Technology is transforming healthcare in unprecedented ways to meet the demands of personalised patient care in the 21st century. Guided by advancements in digital healthcare innovations, such as artificial intelligence, robotics, or nanotechnology, the future of healthcare lies in a collaboration between healthcare specialists, scientists, patients, and corporations. In a conversation with Omnia Health Insights, Majid Kaddoumi, President Central & Eastern Europe, Middle East, and Africa at Medtronic, discusses how breakthroughs in medical technology will elevate patient outcomes.

Geoff Martha, Medtronic Chairman, and Chief Executive Officer said, “Some of the greatest advances in medical technology are unfolding right now at Medtronic”. Can you tell us about these advancements and how are they impacting the healthcare industry?

At Medtronic, we are on a mission to continue unlocking the world’s most complex living system — the human body. Naturally, this is closely followed by the advancement of instruments that help us understand it better. Today, we are using more advanced tools like artificial intelligence (AI), data analytics, predictive modelling, and robotic-assisted surgery to optimise patients’ prevention and treatment based on their individual health needs. As a result, we are creating a bold new era in personalised medicine, one where technology is at the centre stage and makes healthcare more efficient, accessible, and equitable.  

Related: Digital Innovations set in motion a new age for healthcare

For instance, cardiovascular disease patients require frequent medical appointments. During the pandemic, however, non-COVID-related health emergencies were delayed, leading to a disruption in the management of chronic conditions, such as stroke and heart disease. Nevertheless, with a Bluetooth-enabled pacemaker and an associated app on patients’ phones, many patients were able to adhere to a remote monitoring regimen. This revolutionary solution is leading to better clinical outcomes, as well as earning accolades from both patients and doctors; Cleveland Clinic for example nominated smartphone-connected pacemakers, such as ours, as one of the top 10 medical innovations of 2021.

For chronic diseases, we truly believe addressing them when they occur and enabling earlier diagnosis and treatment is key to creating better clinical outcomes. For this reason, we are focused on developing smaller and smarter devices that can be connected to healthcare providers for better outcomes in a more time-effective way.

How is Big data shaping the future of healthcare?

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Big data brings with it enormous volumes of data. At Medtronic, we’re using AI and machine learning to sift through the mountains of data and develop the next generation of sensing technologies to power neurostimulators, pacemakers, insulin pumps, and surgical tools.

Our smart devices are designed to be smaller, work faster, and help physicians deliver tailored care more than ever before. Imagine a not-so-distant future where data-driven solutions can optimise therapies for patients in real-time. Combining computer models and real-world data, our engineers are building virtual representations — also called “digital twins” — of our medical devices to predict how they will respond in the human body under various circumstances. The extensive testing capability helps create the most effective medical technology. When we bring together world-leading engineering expertise and device understanding combined with patient data, we get a much more complete picture of how that device and the patient will co-exist.

Majid Kaddoumi, President Central & Eastern Europe, Middle East, and Africa at Medtronic

Does robotic-assisted surgery enhance outcomes? Is it on the verge of wider adoption?

Combining robotic-assisted surgery with next-generation computing, visualisation, and artificial intelligence can give clinicians a new way to deliver more predictable, standardised, yet personalised patient care. By adding a new surgical video and data platform, doctors can also record, store, and analyse procedures. As a result, this can turn every surgery into a learning opportunity to improve clinical outcomes, propelling the age-old adage “see one, do one, teach one” to a new level.

How successful has the Medtronic hybrid closed loop system been in improving patient management? 

With the Medtronic hybrid closed-loop system for Type 1 diabetes — which combines insulin pump therapy and continuous glucose monitoring — patients and caregivers can find peace of mind. Approved for use in patients as young as two years old, the latest system also provides smartphone connectivity, providing both patients and caregivers regular updates and alerts. In addition, the power of connected care is available for diabetes patients, who rely on multiple daily injections (MDIs) too, thanks to the integration of our continuous glucose monitoring system with the only smart insulin pen cleared by the Food and Drug Administration (FDA); now up-to-date glucose readings and dosage information can be tracked on a single app.

The future of healthcare is digital, what future solutions does Medtronic have in its pipeline?

Stemming from the promising developments in artificial intelligence (AI), data analytics, and sensing technology, Medtronic’s medical devices are advancing chronic disease management by empowering clinicians to personalise medicine more than ever before. These technologies can detect, analyse, and react to ever-changing conditions in the human body, providing revelatory insights into individual patients, in real-time.

