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Artificial Intelligence in Imaging 2018

Artificial Intelligence in Imaging 2018
Early Adopters Speak Out

Authored by: Monique Rasband and Emily Paxman February 27, 2018 | Read Time: 8  minutes

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The HIT industry is abuzz with talk about artificial intelligence (AI), a broad term used to describe the use of algorithms and software to approximate human cognition in the analysis of complex data. Of all the healthcare areas with potential AI applications, imaging has received the greatest attention. Vendors and providers in this space are looking forward to using AI to improve diagnosis processes, develop treatment protocols, and personalize patient care, among other use cases. In this report, 81 healthcare organizations (primarily large IDNS) help separate hype from reality by sharing details regarding their early imaging AI deployments and plans and by identifying which vendors they see as early leaders.

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State of the Market

Until recently, talk about AI in imaging has been more common than actual adoption, but progressive provider organizations and their vendor partners have begun to roll out the technology or are making plans to do so.


organization status with ai in imaging

Almost Half of Interviewed Organizations Are Live or Making Plans

Most organizations live with AI in imaging today are beta testing new technology in limited settings but have committed internal resources to further research and development. Because it is early, it is not uncommon for those live to have NDAs in place with their vendor partner. Others are actively monitoring the evolution of imaging AI, with almost one-third preparing for adoption. Those who are not live or do not have near-term plans to adopt AI in imaging say more research and time are needed to identify use cases and prove an ROI.

when do organizations making plans expect to go live

For Those Making Plans, Deployment Is Years in the Future 

The majority of organizations who are actively planning to adopt an imaging AI strategy anticipate that they are more than a year away from adoption; just over one-third feel it will take at least three years. In the meantime, these organizations are requesting demos, discussing potential use cases with peers who are already live, and assessing the AI needs of their radiologists.

depth of adoption for ai in imaging

Adoption Is Limited Today, but Steady Progress Is Expected

Many organizations that are live with some form of imaging AI use the tools in a limited way and with lower adoption, typically within a single department (e.g., radiology). They are using these deployments as pilots to learn more about AI’s potential. Those who are not live today expect to take a similar path, i.e., lower initial adoption in a controlled, limited setting. Both groups express the long-term desire to see AI in imaging widely deployed and deeply adopted.


Which Vendors Are on Providers’ Radars?

What vendors do organizations view as best positioned to deliver AI in imaging?


Number of Live Validations

Validations


  • Agfa HealthCare1
  • Arterys1
  • Carestream1
  • EchoPixel1
  • IBM Watson/Merge4
  • Philips1
  • Zebra Medical Vision1
  • Internal development/provider partnerships4


Additional Vendors Mentioned

Considerations


  • Agfa HealthCare2
  • Carestream2
  • Cerner2
  • GE Healthcare6
  • IBM Watson/Merge23
  • Nuance2
  • Philips6
  • Vital Imaging2
  • Volpara (breast)2
  • Zebra Medical Vision6



Vendors with One Mention



  • Ambra Health
  • Apple
  • Arterys
  • CancerCenter AI
  • Bay Labs
  • Butterfly Network


  • Entopsis
  • Epic
  • Google
  • HealthMine
  • Lexmark
  • McKesson


  • Mindshare Medical
  • MModal
  • Proscia
  • RADLogics
  • Samsung
  • ScreenPoint Medical


  • Sectra
  • Siemens
  • TeraRecon
  • Visage Imaging



IBM Watson’s Efforts Drive Mindshare; Delivery Concerns Temper Provider Expectations


Receiving over three times the mindshare of any vendor in this study, IBM has piqued the interest of provider organizations by creating the Watson Health Imaging Collaborative, acquiring imaging vendor Merge, and commencing beta testing with development partners. Most organizations express confidence that IBM will be able to deliver a solution for imaging AI but expect that it will be years before mainstream solutions are available—they describe IBM’s current progress as mostly marketing. Expectations around future delivery are also tempered by IBM’s historical lack of strong customer partnerships, which some see as a potential impediment to delivery. Even among organizations currently involved in the Watson Health Imaging Collaborative, confidence in IBM’s delivery is mixed. While progress is being made and IBM has committed vast resources to development, these organizations say that efforts are disorganized, current capabilities are oversold, and true delivery has yet to be seen. A handful of organizations are using IBM’s early tools; reactions from these customers are also split. Some describe the development as exciting and in tune with needs, while other say it lags behind their expectations.

mindshare vs provider confidence in delivery

Philips and Zebra Medical Vision Gain Visibility through Strong Road Maps and Partnerships

After IBM, imaging vendor Philips has made the most headway in terms of mindshare. Philips excels at sharing their road map and AI investments and has gained providers’ trust through the acquisition of AI technology and through the development of PACS overlays and other tools that show competence in imaging AI. Zebra Medical Vision has piqued interest through partnerships with healthcare organizations, Google Health, and others, leading many to see them as committed to imaging. The vendor’s comparatively small size has contributed to the view that they are nimbler than larger players and will be able to develop and adapt well in a rapidly changing market. GE Healthcare’s extensive footprint in imaging has many organizations interested in what GE Healthcare has to offer, and providers point to a strong sales team and portfolio depth as the vendor’s strengths. However, confidence in GE Healthcare’s ability to deliver is lower due to the vendor’s history of stagnant development, lack of strategic relationships with customers, and challenges deploying enterprise imaging technology.


