives. “The thing that’s really cool”, says Huang, “is that AI is software that writes itself, and it writes software that no humans can. It’s incredibly complex. And we can automate intelligence to operate at the speed of light, and because of computers, we can automate intelligence and scale it out globally instantaneously”. If Huang is right, over the next decade, AI is well positioned to play a significant role in re-imagining healthcare.
view in full page
1 year, 10 months ago

The impact of big data, artificial intelligence, and machine learning on the medical technology industry

HealthPad
Directory:
Medical Technology
Tags:
Artificial Intelligence
big data
cloud service
commentary
cybersecurity
Machine Learning
MedTech
  • 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.

You might also like: 
 
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.
You might also like:

Can elephants be taught to dance?



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.
view in full page
5 years, 11 months ago

WeDoctor’s impact on global healthcare

HealthPad
Directory:
Medical Technology
Tags:
affordable quality healthcare
AI
Artificial Intelligence
big data
commentary
global healthcare systems
smart devices
WeDoctor
  • Experienced Western healthcare professionals have little knowledge of WeDoctor a Chinese internet healthcare start-up positioned to have a significant impact on global healthcare systems over the next decade
  • Founded in 2010 and backed by Tencent, a US$0.5trn Chinese conglomerate, WeDoctor has grown rapidly to become an influential US$6bn enterprise
  • WeDoctor bundles services AI and big data strategies into smart devices to help unclog China’s fragmented and complex healthcare system and increases citizens’ access to affordable quality healthcare
  • WeDoctor has expanded its franchise outside of China and has global ambitions to become the “Amazon of healthcare”
  • Is WeDoctor an exemplar for Western healthcare providers?
 
WeDoctor’s impact on global healthcare

The speed and scoop of technological change is forcing traditional healthcare providers to move beyond the comfort of their production models, embrace services and develop smart devices, which support customer-centric, value-based, data driven strategies. To illustrate this shift, we describe a Chinese internet healthcare start-up WeDoctor, which is having an impact on re-engineering China’s overly bureaucratic, fragmented and complex healthcare system and is positioned to influence the delivery of value-based healthcare services globally in the next decade.
 
In this Commentary

This Commentary describes WeDoctor and some of its recent activities to expand its influence and market share. Three things of note:

  • The partnerships that WeDoctor has developed with payers and providers, which are different to conventional transaction-based contracts
  • WeDoctor’s pragmatic approach to evolving technologies, which differentiates it from Western technology companies entering healthcare markets
  • WeDoctor might be considered as an exemplar and its strategy copied by Western companies. Because most giant Western technology companies are banned in China, local firms have stopped copying Western counterparts and innovate. This has resulted in many Chinese apps and services being better than their Western rivals. For example, Huawei’s mobiles outperform Apple’s, and China is ahead on 5G, mobile money and artificial intelligence. In 2016 the US technology publication Wired ran a cover story entitled: “It’s Time to Copy China”.
Smart Clinics

Imagine going to your primary care physician and, within a 15-minute consultation, receiving up to eleven tests, which include analysing your blood and urine, taking your blood pressure and measuring the electrical activity of your heart; and all the tests being delivered by a small portable all-in-one diagnostic device weighing just 5 kilos (11Ibs) and situated on the table of your doctor’s consulting room.

Imagine further that your test results are returned in minutes rather than days or even weeks and uploaded to your cloud-based electronic medical record to be reviewed in real time by your doctor. Simultaneously, your data are anonymously merged with similar information collected from millions of other patients and stored in a cloud file embedded with AI, in the forms of machine learning and cognitive computing, which complement and enhance the capabilities of your doctor. Your physician plays a key role in interpreting your test results and providing you with a diagnosis and treatment options as well as giving you an essential human touch of reassurance and guidance. Notwithstanding, as soon as you leave your doctor’s office, your mobile phone will suggest smart ways to monitor and manage your condition remotely. Information about your condition will appear on your social media feeds, you will also receive prompts for treatments, alerts about health supplements and suggestions about appropriate insurance policies. Currently, no amount of money can buy such a service in advanced wealthy Western economies, but it is a lead device of WeDoctor, which is available in rural China and in other emerging countries. According to Frost and Sullivan, a consultancy, the China market alone for remote diagnostics is currently estimated to be US$2bn and projected to grow to US$28bn in 10 years. WeDoctor’s  near-term goal is to capture a significant share of this market and help re-engineer China’s healthcare system by nudging individuals with the right piece of information at the time to maintain their health. This makes the device valuable to patients, healthcare providers and payers.
 
Reverse innovation
 
It seems reasonable to assume that, in addition to being useful in China and other emerging countries, WeDoctor’s all-in-one diagnostic device is well positioned to help enhance primary care practice in developed Western nations by a process of ‘reverse innovation’. This refers to a strategy where a product offering, which is specifically developed for emerging countries is subsequently successfully marketed in developed wealthy nations. It is particularly relevant to healthcare systems, which are universally challenged to deliver high quality outcomes with increasingly scarce resources. The strategy was formalized in a paper entitled, ‘How GE is Disrupting Itself’, which was published in the October 2009 edition of the Harvard Business Review (HBR), and subsequently expanded into a book published in 2018 entitled, ‘Reverse Innovation in Healthcare: How to make value-based delivery work’.
 
In the early 2000s, General Electric (GE) took an affordable, high quality portable ultrasound device, which it had developed for the Chinese market and successfully marketed it in the US and elsewhere. GE found that ‘affordability’ and ‘portability’ were universally valued healthcare factors. Jeffrey Immelt, then chairman and CEO of GE and one of the authors of the 2009 HBR paper, challenged other multinationals, “to see innovation opportunities in emerging markets in a new light”. Reverse innovation was more widespread than Immelt first thought and over the past decade the strategy has become a significant part in the armoury of many multinational corporations. Although the strategy is relevant for value-based healthcare,it is rarely practiced by Western healthcare providers.
 
The starting point for reverse innovation healthcare strategies is emerging markets where the rapid growth in the demand for quality healthcare outstrips the development of resources and infrastructure. This creates significant opportunities for Western companies with smart solutions to common healthcare challenges. Similar to GE’s portable ultrasound device, WeDoctor’s smart all-in-one diagnostic device, in time, could be marketed in developed regions of the world where healthcare systems are struggling to improve patient outcomes while reducing costs.
 
WeDoctor’s pragmatism

WeDoctor, founded by Liao Jieyuan an AI specialist, is backed by Tencent, which is one of the world’s largest technology and internet companies with a market cap of US$0.5trn and a mission to enhance the quality of life through the development and global distribution of emerging technologies. WeDoctor has a market cap of US$6bn, an established network in China of some 240,000 doctors, 2,700 large premier hospitals, over 15,000 pharmacies in 30 of China’s 34 provinces and about 160m platform users and joins a growing contingent of technology companies with a mission to change the healthcare industry, which to-date has resisted online disruption.
 
Notwithstanding, there is a significant difference between giant Western technology companies who have entered healthcare markets and WeDoctor. While the former have tended to invest heavily in aspirational projects such as unravelling the medical mysteries of anti-ageing, and AI systems to replace clinicians, WeDoctor has been more pragmatic and focused on making money by unclogging bottlenecks in the Chinese US$1trn healthcare market. Although Liao is an AI expert and WeDoctor is a significant user of AI, Liao believes, “AI won’t replace doctors, but will become an important tool for doctors to help improve their efficiency and accuracy”. WeDoctor has a practical mission: to enhance access to quality medical resources, improve patient outcomes and reduce costs. Indeed, Liao founded WeDoctor simply to help people book physician appointments, which is challenging in China. Chinese primary care practices are underused due to the poor distribution of resources, a lack of reputable practitioners and the nation’s relatively low number of doctors per capita. Further, waiting times to see a hospital specialist are long and patients reportedly have to pay significant amounts of money to middlemen to secure appointments.
 
