Authors: Charles Taylor
The sweeping disruption that Covid-19 brought to healthcare systems around the world has been well documented. We’ve seen almost two years of continuous coverage on how the NHS and its international counterparts have fared, with countless news stories devoted to backlogs, staff shortages and faltering service delivery.
About the author
Charles Taylor is founder and CTO at HeartFlow.
However, the challenges laid at the feet of healthcare professionals have been a catalyst for change when it comes to our relationship with MedTech. In fact, healthcare systems have made something of a leap forward when it comes to taking advantage of technology. Patient diagnosis and treatment is now looking considerably different in 2022 compared to 2020.
What do you see as the most impactful change over the past two years?
There’s been a seismic shift, not only in the development of artificial intelligence / deep learning technologies, but in the proficiency and confidence with which clinicians use them. As a general rule, technology is now deployed more easily and with greater depth of analysis. This gives healthcare providers the capabilities to work through cases faster, more confidently and with greater repeatability. The desire and enthusiasm to embrace these technologies has been there for some time, but broad uptake has been slow, preventing AI from becoming ubiquitous across healthcare.
The pandemic has forced the hand of the sector and we now see how impactful AI and deep learning is. One area where this is clear is in the diagnosis of coronary heart disease (CHD), and the utilization of FFRct technology. This technology uses data from a coronary CT scan and leverages deep learning to create a personalized, digital 3D model of a patient’s arteries. Algorithms then solve millions of equations to simulate how blood is flowing through the arteries, which allows clinicians to understand the impact of any blockages. Non-invasive technologies such as FFRct can help negate the need for more invasive investigations such as angiograms, which carry their own risks of complication. It also allows doctors to assess the severity of disease with high accuracy 1, meaning patients get quicker and more tailored treatment plans, and interventions like stenting or bypass surgery are prioritized for those who need it most.
As a result, we’re rapidly moving towards a time where healthcare providers supported by AI will almost always deliver diagnoses faster than those without it.
What changes will patients see?
Heavy caseloads were common to many departments and services in healthcare systems prior to the pandemic. The last two years have inevitably exacerbated this, with many treatments and procedures delayed or cancelled. What’s more, social distancing requirements have forced clinicians to move much of their patient interaction to digital spaces.
This has accelerated the rise of telehealth, which allows healthcare professionals to monitor and connect with their patients remotely. It is a broad term with a wide variety of applications, from virtual check-ups and consultations, to health tracking via smart watches and even robotic surgery performed through remote access. In many ways, it marks the future of healthcare. The necessities of recent years have helped to build confidence in the use of digital technology as patients have become increasingly familiar with its presence in their healthcare experience.
As we continue to embrace and develop the technologies that make AI-led medicine possible, interactions between clinicians and patients will only become more meaningful. Data-led insights will fuel greater understanding of health conditions, easier communication, and more appropriate and individualized treatment plans.
Are there any downsides to the increased presence of MedTech in our lives, such as ingrained bias?
Since 2020, a much needed spotlight has been placed on bias within healthcare systems, and in recent months this lens has extended to those ingrained within AI and technology. It’s something we’re very aware of with our own FFRct technology. No bias is introduced in the FFRct test, as all identifying patient data is removed before our algorithms are applied to patient CT scans.
In 2022 and beyond, there needs to be a determined focus on developing AI with parity in mind. That means ensuring algorithms are trained on diverse data sets with a statistically significant representation of genders, age, BMI and races. AI is always learning and improving, and it is incumbent upon us to ensure the training sets are as diverse as possible.
We’re facing a future where technology will dominate healthcare, becoming an indispensable tool to maintain a healthy population. While that absolutely doesn’t diminish the role of healthcare providers, it’s essential the technologies they use allow them to provide the best possible care for everyone. Increasing diverse representation in medical trials is crucial to deepening our understanding of healthcare and formulating the most effective clinical guidance. If we can start to achieve this, then we really will start to unlock the full potential of MedTech.
What does the future look like for technology in healthcare?
The last two years have been a steep learning curve for healthcare systems. Many of the technological capabilities and applications developed under the duress of the pandemic will become part of best practice healthcare. There’s still much to accomplish, but as we learn to live with Covid-19 as an endemic part of our lives, healthcare providers will gain more time and opportunity to build on the lessons they have learned.
Technology has not only proven its worth in healthcare, but we’ve become much more confident in using it. Continuing to embrace, fund and celebrate its development will help to support systems both in the UK and beyond as we emerge from unprecedented disruption and seek to create a future that optimizes healthcare experience and outcomes for all.