The future of healthcare is smart and connected – a vision for digital transformation

Ever since the first commercial MR systems were launched in the early 1980s, millions of patients have benefited from the detailed images of the body these machines provide to help physicians diagnose everything from cancers, heart damage and spine injuries to brain abnormalities.

Yet initially, like early cell phones, MR systems were essentially designed as static, stand-alone products – revolutionary in what they made possible, but with limited connectivity or services beyond basic break-fix maintenance.
 
That began to change with the introduction of remote connectivity, which I like to think of as a first step in digital transformation. For example, we can now monitor and analyze over 500 parameters on an MR machine remotely, 24/7, using predictive analytics to identify when certain hardware parts may need maintenance or replacement. As a result, 30% of service cases can be resolved before downtime is caused – preventing avoidable interruptions to clinical practice and unnecessary patient delays.

As any MR technologist or operator will tell you, performing an MR exam is not easy. Every patient has a different anatomy. There is a wide range of different protocols to choose from. And an MR exam is also time-consuming, taking anywhere from 15 to 60 minutes depending on the complexity of the case. For patients, spending such a long time in a restricted space can be stressful – especially because they need to hold still during the exam. Patient motion requires a redo in nearly one in five cases [1]. With ever-rising numbers of exams and a scarcity of qualified technologists in many parts of the world, that puts a huge pressure on staff – contributing to high levels of stress and burnout [2].

Can we make MR faster and easier for the operator, and more comfortable for the patient? Thanks to AI and smart algorithms, we now can.

One of my favorite examples is a camera-based patient sensing technology that lets the MR technologist monitor a patient’s breathing without having to set up an old-fashioned respiratory belt. The technology can analyze over a hundred body locations in parallel to extract signs of breathing – allowing the setups of routine MR exams to occur in less than a minute, even for less experienced operators, while helping them keep a caring eye on the patient [3].

By offering automated workflow support we can further boost operator confidence, allowing them to focus more on patients and less on technology. And with the help of smart algorithms, we can also drastically accelerate image acquisition, shortening MR exams by up to 50% [4].

In today’s digital, networked, and increasingly virtual world, asking ourselves how we can make individual MR or other diagnostic systems smarter is not enough. We need to recognize that they are all part of a larger, interconnected “system of systems” – a distributed network in which patient data needs to flow across different systems, different locations, and different care professionals.
 
Just like our smartphones can now seamlessly connect to a smart thermostat or a smart car, the next step in healthcare’s digital transformation will be all about integration.

In the context of radiology, that means we need to look for ways to connect and optimize the entire workflow – all the way from patient scheduling to planning the scan, interpreting it, creating a report, and bringing multiple types of patient information together for clinical decision-making (as my colleague Kees Wesdorp has detailed here).

Although we have made huge steps forward, the digital evolution of MR – as a building block of wider, integrated solutions – remains very much an ongoing journey.

Especially in terms of connectivity, there is still much to gain. Over the last decade, healthcare has been cautious in moving to the cloud. But in the wake of COVID-19, adoption is gaining momentum. During the pandemic, healthcare providers have experienced firsthand how cloud-based services – backed by robust security standards – allow for rapid implementation of innovations across settings [5].

In the future, I imagine we will be able to update and upgrade MR and other diagnostic systems over the air, just like we are used to updating our smartphone overnight. This means we could make the newest features available much more quickly, and always have MR scanners run at peak performance to serve patients optimally.