AI healthcare systems are more challenged in the West than in China
 
In 2017, the Chinese central government released a plan to become the world leader in AI by 2030, aiming to surpass its rivals technologically and build a domestic industry worth almost $150 bn. WeDoctor and other Chinese healthcare providers are mindful that AI is a transformative technology for healthcare partly because of its ability to recognise patterns in vast amounts of data and to detect and quantify biomarkers in non-solid biological materials. Jamie Susskind, in his book Future Politics, published in 2018, suggests that doctors consulting both medical and legal big data banks in support of diagnoses and treatments, will become as commonplace as  consulting standard images such as MRIs or X-rays. And if such data banks are not consulted it will be considered negligent.  
 
WeDoctor’s AI systems hold out the prospect of delivering rapid diagnoses, efficient triage, enhanced monitoring of diseases, improvements in personalized care and making medicine safer. Notwithstanding, a limiting factor in the use of AI systems in healthcare generally is neither investment nor the technology, but the ability to amass vast amounts of reliable personal and genomic data. This is a bigger challenge in the West than in China. More robust privacy legislation, higher levels of security and broader-based ethical concerns in the West are substantial obstacles. A significant advantage of WeDoctor is the freedom in China to collect, store, analyse and use patient, personal and genomic data on an unparalleled scale. China has yet to establish laws to protect such personal information and is systematically building health profiles on its 1.4bn citizens, which, together with Beijing’s commitment to AI, will provide scientists in China a significant advantage to lead and dominate life sciences over the next decade.
WeDoctor is one of several similar start-ups
 
WeDoctor is just one of several recent Chinese online start-ups employing evolving technologies to improve China’s healthcare system. Another is Good Doctor, which is an offshoot of the Ping An Insurance Group, a financial giant with a US$181bn market cap, annual revenues of US$142b and 343,000 employees. Both start-ups compete to build smart clinics in rural China.
You might also like:

Can Western companies engage with and benefit from China?
WeDoctor endeavours to extend its franchise

In addition to its smart diagnostic device, WeDoctor has leveraged Tencent’s substantial expertise and resources in mobile, AI and cloud-based technology to develop a significant customer-focused retail prowess and is rapidly developing a range of services for healthcare providers and manufacturers of medical devices. This positions the company well to have a significant near-term impact on Asia’s healthcare systems. In 2018 alone, WeDoctor has strengthened and extended its franchise by entering into a number of partnerships with a range of healthcare stakeholders, which include insurance companies, specialist in the procurement and distribution of medical devises and also investment companies interested in improving the physical infrastructure of southeast Asian healthcare systems. We describe some of these partnerships, which enable WeDoctor to consolidate and expand its market position both in China and internationally and suggest that Western healthcare providers should be considering similar partnerships to help them make the product to service shift.
 
WeDoctor and the AIA insurance group

In May 2018, WeDoctor formed a strategic alliance with the AIA Group, which is the largest public listed pan-Asian life insurance group with customers in China and across the Asia-Pacific region. WeDoctor and AIA are aligned in their ambition to partner with consumers in China and across southeast Asia to provide innovative quality healthcare and wellness offerings and financial protection solutions. The partnership provides WeDoctor with preferred access to AIA’s customer base and thereby strengthens and enlarges its networks and strategies to deliver affordable, digitally-enabled personalised healthcare offerings. AIA becomes WeDoctor’s preferred provider of life and health insurance solutions and gains access to its 160m registered users. According to Liao the partnership, “leverages AIA’s long history and extensive operations across the Asia-Pacific region . . . and is crucial to meeting the diversified life and health insurance requirements of our growing user base as we look to anticipate users’ needs, through our platform’s expanding functionality and our mission to transform healthcare through technology. This partnership not only helps us to cement our position as the premier technology-enabled healthcare solutions platform in China but also supports us as we expand our international presence in the years to come”.  
 
WeDoctor and China’s IVF market

Also, in May 2018, WeDoctor made a strategic investment in Reproductive Healthcare,a new in-vitro fertilisation (IVF) group, which was formed by a merger between two of Hong Kong’s largest and most reputable IVF practices. This was WeDoctor’s first investment outside of Mainland China and represents a significant milestone for the implementation of its international strategy. The new company provides a comprehensive range of IVF services, which include intra-uterine insemination, frozen-thawed embryo transfer and egg freezing services for China and the Asian region. The new company’s established frozen embryo services benefit from findings of a paper published in the January 2018 edition of the New England Journal of Medicine, which suggest that pregnancy and live birth rates are similar among women who use fresh or frozen embryos.
 
WeDoctor and its expanded international IVF market
 
In August 2018 WeDoctor, entered into an agreement with the Mason Group and Aldworth Management to acquire an 89.9% stake in Genea, Australia's leading provider of integrated advanced assisted reproductive technology (ART) services. Headquartered in Sydney, Genea has over 400 employees and is a leading international fertility group with a 30-year track record and a significant presence in New Zealand and Thailand as well as Australia. The company offers a comprehensive range of ART services, including IVF, egg and embryo freezing, genetic testing, sperm banking, day surgeries and pathology. Genea has developed proprietary technologies, including culture media and embryo transfer catheters, which are used in more than 600 clinics across 60 countries and is the only ART platform, with both services and technology, in the industry worldwide. The agreement strengthens both WeDoctor’s international strategy and its ability to increase its share of China’s US$2bn and fast-growing IVF market. WeDoctor also is targeting a bigger share of the outbound Chinese IVF medical tourism market, which in 2017, grew approximately 40% year-over-year to approximately US$151m. According to Grand View Research, the global IVF market in 2017 was valued at about US$15bn and is expected to grow at a CAGR of around 10%.
 
WeDoctor is China's first smart medical supply chain solutions and procurement company
 
In July 2018, WeDoctor entered into a joint venture (JV) with IDS Medical Systems Group (idsMED Group), to form idsMED WeDoctor China Ltd. This is China's first smart medical supply chain solutions and procurement company and is positioned to transform China’s fragmented, multi-layered and relationship-driven medical device distribution systems.
 
idsMED is a leading Asian medical supply chain solutions company specialising in the distribution of medical devices and consumables, clinical education and hospital design and planning. It represents over 200 global MedTech companies and has extensive Asia Pacific distribution networks with access to over 10,000 healthcare institutions. The company has 1,600 employees, including 700 experienced field sales, product and clinical specialists and 300 professional bio-medical engineers providing installation and maintenance services.
 
The JV, owned 51% by WeDoctor and 49% by idsMED Group leverages the respective companies’ strengths, innovative resources and networks to procure medical devices and services centrally by connecting global manufacturers directly to China’s hospitals and healthcare providers. The JV will further enhance WeDoctor’s value proposition by managing and optimizing China’s entire medical supply chain, which until now has been fragmented, overly bureaucratic and complicated. In addition, idsMED WeDoctor will set up medical education and training academies throughout China to deliver and promote medical devices and clinical education as well as accredited medical training courses for doctors and nurses.
 
