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Report: Healthcare Orgs Unprepared for Societal, Liability Issues of AI and IoT

June 11, 2018
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The healthcare industry is aggressively adopting intelligent technologies, such as the internet of things (IoT) and artificial intelligence (AI), but many health organizations need new capabilities to ensure that technology acts with responsibility and transparency as businesses evolve, according to a new Accenture report.

According to Accenture’s Digital Health Technology Vision 2018 report, more than three-fourths (77 percent) of the 100 health executives surveyed said they expect to invest in IoT and smart sensors this year — the highest among the 20 industries included in the broader Accenture Technology Vision research on which the health industry report was based. In addition, more than half (53 percent) of the health executives expect to invest in AI systems, with four-fifths (86 percent) of the executives saying that their organizations use data to drive automated decision-making at an unprecedented scale.

And, a majority of health executives (85 percent) surveyed agree that every human will be directly impacted on a daily basis by an AI-based decision within the next three years, and most (80 percent) agree that within the next two years, AI will work next to humans in their organization, as a coworker, collaborator and trusted advisor.

At the same time, healthcare executives using technology responsibly and in a transparent manner is critical. Ninety-two percent of health executives believe that ensuring the security of consumer data is important or very important to gain customers’ trust.

The study identified a range of issues related to the aggressive adoption of AI and the greater role it plays in healthcare decision-making, and the report also counsels the need for organizations to instill trust and transparency into the design of their technology systems.  

Eighty percent of surveyed health executives believe AI is advancing faster than their organization’s pace of adoption. More concerning, 81 percent of health executives agree that organizations are not prepared to face the societal and liability issues that will require them to explain their AI-based actions and decisions, should issues arise, according to the Accenture survey. As a result, 73 percent said they plan to develop internal ethical standards for AI to ensure that their systems act responsibly.

In addition, health organizations also face a new kind of vulnerability: inaccurate, manipulated and biased data that leads to corrupted insights and skewed results. More than five-sixths (86 percent) of health executives have not yet invested in capabilities to verify data sources across their most critical systems. In addition, one-fourth (24 percent) of the executives said that they have been the target of adversarial AI behaviors, like falsified location data or bot fraud.

The Accenture report also predicts key trends likely to disrupt business over the next three years, including virtual/augmented reality, blockchain and edge computing. Among the findings from healthcare executives about these technologies:

  • More than four in five (82 percent) of the executives said that extended reality—comprising virtual- and augmented-reality technologies—removes the hurdle of distance in access to people, information and experience, with nearly half (48 percent) of health providers and one-sixth (16 percent) of health payers planning to invest in these technologies in the next year.
  • Nine-tenths (91 percent) of health executives believe that blockchain and smart contracts are critical to enabling a frictionless business over the next three years, and approximately the same number (88 percent) believe that microservices will be crucial for scaling and integrating ecosystem partnerships. 
  • Four-fifths (82 percent) of health executives believe that “edge” architecture will speed the maturity of hyperconnected health environments, and slightly more (85 percent) believe that generating real-time insights from the volumes of data expected in the future will require computing “at the edge,” where data is generated. Yet the vast majority (86 percent) of health executives believe that they’ll need to balance cloud and edge computing to maximize technology infrastructure agility and enable intelligence everywhere throughout their organization.

“Intelligent technologies, such as AI, are enabling health organizations to evolve at speed, collaborate with other entities and create deeper, more meaningful relationships with patients across various care settings,” Kaveh Safavi, M.D., head of Accenture’s global health practice, said in a statement. “As this paradigm-shifting technology evolves—making business more dynamic than ever before—organizations will remain responsible for demonstrating data stewardship and designing systems with trust and transparency to bolster the societal benefits of these technologies.” 

