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MedTech in 2020: the Future of Digital Health

medical-2020Healthcare technology is one of the many areas that stand to benefit from the fast development of Artificial Intelligence, data-based solutions, and other tech advancements. Find out what technologies we’re expecting to see in the digital health & medical device industry in 2020!

However disruptive digital transformation is proving to be in all industries including healthcare, most changes resulting from it are slower to take effect. New technologies around the IoMT (Internet of Medical Things), wearables, and data-based solutions are still evolving, and their applications in the sphere of medical technology are expanding. Therefore, the trends described in our 2019 medical tech report are still relevant as their adoption is expected to grow further in 2020.

Read our previous annual MedTech reports:

MedTech Trends 2019: the Era of Digital & Data-driven Health

Medical Technology Trends in 2018

Digital Health Industry: Medical Technology Trends in 2017

The convergence of personal mobile devices and medical tech is accelerating, and the technologies being put to use in other industries continue to seep over to healthcare. Developers are finding new applications for machine learning and AI, while data-driven solutions (and the blockchain technology that enables their use) continue to fundamentally transform digital health technology.

Those existing solutions will be applied in new ways and complemented by new technologies, driving the evolution of the digital health industry in 2020. Let’s take a closer look at what we can expect in coming years:

New uses of AI & machine learning

The use of Artificial Intelligence is widely believed to become the single most transformative factor of digital change in all industries. In healthcare, developers are looking to apply machine learning and AI to monitor and identify epidemics, to develop virtual nursing technology, and to provide image analysis and interpretation capabilities to diagnostic solutions.

These complement existing research into using Artificial Intelligence to model and predict biological and chemical interactions in drug development, and other solutions delivering insights based on big data. Chatbots supporting the management of patient care also rely on Artificial Intelligence, as do virtual assistants and personalized treatment solutions. As more and more health data becomes available to train algorithms, its use cases will surely expand even further.

Healthcare robotics

The global medical robotics market is expanding fast, with experts forecasting it will grow to $20b by 2023. Up-and-coming 5G connectivity enabling fast and almost immediate data exchange will open up new opportunities for using robots in the future’s digital health economy.

Robots will be applied for various purposes including transportation, prescription dispensing, and disinfection – but also for communication/telepresence and even as surgical assistants. In fact, experts believe that later on, operating robots may even receive a certain level of autonomy to take care of simple tasks in the operating room with a high level of precision.

Before we get there, expect the large-scale adoption of remote-operated robots for telemedicine and specifically to facilitate remote surgery. Nanodevice-related research is also an exciting field that may hold vast opportunities for healthcare practitioners.

In the intersection of robotics and Artificial Intelligence, computer and machine vision looks like a promising field of innovation. Advancements in these technologies increasingly enable robots to sense and interpret visual input, adding more and more value to their use in diagnostics (gaining insights from scans and other medical images), surgery, and more.

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Introducing Intland’s New MedTech Development Templates

Digital twins: medical applications

A digital twin in general is the digitalized replica of something physical – in the context of healthcare, it refers to the lifelong medical data records of a patient represented in the digital space. These data records hold the possibility of brining about a new era of patient-centric care: using the digital twin, a doctor can model and safely determine the possible success of a medical procedure or treatment, enabling them to make more personalized (and more effective) recommendations in therapy. Again, AI has a strong use case here, contributing to the huge potential that digital twin technology holds.

NLP and voice control

Natural Language Processing is a specific field of AI research that concentrates on interpreting human language, whether written or spoken. This technology is at the root of all the voice-controlled devices we’re starting to see everywhere (in cars, smart homes, mobile devices, and more). NLP provides great use cases in predictive analytics and diagnosis, while voice activation and control could have a major impact on senior care and supporting patients with disabilities, and we’re expecting to see much more devices equipped with this technology in 2020.

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