Dr. Visa Suomi, medical devices industry manager at MathWorks, highlights the most important trends shaping the medical devices industry and healthcare.
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Healthcare digitalisation enables new innovations
Healthcare is becoming more digital, which means that increasing amounts of data are stored in electronic health records and hospital information systems. Furthermore, real-time health data is continuously collected by wearables such as smart watches, fitness trackers, or blood glucose monitors. Having all this data in a digital format does, in theory, enable its utilisation in healthcare applications, but the data also needs to be easily accessible, stored in a structured and standardised way, and kept secure to maintain patient confidentiality and privacy. When these conditions are met, new possibilities are unlocked to develop innovative medical devices and digital health applications to improve patient care. These are the five most important trends leveraging the digitalisation in healthcare.
Telehealth
Telehealth, or telemedicine, allows healthcare services to be provided to patients remotely. For example, a patient could be using a wearable medical device that monitors their physiological signals, such as heart rate, and stores the data in the cloud for analysis. Another example would be an operation conducted by a doctor using a remotely operated surgical robot on the patient. Virtual doctor visits have also gained popularity due to the recent pandemic and by some estimates, the utilisation of telehealth services is now up to 38 times higher than before. Telehealth’s popularity is not surprising since it brings several benefits to patients, such as convenience, fewer physical doctor visits, and better accessible healthcare for people with limited mobility. For hospitals and other healthcare providers, telehealth enables better control of infectious diseases, scaled health services, and cost savings. Furthermore, it allows them to offer medical services in remote locations and rural areas where healthcare facilities do not exist.
In silico medicine
In silico medicine uses computational modelling and simulations to design, test, and validate medical devices. Instead of using humans or animals in testing new type of treatments, medical researchers use virtual human populations to evaluate the performance and safety of the device in different clinical situations. For example, a ventilator design could be validated using a realistic lung model to ensure its safety and performance. Similarly, an insulin pump with glucose monitoring (i.e., an artificial pancreas) could be validated using a virtual patient model with varying blood glucose levels. In silico medicine thus allows companies to reduce the time and costs in R&D and, at the same time, improve the quality, performance, and safety of their products. The European Union and FDA have also noted the importance of in silico medicine in their recent strategic policy roadmaps and regulations.
Digital twins
Digital twins in healthcare are virtual representations of patients or medical devices that incorporate their historical diagnostic and/or maintenance data into a single knowledge base. As new data becomes available—for example, when a patient visits a hospital for an examination, or a medical device is inspected—the corresponding digital twin gets updated to keep track of current health status more accurately. This up-to-date data can then be used in AI and simulation models to form predictions for future states and support decision-making. Using digital twins in medical care allows patients to benefit from personalised medicine to individually detect the best possible treatment options as well as more proactively manage chronic diseases and overall health. For medical device manufacturers, digital twins enable predictive maintenance and better product lifecycle management.
AI-based medical devices
Artificial intelligence (AI) is a major trend affecting multiple industries and disciplines including healthcare and medicine. The advantage of AI comes from its ability to determine subtle patterns and characteristics in healthcare data such as medical images, biomedical signals, or health records that would otherwise go unnoticed. This helps clinicians better diagnose and understand underlying health conditions and support decision-making about the most suitable therapy options. For example, an AI model can be used to classify whether a thyroid nodule in an ultrasound image is benign or malignant, and thus reduces the need for unnecessary biopsies. A machine learning model could also be used to restore the sense of touch for paralysed people by interpreting EEG signals using a brain-computer interface with a haptic feedback loop. The FDA has already approved several AI-based medical devices to the market, which is just the beginning of many possibilities in AI benefitting healthcare.
Cloud and IoT
The Cloud and Internet-of-Things (IoT), combined with big data in healthcare, bring new possibilities that are sometimes referred to as healthcare 4.0. The Cloud allows medical devices to be connected and collect patients’ vital information around the clock. The most typical examples of Cloud-connected health devices are wearables and smart watches, which gather data about heart rate, blood pressure, oxygen saturation, sleep patterns, physical activities, and blood glucose levels. This data can then be interpreted either by an algorithm or a clinician to detect any anomalies and decide the necessary actions. The Cloud also enables software-as-a-service (SaaS) applications in healthcare by providing unrestricted and secure online access to electronic medical records, PACS servers, and hospital information systems. Utilising the cloud in healthcare is likely to become even more prevalent in the future due to its cost, security, and scalability benefits.
Technology is the key to digital health
The more medical data is available and accessible in a digital format, the more possibilities exist to develop new and innovative applications that make healthcare more efficient and improve patient outcomes. There are still barriers that the industry and healthcare providers need to overcome together, such as gaining straightforward and secure access to medical data and health records without compromising patient privacy and confidentiality. With the help of the right software solutions and technical capabilities, companies can fully leverage these trends in creating new medical devices and digital health applications.
Learn more: MATLAB and Simulink for Medical Devices