 

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Industry Sage Joe Marion: We Have Yet to See Significant ROI on AI in Radiology

January 21, 2019
by Mark Hagland, Editor-in-Chief
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Artificial intelligence remains a huge topic of discussion and source of fascination in the imaging informatics world, but as industry sage Joe Marion notes, the practical ROI on AI remains elusive

In an article published on December 10, just days after the conclusion of the annual RSNA Conference at Chicago’s McCormick Place Convention Center, and sponsored as always by the Oak Brook, Ill.-based Radiological Society of North America, Siddharth Shah and Robin Joffe wrote in Diagnostic Imaging online, “The dust is now beginning to settle on the idea of AI in imaging—an idea that once took the industry by storm. The questions being asked by radiologists have now changed from “will it replace me?” to “how can it help me?”—and rightly so. AI continues to make significant progress in the field of diagnostic imaging, as can be gauged using the recently concluded Radiological Society of North America’s (RSNA) Annual Meeting in Chicago as a barometer.” What’s more, the authors noted, “Last year, there were 49 exhibitors at RSNA tagged as machine learning companies, and 22 of those were first time exhibitors. This year, the same number more than doubled to 104, 25 of which were first-time exhibitors. More importantly, the incumbents of medical imaging equipment have also made notable AI efforts, with each one launching new or enhanced AI capabilities. Clearly, AI was one of the key themes at RSNA.”

The writers also referenced a recent Frost & Sullivan that found that, “of the 114 startups active in the AI for medical imaging space, a significant majority target the image analysis aspect of medical imaging. Identifying and analyzing specific features in an image form the crux of a radiologists’ job, and since they base their findings on this analysis, it forms the most important clinical step in the imaging workflow. The startup disruption rampant in overall healthcare has focused on image analysis in the case of medical imaging AI.” There are artificial intelligence applications being launched “for triaging, worklist assignment, and workflow orchestration,” available from a growing number of vendors.

One of those who has a uniquely authoritative perspective on all this is Joe Marion, a principal in the Waukesha, Wis.-based Healthcare Integration Strategies LLC, has participated in 42 RSNA Conferences—probably among the most of any current attendee. No one has a broader perspective on the imaging informatics vendor market than Marion, who spent years on the vendor side before shifting over to consulting a number of years ago.

Healthcare Informatics Editor-in-Chief Mark Hagland spoke recently with Marion on his perspectives around AI and other key subjects in imaging informatics, at the beginning of 2019. Below are excerpts from that interview.

Here we are in January 2019; at this moment in time in the evolution of the industry, what’s your 40,000-feet-up view of imaging informatics right now?

The interest-grabber, if you will, that gets all the attention, has been artificial intelligence. And the question is where that’s going. Everybody has their placeholder in the context of a platform for AI application development. That probably gets the most attention right now. The reality is that the number of real practical applications that people are using and implementing remains really pretty small. So it’s more hype than reality. The next area that’s important is workflow orchestration. The driver in that context, if you talk with some of the key players, is largely the fact that there’s a lot of consolidation going on, so the intent of a lot of that consolidation is going to be broader reading capabilities.

Just look at Aurora and Advocate as an example. Part of the intent of any merger will be a broader radiologist base, to apply to my facilities, so that if a radiologist is on vacation at one facility, I can pick up the load at another facility. So I think the best way to describe it is intelligent distribution of studies to the available pool of radiologists.

Do you think that a lot of people are too distracted by shiny objects?

To some degree, yes. I think that’s the whole issue with AI—where’s the ROI? Show me that that’s really going to help. The more likely opportunity for AI in that regard is in the context of the shift towards value-based care. In essence, if I could intelligently analyze studies and suggest or route based on the consequences, that could make a difference. Let’s say if it were a complex case, maybe there’s some AI-based analysis to say, it makes more sense to route this to a specialist, as opposed to a generalist radiologist reading it first.

And another twist to that, a number of companies including IBM, have been vocal about it, is the notion of supportive information—the classic example that Change Healthcare always used was, a radiologist was going to review a case and there are spots on the liver, and his first instinct is that it’s a cyst, but he’s presented with the history of the patient and lab information and other information, and all that is made available, and they can use that information to help guide them, and it might change their initial impression that it’s a cyst, to that it might instead be a tumor. It’s in essence improving their read by presenting them with more information than they would normally  have. And that’s why I think that workflow orchestration actually offers more short-term benefit than to focus on something described as artificial intelligence.

Is there still work to be done on standards in imaging informatics?

Yes, there’s still work to be done. There’s still a fair amount of confusion. If you look at this XDS, cross-document sharing, if that’s the solution or future, there’s an extension of that called XDSI for imaging. Some people will say, yes, that’s great, but you’ll have to have devices that are XDSI-compliant; so building a repository that’s XDSI-compliant is one thing; but leveraging devices that are XDSI-compliant is another thing. So it’s the early days of the ACR-NEMA imaging format standard, which evolved into DICOM. But in the earliest days of that, it was sort of like the same landscape today for all of this. Yes, there was a standard for communicating, say, CT images. But the CT scanner had to support the DICOM standard, in order to get the images out of the scanner. Conversely, if the scanner was DICOM-compliant, but the viewers weren’t, what was the point of having the DICOM standard?