WeDoctor & Fullerton
 
In September 2018 WeDoctor entered into a strategic partnership with Fullerton Health a Singapore-headquartered healthcare service provider. The alliance is, “In line with WeDoctor’s international growth strategy and will extend our reach and facilitate our development in Asia,” said Jeff Chen, WeDoctor’s Chief Strategy Officer. The JV provides WeDoctor access to Fullerton Health’s 500 healthcare facilities and its network of over 8,000 healthcare providers across eight Asian pacific markets. Fullerton Health benefits from WeDoctor’s footprint in China and broadens its patients’ access to online healthcare consultations. In the near term, both companies aim to broaden their reach in the corporate healthcare service market by opening onsite medical centres for businesses across China. In addition, the partnership plans to create about 100 primary care and specialist outpatient facilities.
 
Takeaways

Healthcare has become digital and global and long ago, the geo-political axis of the world has moved East. To remain competitive, Western healthcare providers must increase their knowledge and understanding of initiatives in China and southeast Asia, be prepared to transform their strategies and business models and engage in partnerships with a range of healthcare stakeholders, complementary enterprises and start-ups in emerging nations.
 
Two of China’s largest healthcare challenges are the uneven distribution of its services and its vast and escalating costs. The nation has an underserved primary care sector and the most qualified and experienced doctors are concentrated in a few premier mega-city hospitals, which account for 8% of the total number of medical centres but handle 50% of the nation’s outpatient visits. These challenges are not unique to China but experienced by healthcare systems throughout the world.

WeDoctor is an exemplar of how such universal healthcare challenges might be improved by a combination of evolving smart technologies and strategic partnerships with a range of healthcare stakeholders. As MedTech companies continue to transform their business models to increase customer-centricity, the types of partners they need to engage will only expand. In a rapidly moving market, keeping abreast of these potential collaborators is critical.

Another takeaway is that WeDoctor does not use AI and big data technologies to resolve the mysteries of medicine, but to increase access to healthcare, improve diagnoses, enhance patient outcomes and lower costs. The company also is increasing the effectiveness and efficiency of healthcare providers by simplifying and centralizing procurement processes of medical devices and pharmaceuticals.
 
Once WeDoctor has helped to improve China’s healthcare infrastructure, the nation would have amassed the world’s largest personal, medical and genomic data base of its citizens. WeDoctor will then be well positioned to turn its formidable AI prowess to accelerating R&D in lifesciences, improving the accuracy of early diagnoses, enhancing the monitoring of devastating life-threatening diseases and improving personalized care.
 
WeDoctor is an exemplar for Western MedTech companies.
view in full page
7 years ago

Why Blockchain technology will not disrupt healthcare

HealthPad
Directory:
Health Policy
Tags:
big data
bitcoin
commentary
diagnostic strategies
electronic health records
electronic patients records
interoperability
patients data
personalised treatment strategy
  • Everyone connected with healthcare supports interoperability saying it improves care, reduces medical errors and lowers costs
  • But interoperability is a long way from reality and electronic patient records are only part of an answer
  • Could Blockchain a technology disrupting financial systems resolve interoperability in healthcare?
  • Blockchain is an open-source decentralized “accounting” platform that underpins crypto currencies
  • Blockchain does not require any central data hubs, which in healthcare have been shown to be easily breached
  • Blockchain technology creates a virtual digital ledger that could automatically record every interaction with patient data in a cryptographically verifiable manner
  • Some experts believe that Blockchain could improve diagnosis, enhance personalised therapies, and prevent highly prevalent devastating and costly diseases
  • Why aren’t healthcare leaders pursuing Blockchain with vigour?
 
Why Blockchain technology will not disrupt healthcare

Blockchain technology is disrupting financial systems by enhancing the reconciliation of global transactions and creating an immutable audit trail, which significantly enhances the ability to track information at lower costs, while protecting confidentiality. Could Blockchain do something similar for healthcare and resolve the challenges of interoperability by providing an inexpensive and enhanced means to immutably track, store, and protect a variety of patient data from multiple sources, while giving different levels of access to health professionals and the public?
 
Blockchain and crypto currencies

You might not have heard of Blockchain, but probably you have heard of bitcoin; an intangible or crypto currency, which was created in 2008 when a programmer called Satoshi Nakamoto (a pseudonym) described bitcoin’s design in a paper posted to a cryptography e-mail list. Then in early 2009 Nakamoto released Blockchain: an open source, global decentralized accounting ledger, which underpins bitcoin by executing and immutably recording transactions without the need of a middleman. Instead of a centrally managed database, copies of the cryptographic balance book are spread across a network and automatically updated as transactions take place. Bitcoin gave rise to other crypto-currencies. Crypto currencies only exist as transactions and balances recorded on a public ledger in the cloud, and verified by a distributed group of computers.
 
Broad support for interoperability
 
Just about everyone connected with healthcare - clinicians, providers, payers, patients and policy makers - support interoperability, suggesting data must flow rapidly, easily and flawlessly through healthcare ecosystems to reduce medical errors, improve diagnosis, enhance patient care, and lower costs. Despite such overwhelming support, interoperability is a long way from a reality. As a result, health providers spend too much time calling other providers about patient information, emailing images and records, and attempting to coordinate care efforts across disjointed and disconnected healthcare systems. This is a significant drain on valuable human resources, which could be more effectively spent with patients or used to remotely monitor patients’ conditions. Blockchain may provide a solution to challenges of interoperability in healthcare.
 
Electronic patient records do not resolve interoperability

A common misconception is that electronic patient records (EPR) resolve interoperability. They do not. EPRs were created to coordinate patient care inside healthcare settings by replacing paper records and filing cabinets. EPRs were not designed as open systems, which can easily collect, amalgamate and monitor a range of medical, genetic and personal information from multiple sources. To realize the full potential and promise of interoperability EPRs need to be easily accessible digitally, and in addition, have the capability to collect and manage remotely generated patient healthcare data as well as pharmacy and prescription information; family-health histories; genomic information and clinical-study data. To make this a reality existing data management conventions need to be significantly enhanced, and this is where Blockchain could help.

 

Blockchain will become a standard technology
 
Think of a bitcoin, or any other crypto currency, as a block capable of storing data. Each block can be subdivided countless times to create subsections. Thus, it is easy to see that a block may serve as a directory for a healthcare provider. Data recorded on a block can be public, but are encrypted and stored across a network. All data are immutable except for additions. Because of these and other capabilities, it seems reasonable to assume that Blockchain may become a standard technology over the next decade.
 
You might also be interested in:

The IoT and healthcare  
 
and

Future healthcare shock
Blockchain and healthcare

Because crypto currencies are unregulated and sometimes used for money laundering, they are perceived as “shadowy”. However, this should not be a reason for not considering Blockchain technology. 30 corporations, including J.P. Morgan and Microsoft, are uniting to develop decentralized computing networks based on Blockchain technology. Further crypto currencies are approaching the mainstream,  and within the financial sector, there is significant and growing interests in Blockchain technology to improve interoperability. Financial services and healthcare have similar interoperability challenges, but health providers appear reluctant to contemplate fundamental re-design of EPRs; despite the fact that there is a critical need for innovation as genomic data and personalized targeted therapies rise in significance and require advanced data management capabilities. Here are 2 brief examples, which describe how Blockchain is being used in financial services.
 
