Transitioning from a surge of post-pandemic investment, the MedTech industry continues to grow with an increasing focus on wearables and robotics. However, there is a sea change on the horizon. Investment may have receded from the record breaking numbers observed in the wake of COVID-19, but job growth has not shown signs of letting up. Total revenue for MedTech reached $573 billion in 2022, though growth fell 16% from a post-pandemic high in 2021 to just 3.5% in 2022, the lowest growth data since 2015.
While the lagging trend has been cause for some potential consternation among equity investors cooling the overall marketplace, the MedTech space has exploded over the past decade with annual revenue doubling since 2013 among commercial leaders in the United States and European Union.
Smart Connectivity: Wearables and AI
The rise of these new technologies in the MedTech industry is widely reported, with big data, artificial intelligence (AI), cloud computing, sensors, virtual and extended reality systems, and fifth-generation broadband all recognized as future drivers for the industry. Amid a generally slow year, the pace of innovation among these cutting-edge technologies continued to accelerate. One example of this growth was in the applications of AI with 91 new algorithms approved by the FDA in the first 10 months of 2022, making an immediate impact in the diagnostics and imaging diagnostics markets.
The use of AI-based technology is expected to increase the AI healthcare market size from $10.4 billion in 2021 to $120.2 billion in 2028, a compound annual growth rate (CAGR) of 36.4% from 2024 to 2030.
Specifically, there have been great advances in the integration of sensors and AI as medical devices will be increasingly connected, generating real-time data that can be analyzed by AI to personalize treatments, predict health outcomes, and even prevent disease. According to a 2021 McKinsey report, the medical device industry generates $329 billion annually in North America, making it one of the most profitable industries domestically with exponential room for growth.
One such device has arrived in the form of a baby sleeping monitor. Owlet’s Dream Sock is the first-of-its-kind FDA-cleared smart baby monitor to offer Live Health Readings and Health Notifications for use with healthy infants between 1-18 months, 6-30 lbs. Intended to assist parents and caregivers in tracking a child’s well-being, the Dream Sock monitors sleep patterns, quality and duration of sleep. When enabled in-home for healthy infants only, Dream Sock displays pulse rate (PR) and oxygen saturation (SpO2) values and provides a notification in the rare instance that the values move outside of a preset zone. Coupled with its Dream Camera, the device offers HD quality video and audio. It’s currently being marketed as the ultimate device for newborn parents’ peace of mind.
Furthermore, the Dream Sock advertises not only as a health monitoring device for infants but a methodology to reduce postpartum distress and insomnia, qualifying its results with success stories from parents who advocate for its reduction in stress levels, especially among first time parents.
A recent BDO survey found that 72% of medical device and MedTech companies plan to invest in wearables, compared to 52% that expect to fund robotic projects, a notable shift in investment. Another report by Market.us looks even further out to forecast that the wearable diagnostic and monitoring devices market will reach $165 billion by 2032, commanding the greatest share of the broader wearables market that includes fitness and wellness trackers.
One of the most successful monitoring devices on the market, which has demonstrated life-altering health benefits for type 1 diabetes patients as well as financial success for its investors, has come in the form of continuous glucose monitoring (CGM) via Dexcom Inc. Offering patients up-to-the minute real time data pertaining to their glucose levels as well as the digital adherence tracking for primary care physicians and endocrinologists, Dexcom has unequivocally transformed the diabetes treatment landscape.
As a result, the company expects sales of $4.25 billion at the midpoint. The company got a boost when it reported earnings Oct. 27, 2023. For the third quarter ending only three days later, sales grew 27% to $975 million.
How some MedTech companies scale up and separate from the crowd
Scaling too soon or too fast can kill a growing business. About 74% of failures can be explained by premature scaling, according to a survey by Startup Genome, which is exactly opposite of what so many founders and investors believe. However, by the time MedTech startups have put their business models in place, they will likely have begun penetrating a few key target markets. To adapt to changing preferences among HCPs and nonclinical stakeholders, MedTech companies are using a broader set of omnichannel approach, including the following:
- Digital marketing. Eighty percent of medtech companies shifted some of their marketing expenditures (more than 20%, in most cases) to digital channels in 2020.
- Inside sales. Sixty-four percent of MedTech companies are launching or growing their “inside sales” capabilities, often in the form of ABM – account based marketing.