What do you think will happen this year, in imaging informatics?

I think it’s sort of business as usual. I just saw something about whether PACS deconstruction is real. First of all, a lot of that is terminology and phraseology. It’s hard to sort that out. But I think that there is some question in the context of where everything is headed. And I think the full-service companies are probably still in denial and want to sell you the concept of one throat to choke; whereas the company with the most success in that regard is Visage. There’s just an announcement out that they’ve closed a deal with Partners in Massachusetts. And when you look at the number of entities they’ve picked up—Shands Hospital in Gainesville, Mayo Clinic, Mercy in Iowa, many organizations that they’ve had success with, in saying, we want to be your front-end PACS [picture archiving and communications system] vendor of choice. And they work with a number of different solutions. This will all have to play out over time. But this year will definitely be interesting in this entire area.

 

 

 


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Research: AI, Automation Reshaping Healthcare Technology Support

December 6, 2018
by Heather Landi, Associate Editor
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Supporting an evolving, complex technology stack along with the needs of both internal and external customers is not easy for IT vendors. Moving forward, emerging technologies, such as automation and artificial intelligence (AI) will redesign the way in which tech support firms function, according to a Black Book Research survey.

As a result of new and emerging technologies, support operations will look significantly changed from what exists in 2018, according to the research report.

“IT support will become much more customer-facing, but also much more robotic,” Doug Brown, Black Book Research managing partner, said in a statement. “The power of automation and the rise of the patient experience are disrupting an idling tech support sector as vendors restate relevance in the client services space.”

AI, chatbots and other forms of automation are now grabbing attention within most of the systems targeted at the healthcare IT support industry, but there's not a lot of companies employing them, according to Black Book’s research. Only 3 percent of healthcare providers and 5 percent of payers responding to the Black Book survey have launched automated client service strategies. 

“Healthcare tech support is on the cusp of change and as healthcare technologies evolve and improve, they are likely to reshape the very nature of what is client services and tech support,” Brown stated.

With innovations like AI-powered conversation platforms, tackling challenges in natural language understanding and context resolution, healthcare tech support firms will be able to create advanced virtual agents that retain deep knowledge about supported products.

“Clients will be able to provide end users with a new way of interacting with support services beyond the help desk,” Brown said.

There also is a shift from an exclusively internal focus to an external focus, as delivering and support a superb customer experience is becoming the primary driver of competitive advantage for healthcare organizations.

"As technology becomes more profoundly entrenched into every turn of the healthcare consumer journey, vendors are also beginning to realize that the traditional internally-focused support organization may be best suited to help their provider clients successfully shift their focus to consumers,” Brown said.

Eighty-eight percent of CIO respondents reveal they are beginning to re-imagine the role of the support organization as they recognize technology is now critical to the patient experience and that their existing support teams are not well positioned to provide the best support, the survey findings indicate.

Blockchain, which offers a shared, distributed, and decentralized ledger that serves as a foundation for trusted collaboration among multiple parties throughout the tech support processes, also will play a role in this area. The next wave of innovations will be focusing on standardizing blockchain solutions that can be seamlessly integrated with organizations' IT systems to jointly drive the tech support ecosystem, according to Black Book Research.

The increasing role of Big Data and the Internet of Medical Things also will fundamentally change the technology support functions. Healthcare organizations are growing increasingly dependent on big data direct their initiatives. This tsunami of data requires more computing power, more hardware, more network capacity and more devices, both traditional and mobile, along with the need for ongoing maintenance of cloud infrastructure, servers, desktops, laptops and storage and network devices, according to the report. This will require IT vendors and managed services providers to have a deep pool of skilled subject matter experts available to proficiently service clients and also maintain the certifications to support multiple manufacturers' hardware, storage devices, operating systems, and networks.

With regard to IoT devices, as this technology expands to meet the needs of the industry, service desk teams are given the opportunity to specialize and research better ways to manage these devices and ensure they are under their control, and return value, and not risk to any environment.

