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Healthcare AI Could Generate $150B In Savings By 2025

Posted on September 27, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Is the buzz around healthcare AI solutions largely hype, or can they deliver measurable benefits? Lest you think it’s too soon to tell, check out the following.

According to a new report from market analyst firm Frost & Sullivan, AI and cognitive computing will generate $150 billion in savings for the healthcare business by 2025.  Frost researchers expect the total AI market to grow to $6.16 billion between 2018 and 2022.

The analyst firm estimates that at present, only 15% to 20% of payers, providers and pharmaceutical companies have been using AI actively to change healthcare delivery. However, its researchers seem to think that this will change rapidly over the next few years.

One of the most interesting applications for healthcare AI that Frost cites is the use of AI in precision medicine, an area which clearly has a tremendous upside potential for both patients and institutions.

In this scenario, the AI integrates a patient’s genomic, clinical, financial and behavioral data, then cross-references the data with the latest academic research evidence and regulatory guidelines. Ultimately, the AI would create personalized treatment pathways for high-risk, high-cost patient populations, according to Koustav Chatterjee, an industry analyst focused on transformational health.

In addition, researchers could use AI to expedite the process of clinical trial eligibility assessment and generate prophylaxis plans that suggest evidence-based drugs, Chatterjee suggests.

The report also lists several other AI-enabled solutions that might be worth implementing, including automated disease prediction, intuitive claims management and real-time supply chain management.

Frost predicts that the following will be particularly hot AI markets:

  • Using AI in imaging to drive differential diagnosis
  • Combining patient-generated data with academic research to generate personalized treatment possibilities
  • Performing clinical documentation improvement to reduce clinician and coder stress and reduce claims denials
  • Using AI-powered revenue cycle management platforms that auto-adjust claims content based on payer’s coding and reimbursement criteria

Now, it’s worth noting that it may be a while before any of these potential applications become practical.

As we’ve noted elsewhere, getting rolling with an AI solution is likely to be tougher than it sounds for a number of reasons.

For example, integrating AI-based functions with providers’ clinical processes could be tricky, and what’s more, clinicians certainly won’t be happy if such integration disrupts the EHR workflow already in existence.

Another problem is that you can’t deploy an AI-based solution without ”training” it on a cache of existing data. While this shouldn’t be an issue, in theory, the reality is that much of the data providers generate is still difficult to filter and mine.

Not only that, while AI might generate interesting and effective solutions to clinical problems, it may not be clear how it arrived at the solution. Physicians are unlikely to trust clinical ideas that come from a black box, e.g. an opaque system that doesn’t explain itself.

Don’t get me wrong, I’m a huge fan of healthcare AI and excited by its power. One can argue over which solutions are the most practical, and whether AI is the best possible tool to solve a given problem, but most health IT pros seem to believe that there’s a lot of potential here.

However, it’s still far from clear how healthcare AI applications will evolve. Let’s see where they turn up next and how that works out.

Radiology Centers Poised To Adopt Machine Learning

Posted on February 8, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

As with most other sectors of the healthcare industry, it seems likely that radiology will be transformed by the application of AI technologies. Of course, given the euphoric buzz around AI it’s hard to separate talk from concrete results. Also, it’s not clear who’s going to pay for AI adoption in radiology and where it is best used. But clearly, AI use in healthcare isn’t going away.

This notion is underscored by a new study by Reaction Data suggesting that both technology vendors and radiology leaders believe that widespread use of AI in radiology is imminent. The researchers argue that radiology AI applications are a “have to have” rather than a novel experiment, though survey respondents seem a little less enthusiastic.

The study, which included 133 respondents, focused on the use of machine learning in radiology. Researchers connected with a variety of relevant professionals, including directors of radiology, radiologists, techs, chiefs of radiology and PACS administrators.

It’s worth noting that the survey population was a bit lopsided. For example, 45% of respondents were PACS admins, while the rest of the respondent types represented less than 10%. Also, 90% of respondents were affiliated with hospital radiology centers. Still, the results offer an interesting picture of how participants in the radiology business are looking at machine learning.