Blockchain’s use in financial services
 
In October 2017, the State Bank of India (SBI) announced its intention to implement Blockchain technology to improve the efficiency, transparency, security and confidentiality of its transactions while reducing costs. In November 2017, the SBI’s Blockchain partner, Primechain Technologies suggested that the key benefits of Blockchain for banks include, “Greatly improved security, reduced infrastructure cost, greater transparency, auditability and real-time automated settlements.”
 
Dubai, a global city in the United Arab Emirates, is preparing to introduce emCash as a crypto currency, and could become the world’s first Blockchain government by 2020. The changes Dubai is implementing eventually will lead to the end of traditional banking. Driving the transformation is Nasser Saidi, chief economists of the Dubai International Financial Centre, a former vice-governor of the Bank of Lebanon and a former economics and industry minister of that country. Saidi perceives the benefits of Blockchain to include the phasing out of costly traditional infrastructure services such as accounting and auditing.
 
Significant data challenges

Returning to healthcare, there are specific challenges facing interoperability, which include: (i) how to ensure patient records remain secure and are not lost or corrupted given that so many people are involved in the healthcare process for a single patient, and communication gaps and data-sharing issues are pervasive, and (ii) how can health providers effectively amalgamate and monitor genetic, clinical and personal data from a variety of sources, which are required to improve diagnosis, enhance treatments and reduce the burden of devastating and costly diseases. 
 
Vulnerability of patient data

Not only do EPRs fail to resolve these two basic challenges of interoperability they are vulnerable to cybercriminals. Recently there has been an epidemic of computer hackers stealing EPRs. In June 2016 a hacker claimed to have obtained more than 10m health records, and was alleged to be selling them on the dark web. Also in 2016 in the US there were hundreds of breaches involving millions of EPRs, which were reported to the Department of Health and Human Services. The hacking of 2 American health insurers alone, Anthem and Premera Blue Cross, affected some 90m EPRs.
 
In the UK, patient data and NHS England’s computers are no less secure. On 12 May 2017, a relatively unsophisticated ransomware called WannaCry, infected NHS computers and affected the health service’s ability to provide care to patients. In October 2017, the National Audit Office (NAO) published a report on the impact of WannaCry, which found that 19,500 medical appointments were cancelled, computers at 600 primary care offices were locked and five hospitals had to divert ambulances elsewhere. Amyas Morse, head of the NAO suggests that, “The NHS needs to get their act together to ensure the NHS is better protected against future attacks.”
 
Healthcare legacy systems
 
Despite the potential benefits of Blockchain to healthcare, providers have not worked out fully how to move on from their legacy systems and employ innovative digital technologies with sufficient vigour to effectively enhance the overall quality of care while reducing costs. Instead they tinker at the edges of technologies, and fail to learn from best practices in adjacent industries.  
 
“Doctors and the medical community are the biggest deterrent for change”
 
Devi Shetty, heart surgeon, founder, and Chairperson of Narayana Health articulates this failure: “Doctors and the medical community are the biggest deterrent for the penetration of innovative IT systems in healthcare to improve patient care . . . IT has penetrated every industry in the world with the exception of healthcare. The only IT in patient care is software built into medical devices, which doctors can’t stop. Elsewhere there is a dearth of innovative IT systems to enhance care,” see video. Notwithstanding, Shetty believes that, “The future of healthcare is not going to be an extension of the past. The next big thing in healthcare is not going to be a new drug, a new medical device or a new operation. It is going to be IT.”
 
 
Google, Blockchain and healthcare
 
Previous HealthPad Commentaries have suggested that the failure of healthcare providers to fully embrace innovative technologies, especially those associated with patient data, has created an opportunity for giant technology companies to enter the healthcare sector, which shall dis-intermediate healthcare professionals.

In May 2017, Google announced that its AI-powered subsidiary, DeepMind Health, intends to develop the “Verifiable Data Audit”, which uses Blockchain technology to create a digital ledger, which automatically records every interaction with patient data in a cryptographically verifiable manner. This is expected to significantly reduce medical errors since any change or access to the patient data is visible, and both healthcare providers and patients would be able to securely track personal health records in real-time.
 
Takeaways

Blockchain is a new innovative and powerful technology that could play a significant role in overcoming the challenges of interoperability in healthcare, which would significantly help to enhance the quality of care, improve diagnosis, reduce costs and prevent devastating diseases. However, even if Blockchain were the perfect technological solution, which enabled interoperability, change would not happen in the short term. As Max Planck said, “A new scientific innovation does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.” While we wait for those who control our healthcare systems to die, billions of people will continue to suffer from preventable lifetime diseases, healthcare costs will escalate, healthcare systems will go bankrupt, and productivity in the general economy will fall.
view in full page
7 years, 4 months ago

The IoT and healthcare

HealthPad
Directory:
Healthcare
Tags:
AI
Artificial Intelligence
big data
commentary
diagnostic strategies
healthcare apps
Internet of Things
IoT
preventative strategies
smartphone technology

  • Over the next decade the combination of big data, analytics and the Internet of Things (IoT) will radically change healthcare
  • The social media revolution has raised peoples’ awareness of lifestyles and healthcare
  • The rise of smart watches and fitness sensors combined with IOT and Artificial Intelligence (AI) paves the way for preventative medicine becoming a key driver in the management of straining healthcare services and spending
  • Big data, analytics and the IoT is positioned to accelerate change away from output-orientated healthcare systems to value-based outcome-orientated systems
  • Patients and payers are increasingly aware of the opportunities and demanding change
  • The slowness for MedTech companies to change creates opportunities for newcomers to penetrate and grab share of healthcare markets
  • Regulation and requirements to undergo significant clinical studies to become standard of care will slow consumer and patient access to services
  
The IoT and healthcare
 
The Internet of Things (IoT) is positioned to radically transform healthcare. There are powerful social, demographic, technological, and economic drivers of this change. We describe some of these, and suggest that, within the next 10 years, there will be hundreds of millions of networked medical devices sharing data and knowhow, and this will drive a significant shift away from traditional healthcare systems focused on outputs to value-based systems dedicated to prevention and improving outcomes while lowering costs.
 
The IoT and its potential impact on healthcare
 
The IoT, which Cisco refers to as “the Internet of Everything” and GE as the “Industrial Internet” is also referred to as “machine-to-machine” (M2M) technologies, and as “smart sensors”. Whatever term is used, the IoT is an ever-expanding universe of devices embedded with microchips, sensors, and wireless communications capabilities, which enable them to collect, store, send and receive data. These smart devices and the data they collect are interconnected via the Internet, which significantly expands their potential uses and value. The IoT enables connectivity from anywhere to anywhere at any time, and facilitates the accumulation of big data and artificial intelligence (AI) to either complement or replace the human decision-maker. Over the next decade, anything that can be connected to the Internet probably will be. The Internet provides an almost ubiquitous, high-speed network, and cloud-based analytics, which, in nanoseconds, can read, analyse and act upon terabytes of aggregated medical data. Smart distributed services are positioned to become a powerful tool for health providers by optimizing medical results, preventing mistakes, relieving overburdened health professionals, improving patient outcomes, and lowering costs.
 
Two approaches to a common healthcare challenge

Let us illustrate the shift in healthcare referred to above by considering two different approaches to a shared healthcare challenge: that of providing people with personalized advice about maintaining and improving their wellbeing in order to ward-off lifestyle related illnesses, such as type 2 diabetes (T2DM). This is important because T2DM is a devastating lifestyle induced condition, which affects millions, costs billions, and in most cases can be prevented by lifestyle changes.
 
