How AI Drives Down Healthcare Costs and Improves Quality of Care

By Ronny Shalev, PhD, CEO of Dyad Medical

Artificial intelligence (AI) is one of the main tools powering the next generation of healthcare technology. With the potential to drive down healthcare costs and improve patient outcomes, all while helping doctors do what they do best. AI has high potential to transform our overall healthcare system.

There are many areas of healthcare where AI is being applied, from drug discovery to diagnosis and at the bedside. With the rise of physician burnout and increasing patient backlogs, easing these burdens are one of the biggest opportunities for implementing AI. There is an opportunity to reduce the number of tedious, time-consuming tasks in a physician’s daily workload and improve patient satisfaction.

The High Potential for AI Tools That Aid Decision Making Around Diagnosis and Treatment

Today doctors in fields like cardiology and radiology are using AI to enhance their decision making. Indeed, all healthcare treatment and diagnosis decisions are based on data and data is the foundation of AI, so it is only natural that AI is becoming an integral part of any physician’s toolkit.

Some AI algorithms are already aiding radiologists in making highly accurate conclusions about cardiac and other forms of imaging, eliminating disagreement among experts, and effectively acting as a trusted, instantaneous, automatic “second opinion.” AI can also expand the imaging system operator’s view and help them detect red flags that the human eye cannot see alone. The physician can then use their training and expertise to make a diagnosis and plan for treatment. AI cannot replace our doctors, but it can make their jobs easier and more efficient. When we’re able to automate the tedious parts of doctors’ jobs, they’re able to treat more patients and do the parts of their job they like, such as spending time with their patients.

Efficiency of care and accuracy of results means patients get better treatment faster. Look at the cost of cardiovascular diseases, for example. Coronary artery disease is the most common type of heart disease and is the leading cause of death worldwide, ahead of cancer and coronavirus. According to the U.S. Center for Disease Control, by 2035, more than 130 million people, or 45% of the U.S. population, are projected to have some form of cardiovascular disease. In 2035, projected medical costs of cardiovascular diseases will reach $748.7 billion and indirect costs are estimated to reach $368 billion.

Which AI Tools Are Worth the Investment?

Investing in AI tools to treat and diagnose cardiovascular diseases has the potential to have a profound impact on our health. Especially those tools that aid with detecting and preventing larger health problems such as heart disease. In the medical imaging market alone, AI is expected to grow ten times in size between 2021 to 2027, according to a recent report from Arizton Advisory and Intelligence.

Clearly there is a tremendous opportunity for the global AI in medical imaging market. The importance of doctors having AI resources is only growing as more and more people are diagnosed with chronic diseases tied to cardiovascular health. However, not all AI technology is created equally. It is critical to invest in AI, use good data, and integrate seamlessly into existing healthcare processes to become scalable for use on a global scale. When the AI technology checks all three of these boxes, it is then that we will see the greatest financial return and most improved health outcomes.

AI Built on Good Data

In the world of healthcare, the gold standard for any medical imaging tool is clinical validation and FDA clearance. For something like AI platforms that automatically analyze cardiac images to be FDA cleared means it has undergone a rigorous process FDA review. To obtain FDA clearance, the AI software had to be trained by analyzing millions of images that represent the population that will end up benefiting from the AI tool. (e.g., pediatric cardiac patients). In addition, the technology needs to be clinically validated.

Doctors need to be confident that they’re using a tool they can trust. They simply won’t use it if they’re skeptical because they don’t want to risk the health of their patients because they relied on something built on questionable data.

AI Embedded into Current Workflows

Even if the technology is built extremely well and performs brilliantly, doctors still won’t use the tool if they have to upend their existing workflows. For example, in medical imaging, many clinicians turn to AI tools to reduce the amount of time they spend analyzing images and to get a second opinion on their observations and diagnoses. Some software that automatically analyzes medical images requires the hospital IT team to reconfigure their servers and the data is hosted somewhere outside of the hospital’s network, posing data privacy concerns. On the other hand, cloud-based tools, like the Libby software platform for cardiac imaging, enables secure remote access from anywhere in the world. There is no upfront set up and no maintenance. The software app also easily embeds into existing workflows so clinicians can continue working in a way they find comfortable.

Additionally, a user-friendly interface allows doctors to easily understand and navigate through the AI-powered application efficiently. Using the Libby software application as an example, the interface allows radiologists and cardiologists the ability to get all the information they need, very quickly. Reducing the number of clicks to automatically analyze cardiac images enhances the doctor’s workflow. Shorter wait times for viewing the results also eliminates another tedious step of the doctor’s day-to-day routine. This creates a seamless experience for the clinician so they can focus on treating more patients.

AI That is Scalable and Accessible

For an AI tool to have a meaningful impact on our global health, it has to be available to everyone, not just those who can afford access or live in communities with a large concentration of healthcare resources. Pairing AI with cloud-based technology gives less advantaged communities access to quality care they would not otherwise have. Cloud-based AI tools and platforms could be used anywhere in the world as long as there’s an internet connection. This could be a critical lifeline for communities that don’t have access to cardiology specialists.

As we seek ways to harness AI to augment a physicians’ ability to treat patients and improve our collective health, we must be thoughtful about our investments. The future of healthcare technology is here thanks to AI, but it is up to us to invest in tools that address our collective health.

About the author

Dr. Ronny Shalev is CEO and founder of Dyad Medical Inc. a company that develops FDA-cleared software which automatically analyzes the content of cardiac and cardiovascular images using artificial intelligence. He has spent much of the past 25 years in executive positions, including VP of Sales and Marketing at Orbotech (NASDAQ: ORBK), where he managed teams of >100 people worldwide and Director of the World-wide Program Management at Marvell Semiconductor (NASDAQ: MRVL). An expert in developing new projects employing medical image processing, machine learning and visualization. He has a significant amount of experience as an entrepreneur and is dedicated to using his skills to help physicians make accurate decisions to improve patient outcomes. He holds a Ph.D. in electrical engineering and computer science from Case Western Reserve University.