The proliferation of the Internet of Things (IoT) in healthcare is accelerating, with the estimated number of connected medical devices expected to increase from 10 billion to 50 billion over the next decade, with more than 28 billion projected by 2021. Estimates place the market opportunity at approximately $400 billion by 2026.
The opportunity is there, but the support isn’t (yet)
By harnessing the data from smart medical devices and applying machine learning and artificial intelligence, medical technology (MedTech) companies have the opportunity to show improved patient outcomes, reduce healthcare system costs and offer new digital-enabled services to their customers. But this data is increasing exponentially, and pharmaceutical and healthcare companies will need to manage it to drive clinical prompts, dashboards, and communications. All this will require new skillsets, human and machine learning expertise, and new types of analyses and user interfaces. Most companies have not yet built or are in the early stages of building out this expertise.
Telemedicine is experiencing a meteoric rise
Foley & Lardner’s inaugural 2014 Telemedicine and Digital Healthcare Survey showed that 87 percent of respondents didn't expect their patients to be using telemedicine services by now. The same survey in 2017 reflects a surge in demand for telemedicine-based offerings among providers and patients. Three-quarters of respondents in 2017, including hospitals, specialty clinics and related organizations, offer or will offer such services – with plans to increase them in the U.S. and beyond.
Technology and health care are converging rapidly
Tech and healthcare are converging rapidly, with industry giants Google and Amazon investing heavily in healthcare startups. Google Ventures is working with and investing in leading companies across the healthcare spectrum, and investing roughly a third of the capital it gets from Alphabet into healthcare and life science start-ups, such as Verily and Calico. Industry disruptor Amazon has its sights set on upending the complex healthcare industry. In early 2018, Amazon announced a partnership with Berkshire Hathaway and JPMorgan to launch an independent company that will offer healthcare services to the companies’ employees at a lower cost. This venture, run more like a non-profit than a for profit entity, will be one to watch in the coming market cycles.
The automotive industry provides clues and guidance
To understand the tremendous disruptor opportunity in connected medical devices, we can look to the automotive industry, another highly regulated segment, for some predictors. Like the auto industry, long product lifecycles, a dominance of well-established players, incremental digital investments, and relatively light experience in software and digital all led to sluggish innovation.
But a rapid shift from discrete products (horsepower, speakers, seatbelts and airbags) to connected systems have ushered in opportunities for new market entrants to meet consumer demands and expectations. These include mobile phone operating system integration, robust GPS systems, music platform integration, preventative safety measures such as automatic braking and self-driving vehicles. Disruptors such as Uber, Lyft, Car2Go and Zipcar are redefining the short-term public transportation and vehicle rental landscape. Tesla’s market capitalization is a mere $2 billion less than General Motors ($51 billion versus $53 billion, respectively), yet delivers 2.5% of the total vehicles (250,000) that GM delivers (10 million).
These disruptors all have several things in common that the MedTech industry can learn from: creating customer-centric solutions that solve real pain points, looking beyond traditional industry peers to establish new norms, focusing on ecosystems rather than discrete product siloes, and leveraging the best-in-breed technologies instead of building them from scratch (for example, Google Maps powers Tesla’s GPS system).
Connected medical devices are powering new business models
The automation of clinical interventions for patients experiencing an adverse event is giving rise to a transformation in clinical care and a shift to outcomes-based business models. Capturing data such as patient vitals from medical devices that is then contextualized via predictive algorithms and models can help to improve patient outcomes, predict adverse events before the occur, and track real-world outcomes that enable new business models. Connectivity is also enabling more proactive medical device management, including making over-the-air updates, improving power management, locating devices and more, all of which can be done to help streamline clinician workflow. With the rise in edge computing much of this data processing is taking place closer and closer to the medical devices, enabling faster computing and optimization.
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