Approach 1

One approach is the world’s first nationwide diabetes prevention program, Healthier You, which was launched by NHS England, Public Health England and Diabetes UK in 2016. It is aimed at the 11m people in England thought to have pre-diabetes, which is where blood sugar levels are higher than normal, but not high enough for a diagnosis of T2DM. About 5-10% of people with pre-diabetes progress to "full-blown" T2DM in any given year. Healthier You is expected to be fully operational by 2020. Each year thereafter the program is expected to recruit 100,000 people at risk of T2DM. Personal lifestyle coaches will periodically monitor the blood sugar levels of these, and make recommendations about their diets and lifestyles. This is expected to prevent or slow the people with pre-diabetes progressing to full-blown T2DM.
 
Approach 2

The second approach is GymKit and Chatbox. The former is a new feature Apple is expected to add to its watch in late 2017, and the latter is a mobile app developed by Equinox, a New York-based health club chain, for its members.

Gymkit will enable the Apple watch to have seamless connectivity to the overwhelming majority of different kinds of cardiovascular equipment used in most fitness centres. Currently, there are a variety of smartphone apps, which allow gym users to connect to cardiovascular machines, but these are at best patchy. Gymkit is different, and will automatically adjust a user’s personalized needs to any cardiovascular machine without the user having to press a button. Itwill then wirelessly collect a range of data - if on a treadmill: speed, duration, incline, etc., - and combine these data with the user’s heart rate, age, gender, weight and body type to make health-related calculations and recommendations, and wirelessly transmit these to the user.

Chatbox does something similar. Ituses artificial intelligence (AI) to simulate the human voice, which talks to new health club members, encourages them to set personal goals, and sends them messages when they fall short. Further, Chatbox has sensors, which track users while they are in the gym, and suggests ways of improving and extending their personalized workouts. A survey, undertaken by Equinox of its members across 88 of its facilities reported that Chatbox users visited the fitness centres 40% more often than those without the app. This is significant because people who fail to form a habit of physical exercise tend to drop lifestyle goals.

The 2 approaches compared

Healthier You is unlikely to have more than a modest impact on the UK’s diabetes burden because the format it has adopted is like filling a swimming pool with a teaspoon. It would take over 100 years to recruit and counsel the 11m people with pre-diabetes, especially while the prevalence levels of pre-diabetes and T2DM in the UK are increasing.  Successfully changing the diets and lifestyles of large numbers of people requires an understanding of 21st century technologies. Ubiquitous healthcare technologies such as smartphone apps and wearable’s that support lifestyles abound, and have leveraged people's enhanced awareness of themselves and their health. Hence peoples’ large and rapidly growing demands for such devices to track their weight, blood pressure, daily exercise, diet etc. From apps to wearables, healthcare technology lets people feel in control of their health, while potentially providing health professionals with more patient data than ever before.  

The IoT and consumers

There are more than 165,000 healthcare apps currently on the market, there is a rapid growth in wearables, and smartphone penetration in the US and UK has surpassed 80% and 75% respectively. According to a 2017 US survey by Anthem Blue Cross, 70m people in the US use wearable health monitoring devices, 52% of smartphone users gather health information using mobile apps, and 93% of doctors believe mobile apps can improve health. 86% of doctors say wearables increase patient engagement with their own health, and 88% of doctors want patients to monitor their health. 51% of doctors use electronic access to clinical information from other doctors, and 91% of hospitals in the US have moved to electronic patient records (EPR).
 
Notwithstanding, these apps and wearables are rarely configured to aggregate, export and share the data they collect in order to improve outcomes and lower costs. This reduces their utility and value. However, the large and rapid growth of this market on the back of the social media revolution, and the impact it is having on shaping the attitudes and expectations of millions of consumers of healthcare, positions it well as a potential driver of significant change.

 A “minuscule fraction” of what is ultimately possible

According to Roger Kornberg, Professor of Structural Biology at Stanford University, the current capabilities of smart sensors like those used in Apple’sGymKit and Equinox’s Chatbox, “is only a minuscule fraction of what is ultimately possible . . . A sensor attached to a smartphone will enable it to answer any question that we may have about ourselves, and our environment,” says Kornberg. Smart sensors can provide you with a doctor in your pocket, which can be connected to a plethora of other devices that could collect, store, analyze and feedback terabytes of medical information in real time. Kornberg, who won the 2006 Nobel Prize for Chemistry, is excited about the disruptive effect, which smart sensors are having on traditional healthcare systems. This is because they can be connected to almost any medical device and human organ to, “monitor specimens . . . record in real time the health status of individuals,  . . . transmitelectronic signals wirelessly,  . . .  (and) provide responses to any treatment,” says Kornberg. 

Kornberg is engaged in developing sensors with the ability to detect and measure biological signals and data from humans, which can be wirelessly linked to smartphones to transmit the information for analysis, storage and further communication. Kornberg is convinced that, in the near term, we will be able to create a simple and affordable networked device that will, “detectan impending heart attack, in a precise and quantitative manner, before any symptoms”.
 


Potential of sensor technology



The excitement in the development of biosensors

 
Drivers of the IoT and market trends

Partly driving the IoT in healthcare and other industries are the: (i) general availability of affordable broadband Internet, (ii) almost ubiquitous smartphone penetration, (iii) increases in computer processing power, (iv) enhanced networking capabilities, (v) miniaturization, especially of computer chips and cameras, (vi) the digitalization of data, (vii) growth of big data repositories, and (viii) advances in AI and data mining.
 
Market trends suggest substantial growth in the total number of networked smart devices in use. By 2020, when the world’s population is expected to reach 7.6bn, it is projected that there will be between 19 and 50bn IoT-connected devices worldwide, more than 8bn broadband access points, more than 4m IoT jobs, and the number of installed IoT technologies will exceed that of personal computers by a factor of 10.
 
Crisis in primary care is a significant driver of change
 
In addition to these technological drivers, the simultaneous population aging and the shrinking pool of doctors also drives the IoT in healthcare. Increasing numbers of older people presenting with complex comorbidities significantly increases the large and rapidly growing demands on an over-stretched, shrinking population of doctors. This results in a crisis of care.
 
A 2015 Report from the Association of American Medical Colleges (AAMC) suggests that there is an 11 to 17% growth in total healthcare demand, of which a growing and aging population is a significant component. Further, the Report suggests that the US could lose 100,000 doctors by 2025, and that primary care physicians will account for 33% of that shortage.

There is a similar crisis in the UK, where trainee GPs are dwindling, young GPs are moving abroad, and experienced GPs are retiring early. According to data from the UK’s General Medical Council (GMC), between 2008 and 2014 an average of nearly 3,000 certificates were issued annually to enable British doctors to work abroad. Currently, there are hundreds of vacancies for GP trainees. Findings from a 2015 British Medical Association (BMA) poll of over 15,000 GPs, found that 34% of respondents plan to retire by 2020 because of high stress levels, unmanageable workloads, and too little time with patients.
 
Interestingly, Brexit is expected to compound the crisis of care in the UK. According to a 2017 General Medical Council survey of more than 2,000 doctors from the EU working in the UK, 60% said they were considering leaving the UK, and, of those, 91% said the UK’s decision to leave the EU was a factor in their considerations. 
 
