Nuance Communications Focuses on Practical Application of AI Ahead of HIMSS18

Posted on January 31, 2018 I Written By

Colin Hung is the co-founder of the #hcldr (healthcare leadership) tweetchat one of the most popular and active healthcare social media communities on Twitter. Colin speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

Is there a hotter buzzword than Artificial Intelligence (AI) right now? It dominated the discussion at the annual RSNA conference late last year and will undoubtedly be on full display at the upcoming HIMSS18 event next month in Las Vegas. One company, Nuance Communications, is cutting through the hype by focusing their efforts on practical applications of AI in healthcare.

According to Accenture, AI in healthcare is defined as:

A collection of multiple technologies enabling machines to sense, comprehend, act and learn so they can perform administrative and clinical healthcare functions. Unlike legacy technologies that are only algorithms/ tools that complement a human, health AI today can truly augment human activity.

One of the most talked about applications of AI in healthcare is in the area of clinical decision support. By analyzing the vast stores of electronic health data, AI algorithms could assist clinicians in the diagnosis of patient conditions. Extending this idea a little further and you arrive in a world where patients talk to an electronic doctor who can determine what’s wrong and make recommendations for treatment.

Understandably there is a growing concern around AI as a replacement for clinician-led diagnosis. This is more than simply fear of losing jobs to computers, there are questions rightfully being asked about the datasets being used to train AI algorithms and whether or not they are truly representative of patient populations. Detractors point to the recent embarrassing example of the “racist soap dispenser” – a viral video posted by Chukwuemeka Afigbo – as an example of how easy it is to build a product that ignores an entire portion of the population.

Nuance Communications, a leading provider of voice and language solutions for businesses and consumers, believes in AI. For years Nuance has been a pioneer in applying natural language processing (NLP) to assist physicians and healthcare workers. Since NLP is a specialized area of AI, it was natural (excuse the pun) for Nuance to expand into the world of AI.

Wisely Nuance chose to avoid using AI to develop a clinical decision support tool – a path they could have easily taken given how thousands use their PowerScribe platform to dictate physician notes. Instead, they focused on applying AI to improve clinical workflow. Their first application is in radiology.

Nuance embedded AI into their radiology systems in three specific ways:

  1. Using AI to help prioritize the list of unread images based on need. Traditionally images are read on a first-in, first-out basis (with the exception being emergency cases). Now an AI algorithm analyzes the patient data and prioritizes the images based on acuity. Thus, images for patients that are more critical rise to the top. This helps Radiologists use their time more effectively.
  2. Using AI to display the appropriate clinical guidelines to the Radiologist based on what’s being read from the image. As information is being transcribed through PowerScribe, the system analyzes the input in real-time and displays the guideline that matches. This helps to drive consistency and saves time for the Radiologist who no longer has to manually look up the guideline.
  3. Using AI to take measurements of lesion growth. Here the system analyzes the image of lesions and determines their size which is then displayed to the Radiologist for verification. This helps save time.

“There is a real opportunity here for us to use AI to not only improve workflows,” says Karen Holzberger, Vice President and General Manager of Diagnostic Solutions at Nuance. “But to help reduce burnout as well. Through AI we can reduce or eliminate a lot of small tasks so that Radiologists can focus more on what they do best.”

Rather than try to use AI to replace Radiologists, Nuance has smartly used AI to eliminate mundane and non-value-add tasks in radiology workflow. Nuance sees this as a win-win-win scenario. Radiologists are happier and more effective in their work. Patients receive better care. Productivity improves the healthcare system as a whole.

The Nuance website states: “The increasing pressure to produce timely and accurate documentation demands a new generation of tools that complement patient care rather than compete with it. Powered by artificial intelligence and machine learning, Nuance solutions build on over three decades of clinical expertise to slash documentation time by up to 45 percent—while improving quality by 36 percent.”

Nuance recently doubled-down on AI, announcing the creation of a new AI-marketplace for medical imaging. Researchers and software developers can put their AI-powered applications in the marketplace and expose it to the 20,000 Radiologists that use Nuance’s PowerScribe platform. Radiologists can download and use the applications they want or that they find interesting.

Through the marketplace, AI applications can be tested (both from a technical perspective as well as from a market acceptance perspective) before a full launch. “Transforming the delivery of patient care and combating disease starts with the most advanced technologies being readily available when and where it counts – in every reading room, across the United States,” said Peter Durlach, senior vice president, Healthcare at Nuance. “Our AI Marketplace will bring together the leading technical, research and healthcare minds to create a collection of image processing algorithms that, when made accessible to the wide array of radiologists who use our solutions daily, has the power to exponentially impact outcomes and further drive the value of radiologists to the broader care team.”

Equally important is the dataset the marketplace will generate. With 20,000 Radiologists from organizations around the world, the marketplace has the potential to be the largest, most diverse imaging dataset available to AI researchers and developers. This diversity may be key to making AI more universally applicable.

“AI is a nice concept,” continued Holzberger. “However, in the end you have to make it useful. Our customers have repeatedly told us that if it’s useful AND useable they’ll use it. That’s true for any healthcare technology, AI included.”