- Portals and e-commerce. Two-thirds of MedTech companies expect online channels to account for more than 20% of their revenue by 2025.
- Hybrid sales rep interactions. Most medtech companies are equipping their reps with virtual-communication tools and digital content to train them in remote selling.
However, MedTech companies have yet to reinvent the way they engage with stakeholders to provide a seamless experience across digital, remote, and in-person channels; in fact, 77 percent of companies report experiencing channel conflict. Developing and employing an omnichannel engagement model calls for close collaboration among different functions and a rapid progression from ideas that are quickly tested and refined.
Successful companies set up cross-functional squads to deliver the building blocks of the new engagement journeys with members drawn from sales, marketing, service, analytics, IT, and design groups (DevOps, Product Dev, RevOps, and Sales force teams). Any agile omnichannel transformation revolves around these interconnected squads: they foster, test, and institutionalize innovation; build organizational capabilities; deliver targeted coaching; kick off change management; identify barriers to change; and help shape the scale-up of processes and key performance indicators.
The proliferation of wearables + AI in MedTech
Wearables may be currently leading the MedTech industry, but AI will play a pivotal role in the future of digital telemedicine, chat development, and many other innovative leaps, like the use of blockchain in healthcare. Studies show that administrative burdens are directly linked to rising rates of physician burnout. Clinicians face those same administrative burdens during virtual care visits. By 2025, the U.S. Department of Health and Human Services predicts that there will be a nationwide shortage of 90,000 physicians worsened by professional burnout related to the demands of electronic paperwork.
Services such as Teladoc, an online application synced with your medical records and a host of physicians, are ramping up investment in AI to infuse innovation into its telehealth solution for hospitals. Traditionally, Teladoc sold integrated care packages to companies and organizations with the goal of becoming their “whole person” service provider. So, at Teladoc, patients can find primary care, specialists, management for chronic conditions, and mental health services.
Recently, Teladoc expanded its partnership with Microsoft’s Azure OpenAI, tapping into its two-year partnership with the tech giant to integrate AI and ambient clinical documentation technologies into its Solo virtual care platform.
In effect, the company will use the tech giant’s artificial intelligence services to automate clinical documentation across the telehealth platform, saving physicians’ time and saving money in addition to resources on the margins. Teladoc states that it uses about 60 of its own AI models for various tasks across its platform and business, utilizing AI to connect patients to the right providers based on various criteria such as patient preferences and providers’ specialties.
In-demand MedTech professionals for the current and future market
One of the great challenges for the healthcare industry has always been patient privacy. Whether it’s a hospital setting, a physician’s office, or a child’s vaccination records required by a school, we are right to be cautious with sensitive medical data. There are 26 different electronic medical records systems used in the city of Boston, each with its own language for representing and sharing data. Critical information is often scattered across multiple facilities, and sometimes it isn’t accessible when it is needed most — a situation that plays out every day around the U.S., costing money and negatively impacting outcomes.
As MedTech expands and becomes more pervasive, the industry will require more data security analysts, those gifted data detectives functioning as the guardians of our digital privacy and working behind the scenes to ensure the information we entrust to HCPs remains secure.
According to the U.S. Bureau of Labor and Statistics (BLS), the field of information security analysts is projected to grow by 35% between 2021 and 2031. Similarly, BLS projects the job growth for health information technicians to reach nearly 20 percent.
Data security analysts need a potent blend of technical expertise, analytical prowess, and critical thinking skills to secure the digital fortresses of information. Typical roles and responsibilities for a data security analyst:
Threat Detection and Protection:
- Monitoring security systems and logs for suspicious activity and potential breaches.
- Analyzing network traffic and data patterns to identify vulnerabilities and anomalies.
- Investigating security incidents and determining the scope and root cause of threats.
- Implementing and maintaining security measures like firewalls, intrusion detection systems, and data encryption.
Risk Management and Policy Development:
- Conducting security assessments and identifying potential risks, and weaknesses in systems.
- Developing and implementing security policies and procedures to mitigate risks and ensure compliance.
- Providing security awareness training to employees and educating them on potential threats and best practices.
- Staying up-to-date on emerging security threats and adjusting security measures.