Changing healthcare ecosystems

These trends help healthcare payers to employ IoT strategies in an attempt to replace traditional healthcare systems, which act when illnesses occur and report services rendered, with value-based healthcare systems focused on outcomes. US payers are leading this transformation. Some payers in the US have employed IoT strategies to convert a number of devices used in various therapeutic pathways into smart devices that collect, aggregate and process terabytes of healthcare data gathered from thousands of healthcare providers, and electronic patient records (EPRs) describing millions of treatments doctors have prescribed to people presenting similar symptoms and disease states. Cognitive computing systems analyse these data and instantaneously identify patterns that doctors cannot. Such systems, although proprietary, are positioned to help reduce the ongoing challenges of inaccurate, late, and delayed diagnoses, which each year cost the US economy some US$750bn and lead to between 40,000 and 80,000 patient deaths.
 
IBM Watson
 
IBM’s supercomputer, Watson is a well-known proprietary system that uses IoT strategies that include a network of smart sensors and databases to assist doctors in various aspects of diagnoses and treatment plans tailored to patients’ individual symptoms, genetics, and medical histories. Watson draws from 600,000 medical evidence reports, 1.5m EPRs, millions of clinical trials, and 2m pages of text from medical journals. A variant, IBM Watson for Oncology, has been designed specifically to help oncologists, and is currently in use at the Memorial Sloan-Kettering Cancer Center in New York. Also, it is being used in India where there is a shortage of oncologists. The Manipal Hospital Group, India’s third largest healthcare group, which manages about 5,000 beds, and provides comprehensive care to around 2m patients every year, is using Watson for Oncology to support diagnosis and treatment for more than 200,000 cancer patients each year across 16 of its hospitals.
 
In 2016 IBM, made a US$3bn investment designed to increase the alignment of its Watson super cognitive computing with the IoT, and allocated more than US$200m to its global Watson IoT headquarters in Munich. IBM will have over 1,000 Munich-based researchers, engineers, developers and business experts working closely with specific industries, including healthcare, to draw insights from billions of sensors embedded in medical devices, hospital beds, health clinics, wearables and apps in endeavors to develop IoT healthcare solutions.
 
Babylon
 
Using a similar IoT network of smart sensors and databases, Babylon, a UK-based subscription health service start-up, has launched a digital healthcare AI-based app, which offers patients video and text-based consultations with doctors, and is designed to improve medical diagnoses and treatments. Early in 2017, NHS England started a 6-month study to test the app’s efficacy by making it available to 1.2m London residents. The Babylon app is expected to be able to analyse, “hundreds of millions of combinations of symptoms” in real time, while taking into account individualized information of a patient’s genetics, environment, behavior, and biology. Current regulations do not allow the Babylon app to make formal diagnoses, so it is employed to assist doctors by recommending diagnoses and treatment options. Notwithstanding, Ali Parsa, Babylon’s founder and CEO says, "Our scientists have little doubt that our AI will soon diagnose and predict personal health better than doctors”.
 
Market forecasts

Market studies stress the vast and growing economic impact of the IoT on healthcare. Business Insider Intelligence (BII) suggested that the IoT has created nearly US$100bn additional revenue in medical devices alone. It forecasts that cost savings and productivity gains generated through the IoT and subsequent changes will create between US$1.1 and US$2.5trillion in value in the healthcare sector by 2025. In 2016, Grand View Research Inc. projected that the global IoT healthcare market will reach nearly US$410bn by 2022. A 2013 Report from the McKinsey Global Institute on Disruptive Technologies, suggests that the potential total economic impact of IoT will be between US$3 and US$6trillion per year by 2025, the largest of which will be felt in healthcare and manufacturing sectors. Although forecasts differ, there is general agreement that, over the next decade, the IoT is projected to provide substantial economic and healthcare benefits in the way of cost savings, improved outcomes, and efficiency improvements.
  
IoT and MedTech companies

We have briefly described the impact of the IoT on patients, healthcare payers and providers. But what about MedTech companies? They have the capabilities and knowhow to develop and integrate the IoT into their next generation devices. However, MedTech innovations tend to be small improvements to existing product offerings. Data, accumulated from numerous smart medical devices, are enhanced in value once they are merged, aggregated, analyzed and communicated. And herein lies the challenge of data security. Arguably the greater the connectivity between medical devices, the greater the security threat. In 2013 the FDA issued a safety communication regarding cyber security for medical devices and health providers, and recommended that MedTech companies determine appropriate safeguards to reduce the risk of device failure due to cyber-attacks. The cautious modus vivendi of most MedTech companies suggests that, in the near term, a significant proportion will not develop IoT strategies, and this creates a gap in the market.
 
The IoT and new and rising healthcare players

Taking advantage of this market gap is a relatively small group of data-orientated companies, which have started to employ IoT technologies to gain access to healthcare markets by developing specific product offerings, increasing collaborative R&D, and acquiring new data oriented start-ups. For instance, in addition to IBM and Apple mentioned above, Amazon is expected to enter the global pharmaceutical market, which is anticipated to reach over US$1 trillion by 2022. Microsoft has used IoT strategies to build its Microsoft Azure cloud platform to facilitate cloud-based delivery of multiple healthcare services. Google Genomics is using IoT strategies to assist the life science community organise the world’s genomic data and make it accessible by applying the same technologies that power Google Search to securely store petabytes of genomic information, which can be analysed, and shared by life science researchers throughout the world.

Takeaways
 
The powerful social, demographic, technological and economic drivers of healthcare change over the next decade suggest an increasing influence of IoT technologies in a sector not known for radical or innovative change. Research suggests that hundreds of millions of networked medical devices will proliferate globally within the next decade. The potential healthcare benefits to be derived from these are expected to be significant, especially through enhancing preventative and outcome-oriented healthcare while reducing costs. This has to be achieved in a highly regulated environment where concerns of data security are paramount. To reap the potential benefits of the IoT in healthcare, policymakers will have to reconcile the need for IoT regulation with the significant projected benefits of the IoT. Smart technologies require smart management and smart regulation.
 
view in full page
8 years, 1 month ago

Future healthcare shock

HealthPad
Directory:
Health Policy
Tags:
big data
chronic disease
commentary
genomics
healthcare costs
healthcare data
human genome
medical technology
  • Healthcare systems throughout the world are in constant crisis
  • Attempts to introduce digital infrastructure to improve the quality of care, efficiency, and patient outcomes have failed
  • Modern healthcare systems were built on the idea that doctors provide healthcare with meaning and power, but this is changing
  • Advances in genetics and molecular science are rapidly eating away at doctors’ discretion and power
  • People are loosing their free will and increasingly being driven by big data strategies
  • An important new book suggests that a biotech-savvy elite will edit people's genomes and control health and healthcare with powerful algorithms, and that people will merge with computers
  • Homo sapiens will evolve into Homo Deus
 
Future healthcare shock
 
This book should be compulsory reading for everyone interested in health and healthcare, especially those grappling with strategic challenges. Homo Deus: A brief history of tomorrow, by Yuval Harari, a world bestselling author, published in 2016 is not for tacticians responding to their in-trays, but for healthcare strategists planning for the future.

The book is published a year after an OECD report concluded that NHS England is one of the worst healthcare systems in the developed world; hospitals are so short-staffed and under-equipped that people are dying needlessly. The quality of care across key health areas is “poor to mediocre”, obesity levels are “dire”, and the NHS struggles to get even the “basics” right. The UK came 21st out of 23 countries on cervical cancer survival, 20th on breast and bowel cancer survival and 19th on stroke.