Provider Perspective on Early Imaging AI Leaders


IBM Watson/Merge

“I think IBM has a lot of resources to throw at the AI problem, so that gives them a bit of an advantage over niche companies. However, I don’t feel that IBM has done much to move beyond their marketing pitch. I am also not sure they really understand the imaging world the way they need to in order to really blow this thing out of the water. If we have learned anything from doing enterprise imaging, it is that we need a real partner to expand and be successful. That is not what IBM is known for, so I don’t know that they are really set up to be successful.” 
—Director of Radiology

Philips

“We speak with and work with Philips regularly to get updates for the system. They talked with us recently about their road map. Philips tries to avoid heavily marketing things that aren’t real. In that way, we have appreciated Philips’ approach.” 
—VP of Imaging

Zebra Medical Vision

“I have looked at Zebra Medical Vision; I don’t have much experience with them, but I do have some confidence in them based on the people they have been able to partner with in the imaging space. I think they have done a nice job of focusing on what imaging-specific issues need to be tackled. Even though artificial intelligence in imaging is still new, Zebra Medical Vision is a vendor to watch.” 
—VP of Imaging

GE Healthcare

“GE Healthcare has touted AI for a long time, so they are under the spotlight. They need to make something happen if they want to back up that hype. They are doing some things already, but it isn’t where they expected it to be.” 
—Director of Radiology


Will the Most-Mentioned Imaging Vendors Deliver? A Historical Look at Vendor Performance

Of all the vendors that organizations view as best positioned to deliver AI in imaging, traditional imaging players are mentioned most frequently. A look at these vendors’ development and delivery histories offers insight into their potential ability to meet providers’ expectations for AI in imaging.

a historical look at vendor performance

What Should Providers Look for in a Vendor to Be Successful?

Over the last 20 years, KLAS has watched many emerging spaces gain momentum only for vendors to fail to deliver on the market’s expectations. Where there is success, there are typically several key vendor attributes present. By looking to partner with vendors who exemplify these traits, providers can begin their imaging AI journey on the right foot.


people communicating icon

Crystal Clear Expectations

One of the primary reasons providers are left unsatisfied with new technology is that their expectations go beyond a vendor’s ability to deliver. A clear discussion about what outcomes will be achieved, when those outcomes will be realized, and the steps that both the customer and vendor need to take to realize the outcomes is key. An excellent vendor will not only set clear expectations with potential customers but also ensure that all the modules and services customers need to be successful are part of the initial sale.

handshake icon

Proactive, Strategic Relationships

In emerging spaces where new use cases are rapidly developing and best practices are being discovered, ongoing communication between vendors and customers is essential. Vendors who excel in this area foster strong relationships by providing dedicated account management, proactively sharing use cases and other insights, and deeply understanding their provider partners.

person presenting icon

A Central Focus on Training

Quality of training is one of the best predictors of customer satisfaction, affecting usability, adoption, and perception of a system’s functionality. Unfortunately, training (particularly ongoing training) is often taken off the table by vendors during contract negotiations to lower the purchase price. Top-performing vendors who take steps to remove financial barriers to training, pair end users with trainers who have a similar background, and provide healthy follow-up training are most likely to have satisfied customers.

person showing graph icon

Strong Data Governance

Strong data governance can make or break an imaging strategy. Starting early and making this a priority can be the difference between realizing a tangible ROI and sinking resources into a failed project. Those live with an AI strategy today emphasize the role governance played in their success, and they encourage their peers to ensure data governance is a priority by involving key stakeholders across multiple areas/departments and leveraging best practices from other organizations and vendors. Vendors can encourage customers to tackle governance and even provide suggestions and useful industry connections to facilitate customer efforts.


chart legend

how well do imaging vendors set and deliver on expectations
how well do imaging vendors build relationships
how well do imaging vendors train end users

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This material is copyrighted. Any organization gaining unauthorized access to this report will be liable to compensate KLAS for the full retail price. Please see the KLAS DATA USE POLICY for information regarding use of this report. © 2020 KLAS Research, LLC. All Rights Reserved. NOTE: Performance scores may change significantly when including newly interviewed provider organizations, especially when added to a smaller sample size like in emerging markets with a small number of live clients. The findings presented are not meant to be conclusive data for an entire client base.