When asked how important machine learning was for the future of radiology, one-quarter of respondents said that it was extremely important, and another 59% said it was very or somewhat important. When the data was sorted by job titles, it showed that roughly 90% of imaging directors said that machine learning would prove very important to radiology, followed by just over 75% of radiology chiefs. Radiology managers both came in at around 60%. Clearly, the majority of radiology leaders surveyed see a future here.

About 90% of radiology chiefs were extremely familiar with machine learning, and 75% of techs. A bit counterintuitively, less than 10% of PACS administrators reported being that familiar with this technology, though this does follow from the previous results indicating that only half were enthused about machine learning’s importance. Meanwhile, 75% of techs in roughly 60% of radiologists were extremely familiar with machine learning.

All of this is fine, but adoption is where the rubber meets the road. Reaction Data found that 15% of respondents said they’d been using machine learning for a while and 8% said they’d just gotten started.

Many more centers were preparing to jump in. Twelve percent reported that they were planning on adopting machine learning within the next 12 months, 26% of respondents said they were 1 to 2 years away from adoption and another 24% said they were 3+ years out.  Just 16% said they don’t think they’ll ever use machine learning in their radiology center.

For those who do plan to implement machine learning, top uses include analyzing lung imaging (66%), chest x-rays (62%), breast imaging (62%), bone imaging (41%) and cardiovascular imaging (38%). Meanwhile, among those who are actually using machine learning in radiology, breast imaging is by far the most common use, with 75% of respondents saying they used it in this case.

Clearly, applying the use of machine learning or other AI technologies will be tricky in any sector of medicine. However, if the survey results are any indication, the bulk of radiology centers are prepared to give it a shot.

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.”

Roundup of Tweets from #RSNA15

Posted on December 2, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.


The number of international people at RSNA 2015 is impressive. It provides a unique mix of perspectives.


Like the rest of health care, radiologists care deeply about patients.


The visualizations at RSNA were really extraordinary.


One thing I discovered about RSNA and radiology is that they have a really strong grip on history. In some cases that’s good, but in other ways it’s damaging to progress.


This ultrasound is an example of how inexpensive and portable imaging and other health data collection has become. It’s incredibly powerful!


Outside of the various visualizations, the 3D printing was one of the most exciting things I saw at the conference. It was all over the place and has really become a reasonable option.

We’re More Alike Than We Are Different – Day 2 at #RSNA15

Posted on December 1, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

As I’ve continued my virgin journey at the massive RSNA (radiology) conference, I continue to be struck by how the challenges radiologists face are so similar to the challenges that are faced around healthcare IT. Here’s a look at some of them I’ve heard so far:

Data Standardization – In the EHR world we’ve been talking about data standardization forever. In the imaging world the challenges are very much the same. There are large and small vendors and the same challenge of trying to get them all on the same page. I do think imaging is a touch further along than the EHR world when it comes to standardization. However, they still have a ways to go too.

Workflow – Creating the right process for capturing and documenting the image is a major challenge. Getting the image to display at the right place and the right time is also a challenge. Sounds a lot like all the other EHR data doesn’t it?

Patient Engagement – This one really surprised me. In fact, some radiologists argue that the patient doesn’t want to interact with the radiologist, but only wants to interact with their referring provider. However, I’ve heard over and over from people about the opportunity for radiologists to really engage the patient. I think it’s a slightly different engagement, but all of healthcare IT is talking patient engagement.

Privacy and Security – The breach is just as strong in imaging as it is in all other health IT.

Smart Use of Data – There’s a feeling that we need new systems to process all the imaging data in a better way and that we should present only the data that’s relevant and necessary to the situation. In other words, exactly what we’re trying to do with the patient’s entire medical record. In fact, I think the smart use of data has to apply across all of a patient’s data from imaging to consumer collected data to EHR data.

Data Trust Issues – We trust radiology data, but as Kim Garriott, Principal Consultant of Healthcare Strategies for Logicalis Healthcare Solutions pointed out to me, the same isn’t true for a lot of other imaging data. There’s still a lot of work to do to ensure that the capture of other data from ultrasounds to scopes is done in a way that other providers can trust that data. Sounds exactly like our discussion around trusting EHR data.