Harari pulls together history, philosophy, theology, computer science and biology to produce an important and thought provoking thesis, which has significant implications for the future of health and healthcare. Homo Deus, more than the 2015 OECD Report,  will make you think.
 
Healthcare’s legacy systems an obstacle for change

While a large and growing universe of consumers regularly use smartphones, cloud computing, and global connectivity to provide them with efficient, high quality, 24-hour banking, education, entertainment, shopping, and dating, healthcare systems have failed to introduce digital support strategies to enhance the quality of care, increase efficiency, and improve patient outcomes.

Why?

The answer is partly due to entrenched legacy systems, and partly because digital support infrastructure is typically beyond the core mission of most healthcare systems. Devi Shetty, cardiac surgeon, founder and CEO of Narayana Health, and philanthropist, laments how digital technologies have, “penetrated every industry in the world except healthcare”, and suggests doctors and the medical community are the biggest obstaclesto change.
 
 
Doctors’ traditional raison d'être is being replaced by algorithms

Notwithstanding, modern medicine has conquered killer infectious diseases, and has successfully transformed them, “from an incomprehensible force of nature into a manageable challenge . . . For the first time in history, more people die today from old age than from infectious diseases,” says Harari.
 
Further, modern healthcare systems were built on the assumption that individual doctors provided healthcare systems with meaning and power. Doctors are free to use their superior knowledge and experience to diagnose and treat patients; their decisions can mean life or death. This endowed doctors and healthcare systems with their monopoly of power and their raison d'être. But such power and influence is receding, and rapidly being replaced by biotechnology and algorithms.
 
Healthcare systems in crisis

This radical change adds to the crisis of healthcare systems, which lack cash, and have a shrinking pool of doctors treating a large and growing number of patients, an increasing proportion of whom are presenting with complicated co-morbidities. Aging equipment in healthcare systems is neither being replaced nor updated, and additionally, there is a dearth of digital infrastructure to support patient care.
  
A symptom of this crisis is the large and increasing rates of misdiagnosis: 15% of all medical cases in developed countries are misdiagnosed, and according to The Journal of Clinical Oncology, a staggering 44% of some types of cancers are misdiagnosed, resulting in millions of people suffering unnecessarily, thousands dying needlessly, and billions of dollars being wasted. Doing more of the same will not dent this crisis.
 
Computers replacing doctors
 
As the demand for healthcare increases, healthcare costs escalate, and the supply of doctor’s decrease, so big data strategies and complex algorithms, which in seconds are capable of analysing and transforming terabytes of electronic healthcare data into clinically relevant medical opinions, are being introduced.
 
Such digital infrastructure erodes the status of doctors who no longer are expected solely to rely on their individual knowledge and experience to diagnose and treat patients. Today, doctors have access to powerful cognitive computing systems that understand, reason, learn, and do more than we ever thought possible. Such computers provide doctors almost instantaneous clinical recommendations deduced from the collective knowledge gathered from thousands of healthcare systems, billions of patient records, and millions of treatments other doctors have prescribed to people presenting similar symptoms and disease states. Unlike doctors, these computers never wear out, and can work 24-7, 365 days a year.
 
The train has left the station

One example is IBM’s Watson, which is able to read 40 million medical documents in 15 seconds, understand complex medical questions, and identify and present evidence based solutions and treatment options. Despite the resistance of doctors and the medical establishment the substitution of biotechnology and algorithms for doctors is occurring in healthcare systems throughout the world, and cannot be stopped. “The train is again pulling out of the station . . . . Those who miss it will never get a second chance”. For healthcare systems to survive and prosper in the 21st century is to understand and embrace “the powers of biotechnology and algorithms”. People and organizations that fail to do this will not survive, says Harari.
 
The impact of evolutionary science on healthcare systems

Roger Kornberg, Professor of Medicine at Stanford University who won the 2006 Nobel Prize in chemistry, "for his studies of the molecular basis of eukaryotic transcription", describes how human genome sequencing and genomics have fundamentally changed the way healthcare is organized and delivered. “Genomic sequencing enables us to identify every component of the body responsible for all life processes. In particular, it enables the identification of components, which are either defective or whose activity we may wish to edit in order to improve a medical condition,” says Kornberg.



 
The new world of ‘dataism’

Harari’s “new world” describes some of the implications of Kornberg’s discoveries, and suggests that evolutionary science is rapidly eroding doctors’ discretion and freewill, which are the foundation stones of modern healthcare systems and central to a doctors’ modus vivendi. Because evolutionary science has been programmed by millennia of development, our actions tend to be either predetermined or random. This results in the uncoupling of intelligence from consciousness and the “new world” as data-driven transformation, which Harari suggests is just beginning, and there is little chance of stopping it.
 
Over the past 50 years scientific successes have built complex networks that increasingly treat human beings as units of information, rather than individuals with free will. We have built big-data processing networks, which know our feelings better than we know them ourselves. Evolutionary science teaches us that, in one sense, we do not have the degree of free will we once thought. In fact, we are better understood as data-processing machines: algorithms. By manipulating data, scientists such as Kornberg, have demonstrated that we can exercise mastery over creation and destruction. The challenge is that other algorithms we have built and embedded in big data networks owned by organizations can manipulate data far more efficiently than we can as individuals. This is what Harari means by the “uncoupling” of intelligence and consciousness.
 
We are giving away our most valuable assets for nothing

Harari is not a technological determinist: he describes possibilities rather than make predictions. His thesis suggests that because of the dearth of leadership in the modern world, and the fact that our individual free-will is being replaced by data processors, we become dough for the Silicon Valley “Gods” to shape.
 
Just as African chiefs in the 19th Century gave away vast swathes of valuable land, rich in minerals, to imperialist businessmen such as Cecil Rhodes, for a handful of beads; so today, we are giving away our most valuable possessions  - vast amounts of personal data - to the new “Gods” of Silicon Valley: Amazon, Facebook, and Google for free. Amazon uses these data to tell us what books we like, and Facebook and Google use them to tell us which partner is best suited for us. Increasingly, big-data and powerful computers, rather than the individual opinion of doctors, drive the most important decisions we take about our health and wellbeing. Healthcare systems will cede jobs and decisions to machines and algorithms, says Harari.
 
Takeaways

For the time being, because of the entrenched legacy systems, health providers will continue to pay homage to our individuality and unique needs. However, in order to treat people effectively healthcare systems will need to “break us up into biochemical subsystems”, and permanently monitor each subgroup with powerful algorithms. Healthcare systems that do not understand and embrace this new world will perish. Only a relatively few early adopters will reap the rewards of the new technologies. The new elite will commandeer evolution with ‘intelligent’ design, edit peoples’ genomes, and eventually merge individuals with machines. Thus, according to Harari, a new elite caste of Homo sapiens will evolve into Homo Deus. In this brave new world, only the new “Gods”, with access to the ultimate source of health and wellbeing will survive, while the rest of mankind will be left behind.

Harari does not believe this new health world is inevitable, but implies that, in the absence of effective leadership, it is most likely to happen.
 
 
view in full page
8 years, 8 months ago

The Future of Healthcare

HealthPad
Directory:
Health Policy
Tags:
3D printing
artificial intelligence
big data
cancer genomics
commentary
communication technology
healthcare unplugged
human genome project
virtual reality
 

The Future of Healthcare
 
Fahad Aziz
Co-founder of Caremerge, which provides comprehensive web and mobile communications and care-coordination solutions for senior living communities. Fahad is the author of several technical papers, and the recipient of Pakistan’s prestigious Performance Excellence Award.
 