We are also very thrilled to reveal that we have over 130 new smart devices in the pipeline designed to treat cardiac complications, chronic pain, brain-related disorders, urinary incontinence, and diabetes in addition to being smaller, smarter, and less invasive devices that recharge faster and hold full capacity for longer.

Digital health has the power to revolutionise healthcare, Alternova Chief Operating Officer Maria Clara Mesa believes, not only by making the patient experience easier and more engaging, but also by democratising access to care worldwide, ensuring that no one is left out. 

It's why San Francisco-based tech company Alternova seeks to empower people to assume greater control of their health simply through their daily interactions with consumer devices.

In a video interview with Omnia Health Insights (below), Mesa explained that many healthcare businesses were unsure of how to integrate technology or implement digital transformation in their organisation. Developing digital health solutions is furthermore seen by some as risky and expensive. 

To remedy this, Alternova in partnership with Stanford Biodesign is offering an open source framework, CardinalKit, that “democratises” the development of digital health solutions and applications.

Currently an iOS platform with Android to come, CardinalKit may be used by developers, startups and physicians to accelerate rapid prototyping of digital health applications by collecting mobile and wearable healthcare data that is then displayed on an interface. Ensuring the privacy of this data is paramount, and in this regard CardinalKit is also compliant with the Health Insurance Portability and Accountability Act (HIPAA) in the US, which sets the standard for sensitive patient data protection. 

This allows solutions to be developed more cheaply and quickly, Mesa explained, including consumer-facing applications. She offered an example in the area of mental health: video games in particular have the potential to collect data on how a patient’s brain works, derived from the end user’s interactions, and implement changes that “reshape” the brain, resulting in better mental health. 

These video game applications may even replace pharmaceutical products, especially for children, Mesa continued. “Instead of a [pharmaceutical] formula for all patients for anxiety or ADHD, patients will have a personalised medicine in their pocket that is designed for the patient,” she said. “Scientists are trying to figure out how to arrive at a personalised experience that will modify a patient’s brain, allowing them to live better with anxiety or depression.”

Looking further ahead, Mesa is excited by digital health’s potential in the coming years, with patient-centred models, AI and cheaper wearables all combining to fuel its growth. “Tools to hack your health is where healthcare is going,” she concluded. “Health is the new social.”

Following the global epidemic of SARS-COV-2, most countries have recommended limiting non-urgent patient contact. In terms of practice guidelines, recommendations are still evolving, although many guidelines advocate limiting non-urgent operations and patient contact, conserving personal protection equipment, and limiting patient and physician interaction.

Before official regulations and consensus standards were established at the start of the COVID-19 pandemic, common practice was concerned about patients' need to return to the clinic following surgery for superficial suture removal. Patients who are older and may have underlying comorbidities are thought to be the most susceptible to the virus. As a result, several physicians explored wound closure procedures that would effectively support their wounds while also reducing the necessity for personal contact with patients.

Depending on the size of the incision, medical practitioners explored several wound closure methods. Sealants, such as acrylate or fast-absorbing gut sutures can be used alone for minor wounds once dermal absorbable sutures have been placed. Physicians preferred a more lasting superficial closure technique for bigger wounds that would not prematurely fail and could be readily removed by the patient at home.

According to JAAD Case reports published in Elsevier journal, it has been observed that using an adhesive retention suture device can help support vulnerable skin during wound closure. This ARS device is a low-cost, FDA-approved class I suture retention device that strengthens the skin and allows for high suture tension without causing tears. Physicians in this research chose to utilise the ARS device with retention sutures as the main support for many wound closures prior to COVID-19 to save patients from having to return for a follow-up appointment.

Other wound closure methods that require less in-clinic follow-up, such as topical adhesives or fast-absorbing gut sutures, can be considered. Physicians believe that using them without the ARS device would result in ineffective wound closure in high-tension wounds. Previous research revealed that cyanoacrylate and fast-absorbing gut had equal aesthetic effects when it came to closing linear wounds on the face, but that fast-absorbing gut was superior to cyanoacrylate when it came to linear closures of high-tension wounds on the trunk and extremities. The use of fast-absorbing gut is restricted by its tensile strength, which lasts around 5 days and increases the danger of wound dehiscence, particularly on fragile skin under stress. Fast gut may cause a strong inflammatory tissue reaction, which can be upsetting for patients and impair the aesthetic outcome.

Other adhesive closure devices, such as Clozex and Zip Surgical, are designed to offer just superficial wound support and are not as effective as ARS. They're designed to be utilised on wounds that have had their tension decreased by another closure method, for example, standard buried absorbable sutures, barbed sutures, or retention sutures.