I guess it shouldn’t come as a surprise that the challenges are very much the same even if it sometimes feels like another world. We’re more alike than we are different. It’s just easy to focus on our differences. I think there’s a lot we can learn from each other.

First Impressions of RSNA 2015 (#RSNA15)

Posted on November 30, 2015 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

This year will be my first time attending RSNA (see my full schedule of healthcare IT conferences), the massive radiology conference held in Chicago each year. I’d been wanting to check it out for years, but traveling to Chicago right after the Thanksgiving holiday never seemed all that appealing to me. Don’t ask me what convinced me to do it this year. I’m not sure why other than a real desire to experience the show first hand. I’d heard it was massive and would be worth my time. I’ll be sure to let you know what I think.

I’ve already got a schedule that’s nearly as full as HIMSS or MGMA and that’s saying something. I’ll be interested to see how many of them give me the radiology pitch as opposed to the healthcare IT pitch. I think I’ve made myself pretty clear, but we’ll see when we get to the actual meetings. Of course, there’s plenty of healthcare IT that’s worth hearing about. Not to mention amazing innovations around 3D printing and other mobile health technologies. I even saw a virtual reality viewer that I hope I get a chance to check out.

As I’ve prepared for my first trip to RSNA, I’ve been watching the #RSNA15 hashtag on Twitter. It’s been a great way for me to connect with those in the RSNA community. Plus, it’s given me a good overview of what’s likely to be topic of conversations at RSNA. The power of Twitter and hashtags is really amazing to me.

One thing that surprised me on the Twitter stream is how the message to Radiologists is very similar to many of the other healthcare IT events I go to around the country. No, I’m not talking about the #RSNA15 tweetup or the Cannoli Shooters. It seems that radiologists are being encouraged to be more involved in health care. This tweet illustrates an example of this message:

Here’s a good roundup of tweets from the opening RSNA keynotes and day 1 of RSNA 2015:

I look forward to seeing many of you at RSNA and reporting on the event for those of you who can’t make it.

On-Demand and Just in Time: Healthcare CIOs Respond to an On-Demand World

Posted on November 9, 2015 I Written By

The following is a guest blog post by Eric Rice, Chief Technology Officer, Mach7 Technologies.
Eric Rice CTO Mach7 Technologies
Doesn’t it feel at times like we’re living in a total “on demand” world? How did we survive before DVRs, push notification to our pockets and, my current favorite, voice on-demand ordering with “Alexa” (no commercial here for a certain on-line/on-demand retailer).

Consider our on-demand workforce. A recent Intuit survey suggests that the number of Americans working as providers in the on-demand economy will more than double to 7.6 million in 3 years. Our culture is “demanding” on-demand and this trend is naturally impacting healthcare. CIOs must be on-demand-ready both in their delivery of services and in providing access to patient care data.

As a provider of healthcare information technology (i.e., a software and services vendor), our customers are the CIOs and IT directors of hospitals and imaging centers, but the clinical customer has always been the patient.

In our connected world where consumers expect to obtain information easily, shop for the best prices, and control how and where personal information is managed (i.e., financial data, shopping data, exercise data), it’s not surprising that the highly-regulated, compartmentalized world of hospital IT and information management is facing a groundswell for on-demand images and just-in-time information from all corners of the market.

This demand is more than a cry for convenience and personal preferences; in healthcare, on-demand access to patient information and timely decisions can have life-altering impacts. Access to accurate information “on demand” isn’t just a nice-to-have feature, it’s a necessity.

Health IT Standards Meet the Demand for “On Demand”

Adopting a standards-based, robust infrastructure for healthcare data collection, storage, access, sharing, and workflow management is key to handling an on-demand healthcare IT world. CIOs must be able to deliver patient data in all of its formats, from all of its sources, to meet a growing set of regulations, requirements, and constituents. From Meaningful Use to EHR/EMR demands to referring physicians, specialists and, oh yes, patients!

Here’s my take on healthcare transformation for CIOs.