  • How will machine learning, virtual reality, the Human Genome Project, and the Internet of things change healthcare?
  • Will technology result in a healthier future full of empowered patients?
  • Will big data strategies help physicians perform their jobs better?
  • Will 3D printing be used to replace tissue and organs?
  • Will VR allow scientists to experience physical and psychological challenges rather than observe them?

 
Living in Silicon Valley I have a front row seat to the in technology poised to reshape the future of humanity. Machine learning, Virtual Reality, the Human Genome Project and the Internet of things will undoubtedly impact our lives in general, but they can also have a major impact on the Healthcare industry in particular.

To visualize the future of healthcare, I took a look at what’s trending in Silicon Valley and applied them to the healthcare industry. If the possibilities seem farfetched today, remember the iPhone is less than a decade old and has spawned countless industries that have shaped our daily existence, and will continue to do so. Technology moves fast and these four trends can potentially disrupt all aspects healthcare.

Machine learning
Artificial Intelligence (AI) is not new to the technology world, but with machine learning, AI has taken on an open-ended form rife with endless opportunities for technology in general and healthcare in particular.

Machine learning enables computers to identify patterns and observe behaviors based on empirical data, and use all that to ‘learn’. In other words, machine learning is a set of self-learning algorithms that can eventually become smarter than any human being on this planet.

In 2012, Vinod Khosla, an American businessman and a co-founder of Sun Microsytems, predicted that in time, “Technology will replace 80% of what doctors do”; sparking outrage and umbrage within the healthcare industry. Physicians overlooked what Khosla was really saying: that big data, properly harnessed and utilized, had the potential to help physicians perform their jobs better. Farfetched at the time, big data and machine learning have come far enough in just four years to provide levity to Khasla’s argument.

When given access to a trillion gigabytes of patient data collected from devices, electronic health records (EHRs), laboratories, and DNA sequencing - alongside surrounding factors such as weather, geo-location, and viral outbursts - computers learn quickly, and they learn everything. The depth of information provided at such a scale suggests patients will not need to consult with various specialities to figure out what’s ailing them in the future. Instead, consolidated data will create and provide a fully coordinated treatment plan.

If you are thinking this sounds crazy, consider the fact that IBM acquired Truven Health for $2.6 Billion in early 2016. Truven delivers information, analytic tools, research, and services to the healthcare industry, and gives IBM access to data of some 200 million patients to feed Watson, which is IBM’s machine learning product that is a powerful question answering computer system capable of answering questions posed by natural language.

I can only imagine what Watson will offer after digesting this massive data, but one thing is for sure: the result is nothing but good news for patients and their care plans.

The Internet of things
Gartner, a US IT research and advisory firm, estimates six billion devices will be “connected” by 2020; collecting data for consumption, analytics and a whole lot more.

Healthcare has historically been a sucker for devices, embracing hardware that captures data, provides diagnostics and even treats patients. Previously, these devices have been in use only at hospitals and other healthcare locations, but in the future this technology has the potential to become a part of every single home; marking a new era in care.


How can the NHS innovate? - Mike Farrar, former NHS Confederation CEO

In the future, doctor’s visits will begin before we even head out the door. Our vitals will be captured at home and sent to our doctor. In some cases, we may even receive treatment in the comfort of our home. Further, once treatment begins, a real-time feed of our vitals and conditions will be shared and analyzed automatically via set protocols, which will trigger alerts if our health declines and requires a change in treatment.
 
The Internet of things has implications elsewhere for the healthcare industry. Pharmaceutical research could bid farewell to clinical trials once they can access millions of patients’ data to accurately analyze behaviors and outcomes.

Challenges facing immunizations could also be solved using simple, digitized solutions. Currently, vaccinations are rendered ineffective by temperature changes during their transport; a simple tracking device with a thermometer could solve that problem. Similar challenges with manufacturing, delivery and tracking of vaccination can also be digitized to make the immunization programs successful globally.

Last but not least, I foresee nano devices embedded within the human body to monitor glucose, blood pressure, temperature, and more; to allow for swifter, more effective decisions to be made so treatments can begin as soon as needed, significantly increasing positive outcomes.

The Human Genome Project
One of the greatest breakthroughs in healthcare this last decade was decoding the human genome to understand the DNA sequencing. It took over 10 years and a staggering US$2.7bn to crack the code of one human being. Just a decade later, it takes US$1,500 and a couple of hours to run the genome for any person.

The more we learn about DNA and its sequencing, the more accurately we can treat patients for their illnesses. There will be no guesswork involved, instead, a complete technical report will show exactly what went wrong since last time, and what can be done to fix it.

The future is closer than we think. I suspect human genome machines will be deployed at healthcare locations in the near term. The appetite for this type of information will grow, and eventually, we may live in an age where small genome devices are installed under your sink or inside your toilet seat to analyze changes in your DNA sequencing several times a day.

Today, researchers in Europe are using 3D printers and DNA sequencing to create human body parts that can potentially replace limbs or ailing organs. Prototypes already exist. DNA sequencing will help people take more control over their bodies, allowing them to make better informed decisions about their lifestyle, illnesses and treatments. This means that doctors’ roles will change, potentially allowing for a complete shift in the healthcare paradigm.

Virtual reality in healthcare
Mark Zuckerberg, chairman, CEO and co-founder of Facebook, takes every opportunity he can to promote his latest US$2bn acquisition, Oculus VR, an American virtual reality company, whose product, Oculus Rift, is a virtual reality (VR) headset. I had the opportunity to try Oculus Rift, and was blown away. Market analysts say Zuckerberg was crazy to bet on this, but I know he has discovered a platform with the potential to be larger than Facebook.

Virtual reality transports you into another world by creating an artificial environment, deceiving your sense of sight and touch, so your mind believes you are part of that environment. At a recent Aging2.0 conference, I watched a man in his 30s struggle to walk while wearing an Oculus Rift headset. A moment after putting it on he experienced the physical shortcomings of someone in there 80s. These types of experiences open up a new world for researchers by providing them with the ability to directly experience physical and psychological challenges rather than rely on observations.


Doctors' resistance to change - Devi Shetty,  founder of Narayana Hrudayala, Bangalore, India

The environment created by VR is artificial and programmed, at least for now. But fast forward three to four years, and you will likely be in a real environment. Consider this: a doctor could be transported to a hospital in Kenya while sitting in the relative comfort of his clinic in San Francisco. VR would allow the user to move around and interact with people enabling participation in treatments, research or even surgery.

I suspect Zuckerberg will combine social networking and virtual reality, allowing people from any part of the world to meet up with one another, to visit places they have previously only dreamed of, and go on adventures their body would never allow in the real world.

In healthcare, innovators are already leveraging VR for treating post-traumatic stress disorder (PTSD), autism, social cognition, meditation, and help with exposure therapy and surgical training. And this is just the beginning.
 
Takeaways
The day is fast approaching when I will be able to virtually go to hospital to meet with doctors and specialists, share my vitals through various devices and a video camera to gain assessment and treatment plans from the comfort of my own home.

Healthcare information and management systems (HIMSS) have never disappointed me in terms of their participation and size, and I am hopeful that innovations will continue to shock, whispering promises of a healthier future full of empowered patients.
 
view in full page
load more Loading..