The physical edition of FIME opens today at the Miami Beach Convention Centre. However, for those not attending, the online edition of the event that has been live from August 2 and will run until October 1, has a slew of virtual conferences discussing key topics that are changing the course of healthcare. One of them is AI in medical imaging: current state and future state by Dr Vijay Rao, discussing the future of imaging and diagnostics navigated through the lens of AI.

Radiology has been at the leading edge of the technological and digital revolution in medicine over the past several decades with the advent of CT, ultrasound and MRI. The next frontier innovation that will once again transform the future practice of Radiology to improve outcomes and patient care is Artificial Intelligence, which includes machine and deep learning.

Related: Artificial Intelligence acts as a heads-up display for doctors

With the technology revolution, there has been an explosion in the number of images, which necessitated the evolution of Picture archiving and communication systems (PACs). However, this has also created isolation of radiologists as clinicians have access to images on patient floors – they don't feel the need to come down to the department any longer. There are about two trillion images that are produced per year globally and half of them are from the U.S., which necessitates the need for storage. There are several challenges for radiologists because of data explosion. In addition to a shortage of radiologists, there's an emphasis on more productivity, which is leading to burnout of radiologists.

Machine learning is a data science methodology that enables the creation of algorithms that can self-learn and improve with exposure to large data sets. AI is not new by any means, it's been around since the 1950s, however, there are some key areas within radiology where its taking centre stage:

• With advances in AI with machine learning and neural networks, now we can simulate the environment, which was almost similar to the brain neural networks.
• For test selection, AI can help in building appropriate tests for the clinicians, generate the report, and help in how the results can be communicated. The protocols can be auto-generated by triage, and patients can be categorised according to case basis to reduce the length of stay.
• For scanning, smart machines are coming into play that can lower radiation doses, order quality assurance, classify diseases, reduce scan times, and prioritise work lists and changing protocols.
• Cognitive assistance with interpretation, assistance with workflow beyond interpretation, assistance with quality and safety of patient care, and assistance with lowering costs and better outcomes are four areas of machine learning and medical imaging. There have been several early achievements at image classification or detection of disease using AI, some of them being cases of stroke, cerebral haemorrhage, breast masses, lung nodules, spinal stenosis, bone age, pneumonia, and colon polyps.
• AI will assist radiologists in becoming more efficient by automating time-consuming tasks such as lesion counting, the number of metastases in the brain, and liver measurements. Another value add of AI is its accuracy and precision and reducing physician workload.
• AI assists with change detection and monitoring comparisons during therapy, detecting subtle changes which are not visible to the human eye. When it comes to physiologic assessments, AI performs better than the human eye in measuring the level of stenosis, measuring the tumour size, and all the physiologic changes of circulation.
• In the future, neural networks or AI can accurately classify genetic mutations in gliomas. We are now entering the realm of predictive medicine that takes us to precision imaging, which enables personalised treatment by accurately measuring the impact of therapy. This entails detection, quantification, predicting the nature of the tumour, and which therapy would suitable. In addition, by predicting and using imaging biomarkers, the need for interventions or biopsies can be reduced.
• Workplace virtualisation and communication is another important area. AI assistants can scan the cases rapidly and alert the provider if there's a critical finding. It can also highlight and prioritise the radiologist’s worklist to filter their study and accordingly identify which should be reviewed and reported first. Using natural language processing, there are concepts that can be traced from the report to automate several processes using the metadata logic layer. This can create actionable findings to highlight critical results and send information to the data registry. Different versions of the reports can be created, either a simplified version for the patient or one that provides data for research.

Related: Why we need to drop the sensationalism around AI in healthcare

To conclude, radiologists will often embrace AI applications to carry out time-consuming quantitative work and spend less time in front of computers – it will truly be a man/machine partnership. Not all the imaging benefits are pixel-based, many of the useful applications will come from non-excel based data analysis that are improving workflow, making radiologists more efficient, reducing burnout, etc. With initial approval by the U.S. Food and Drug Administration (FDA) and a temporary payment model by the Center for Medicare and Medicaid Services (CMS) in the U.S., it is likely that AI costs will become a cost of doing business and be absorbed by radiology practices and hospitals in the future. Future imaging scanners and interpretation platforms will have built-in AI applications.

Hope is that such advances will help democratise healthcare for the underprivileged and underserved at lower cost and facilitate global outreach, therefore, AI will augment not replace radiologists.

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