Patient Self-Service: Enabling patients to pay their bills online is a no-brainer, but in an on-demand world, patients want more control and greater visibility. Why should we be surprised? Beyond appointment reminders and bill payment, patients want to “self-schedule”, upload new content, be more in control of their health and involved in their healthcare. They want to review lab and test results and make those data points available to other providers for second opinions. They want to shop for healthcare like they shop for any other retail products – and they want to communicate electronically with their doctors and expect those providers to have full access to a full healthcare history – complete with images, pictures and video. We have the technology today to provide this level of self-service, on-demand access; we need to transform our thinking to make the vision a reality.

Access and Sharing of a Complete Health Record:  We may recognize “show me the money”, but how about “show me the images!” The transition in patient record management made by EHR/EMR deployment was huge. The next step is building and providing a complete patient record that includes image sharing with both referring providers and patients. We are seeing these requirements promoted by regulatory bodies – nationally, CMS and ONC are pushing these requirements through avenues like Meaningful Use. Some states, such as Florida, are mandating that Level 1 and 2 trauma centers have the ability to share images to and from referring organizations.

Imaging access lags the IT advances made in most other industries. With the rollout of EMRs, care record access and sharing may be improved but often a key component is still missing, the specialty images. As one of our customers is fond of saying, ‘an EHR without images is like a museum without paintings.’ Patients and clinicians demand access to a complete healthcare record, and that complete record must contain images – yes, on-demand.

Interoperability in Merger Mania:  Healthcare consolidation is on the rise with increased merger and acquisition activity every year. Connecting, consolidating, and managing patient records across consolidated facilities is a significant challenge. CIOs understand that on-demand access to patient care records requires interoperability for seamless access and sharing of information across HIT vendor solutions.

Proactive Healthcare CIOs and IT professionals are getting in front of this transformation with new thinking, open, flexible technologies, standards, and policies. They know that “on demand” access is a key driver of care delivery, clinician satisfaction and patient satisfaction. After all, we’re all living in an on-demand world.

About Eric Rice
Eric Rice has 12 years of systems architecture and design, engineering and management experience, with the most recent 7 years focused on medical imaging IT. His team is focused on medical imaging workflow and interoperability across disparate RIS, CVIS, PACS, and reporting solutions. He brings strong software engineering techniques, a solid understanding of R&D processes, and excellent medical imaging domain skills to Mach7. Eric holds a Bachelors of Science degree from Virginia Polytechnic Institute and a degree in Management Science & Information Technology with a specialty in Decision Support Systems from the State University (Virginia Tech).

Insightful Tweets from #RSNA14

Posted on December 3, 2014 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

If you’re not following @RasuShrestha, you’re missing out on some really good tweets. He’s sent a number of insightful tweets from RSNA that I thought were worth sharing..


I like the rhetoric of his statement, but I’d like to see more action too.


It’s interesting that they’re fans of consumerism. I know that many in healthcare don’t like to think of patients as consumers. They have good reasons for not wanting the comparison and it’s worthwhile to consider the difference. Plus, it’s worth noting that in our current system patients don’t really act like consumers. That’s why I think it’s true that consumerism is hitting healthcare.


I love plays on words. I’m going to have to chew on this one a bit more though.


Click on this image to blow it up. It definitely illustrates how important the EHR is, but also that the other health IT systems are important as well.


This is my favorite tweet. I saved it for the end so only the most faithful readers would get to see it. I’m not an expert on radiology, but this provides an interesting roadmap for some of the things that happening in radiology.

EHR Adaptation, Film to Digital, and Box

Posted on March 23, 2014 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.


I agree completely that patient expectations are changing. I think we’re going to see a dramatic shift in the patient experience. What I’m not as sure about is whether the EHR will be the one to meet those changing expectations. EHR software is distracted with other things and they’re not well positioned to handle the change.


I’m not sure I’d really classify this as a pivot. I think Viztek is doing pretty well with their PACS. They’re not going to stop doing that anytime soon. It is an interesting diversification for the company. Although, I was more intrigued to think about what we could learn from the PACS experience going from film to digital. We need more people writing about those learnings.


Those are two big powerhouses that Box brought on board. I’d heard a lot about box and its efforts in healthcare. This illustrates how important healthcare is to Box’s future.