In recent years, Artificial Intelligence (AI) has become part of our daily lives. From having our smartphones interpreting voice commands, to receiving movie recommendations based on our activities, we have been living with AI for quite some time now.

AI can play a significant role when we are faced with large amounts of data that require timely decisions. Sounds perfectly suited to healthcare, right?

One of the initial applications of AI in health was in imaging diagnostics, where programs and algorithms analyzed radiography images to detect abnormalities such as the presence of small tumours. It is true that AI programs need thousands, if not millions, of data points to “learn” what abnormal radiography is. On the other hand, this learning process takes a considerably shorter amount of time than a human would take.

There are many current and future applications for AI in healthcare in drug discovery, real-time patient flow management, an efficient organization of resources, rapid diagnostics, robotic-assisted surgeries, more efficient treatments, etc. Think of any situation where cognitive functions are required, such as reading and interpreting a report, and AI will definitely have a role to play there.

After all, data in healthcare is not a large lake but a non-stop river.

Medical technology represents one of the most innovative industries in the world based on the number of patents and products launched every year. However, the same barriers that impair access to medical innovations also exist for AI in healthcare.

Most of us will agree that we must consider patient value as the number one quest for any healthcare system: hence, whatever makes the patient better, should be considered for implementation and use by the healthcare systems.

In parallel to the clinical aspects, payment mechanisms have a tremendous impact on the adoption of technologies and processes. Put simply, we must identify who is going to pay for a medical technology if we plan to launch it into a certain market. And the same applies to AI.

We cannot ignore the fact that even though healthcare is a highly innovative industry, it remains conservative. We, in the medical technology industry, have the responsibility to take these factors into consideration so that we can quantify and demonstrate the value of AI solutions, accelerating their availability for providers, professionals, and patients.

The good news is that most healthcare systems in the world have committed to accelerate the inclusion of AI and digital health technologies in general. Take the example of Germany, where healthcare authorities implemented the new Digital Health Applications Ordinance (“Digitale-Gesundheitsanwendungen-Verordnung” – DiGAV). This came into force in April this year, and it entitles more than 70 million patients to reimbursement of digital health solutions.

The possibilities for AI to create value in healthcare are significant. As we celebrate MedTech Week 2020, let’s commit to taking on the challenge of quantifying this value and planning which payment, funding, and reimbursement mechanisms must be in place so that the AI benefits reach patients as quickly and efficiently as possible.