Technical Skills:
- Security Tools and Technologies: Familiarity with firewalls, intrusion detection systems, data encryption, and security information and event management (SIEM) systems.
- Network Security: Understanding of protocols, security configurations, and common network vulnerabilities.
- Operating Systems and Scripting: Knowledge of various operating systems like Windows, Linux, and Mac, with an ability to write basic scripts for automation and analysis.
- Data Analysis and Visualization: Skills in analyzing security logs, identifying patterns, and visualizing data to identify potential threats.
Historically, healthcare consumers have had little control over their private medical records across fragmented systems in our decentralized healthcare infrastructure. There is no concept for the average consumer about where their information is stored, how it’s secured, or who else has access to it.
One such company providing state of the art AI software to clinicians is Augmedix, clinician-controlled mobile app that uses ambient AI technology and structured data to instantaneously create a fully automated draft medical note after each patient visit. The note is available in the EHR (electronic health records) for the clinician to review and sign off.
Companies like Augmedics will require AI chat developers in linguistics and language understanding (specifically within the medical field). AI chat developers must also possess a comprehensive grasp of grammar, syntax, and semantics to craft realistic and natural language-based interactions concurrent with the needs of physicians and patients such as:
Conceptualizing and Architecting:
- Understanding the purpose and target audience of the chatbot.
- Defining the chatbot’s functionalities and conversational flow.
- Choosing the appropriate AI platform and programming languages.
- Designing the chatbot’s interface and user experience.
Technical Skills:
- Programming Languages: Proficiency in scripting languages like Python, Java, or JavaScript, with additional knowledge of AI-specific libraries like TensorFlow or PyTorch.
- Natural Language Processing (NLP): Deep understanding of NLP concepts like tokenization, stemming, lemmatization, and dialogue state tracking.
- Machine Learning: Familiarity with machine learning algorithms like recurrent neural networks (RNNs) and transformers for training chatbot models.
- Cloud Platforms and APIs: Knowledge of cloud platforms like Google Cloud Platform, Amazon Web Services, or Microsoft Azure for deploying and managing AI models.
- Database Management: Ability to work with databases to store and retrieve chatbot training data and user interactions.
A new trend and emphasis of exploration within MedTech has been the proposition of modernizing patient access through the use of blockchain. The encrypted and impervious nature of blockchain offers a highly secure platform for managing patient data, allowing consumers to circumvent the complicated nexus of their personal health records between competing hospitals and EHR systems. This level of security is crucial in healthcare, where data integrity and patient privacy are of the utmost importance. Blockchain technology ensures that patient records are not only secure from unauthorized access but also accurate and unaltered.
Topflight MedTech blockchain developers have a multifaceted skill set, blending cryptographic prowess with coding agility and a sincere vision for what matters and where blockchain is headed.
Blockchain Architecting and Development:
- Understanding and analyzing various blockchain platforms and their capabilities.
- Choosing the appropriate blockchain technology for the specific project requirements.
- Designing and developing smart contracts, decentralized applications (dApps), and blockchain protocols.
- Implementing cryptographic algorithms and security mechanisms to ensure the integrity of the blockchain.
- Testing and debugging blockchain applications to ensure functionality and performance.
Technical Skills:
- Programming Languages: Proficiency in scripting languages like Python, Java, or JavaScript, with additional knowledge of blockchain-specific languages like Solidity or Go.
- Cryptography and Security: Deep understanding of cryptography concepts like hashing, digital signatures, and encryption algorithms for secure blockchain development.
- Distributed Systems: Knowledge of distributed systems architecture, consensus mechanisms, and peer-to-peer networking.
- Data Structures and Algorithms: Strong grasp of data structures and algorithms to optimize blockchain performance and efficiency.
- Database Management: Ability to work with databases to store and retrieve blockchain data.
As the MedTech field evolves and a steady flow of commercial and consumer products go-to-market, leaders in this field will find themselves studying product performance and security data in addition to medical charts and studies. Just as professionals in other fields have educated themselves for a technological future, especially around hiring top tech talent, the chief medical officers and others will soon find themselves steeped in a world of digital product development and AI deployment best practices. Worky is here to provide talent in these fields, even to help scope out full teams on an ongoing, as-needed basis so that the MedTech companies of the future can scale efficiently.