More sophisticated tech support also will be necessary to support enhance patient care, according to the research. Eighty-eight percent of clinicians responding to the survey assert their delivery of patient care services are continually impeded by subpar user tech support, increasing nearly ten percent from last year's survey. Ninety percent of hospital chief medical officers surveyed asserted multi-level tech support from their health records vendor ranging from help desk through engineering interventions will be a leading competitive inpatient electronic health record (EHR) differentiator in 2019.

Of the 92 percent of hospital respondents that view high quality user support as a make or break feature in a vendor relationship, 60 percent say their tech support (both EHR firm provided and from EHR tech support outsourcing partners) are currently falling short in their responsibilities to ultimately allow patient care improvements through well trained delivery personnel.

Eighty-three percent of hospital tech managers prefer that their EHR deliver direct, comprehensive tech support, not push the responsibility to third parties or on the hospital system itself as the only options. Eighty-one percent of those clients employing third party outsourcing tech support are significantly dissatisfied with the level of response and the quality of their services in the twelve months following go-live. Clients could potentially be leveraging one vendor for their help desk services and another for their upgrade services and so on which can lead to an overall disparate support strategy, according to the report.

“The increasing complexity of healthcare technology has made it even harder for an in-house help desk team, especially in small and medium sized communities to have sufficient expertise to meet all of an organizations' tech support needs,” Brown said.

Enterprise tech support is a highly complex and niche area in healthcare, where specialists can make a big difference in client loyalty by catering from Level 1 to Level 4 product support to ensure all the provider's business goals are aligned with technology readiness.

Vendors scoring highest among the four comprehensive levels of technical support are Cerner, Allscripts and MEDITECH.  The majority (84 percent) of tech support for Epic clients were attributed to third party outsourcers, consultants, and independent tech support firms working in Epic Systems client facilities.

 

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RSNA 2018: Imaging’s Resurgence?

November 29, 2018
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Today wraps up the 104th annual Radiological Society of North America (RSNA – www.RSNA.org) meeting.  Mother Nature made it a challenging place to get to early in the week, but from all accounts, attendance was on par with the past few years. 

From an imaging informatics perspective, this year saw a number of things that point to a resurgence in imaging.  It also presented some disappointment with respect to how the imaging vendors are dealing with a changing healthcare environment.

Artificial Intelligence – the obvious

Let’s begin with the 600-pound gorilla in the room, and that would be Artificial Intelligence (AI).  By all accounts, if you were to sum up this year’s meeting, AI everywhere would be how one would describe it!  AI has been a topic of discussion for several years now, initially driven by IBM’s Watson Health initiative. 

In prior years, there was considerable talk about how AI was going to revolutionize Radiology, and potentially replace the radiologist.  This year, the emphasis seemed to really shift from the “pie-in-the-sky” discussion to real-world, commercially available solutions.

A key development conundrum has been how to commercialize AI.  Academic centers represent a first line of research into AI applications, while “boutique” companies have struggled with how to get developments to market.  Large imaging informatics companies have likewise wrestled with how to approach bringing AI applications to market.  The solution prevalent this year seems to be for both large and small companies to offer a “platform” for the implementation of AI.  By supporting such capabilities as software development toolkits (SDK’s), vendors are providing a means for commercialization of academic and third-party applications without themselves reinventing the wheel.

The AI “store” borrows from the way smart-phone applications have evolved by providing the infrastructure for the validation and distribution of AI applications.  What is not yet clear is the liability of providing access to other entity’s applications.  Is the Store vendor responsible for the application, or the developer?  Who files for and secures FDA approval?  Given that the objective is for these external applications to interoperate with the vendor’s imaging informatics system, there is some development risk on the part of the distributing company, and potentially a shared liability as well.  Only time will tell how effective this strategy is.

Depending on who you ask, AI primarily is perceived as clinical tools to improve the radiologist’s interpretation efficiency, not as a replacement to the radiologist from a clinical perspective.  Conversely, there were a number of applications that make use of AI technology to enhance the way information is handled and presented, and the way it impacts the decision process.  Much of this revolves around the way information is collected and made available to the clinician, such as retrieving relevant lab and other study information. 

One interesting example might be Siemens Healthineers’ Proactive Follow-up application (https://usa.healthcare.siemens.com/healthineers-population-health-management/value-based-care/proactive-follow-up-for-incidental-findings).  It uses natural language processing to identify incidents of follow-up, such as “repeat CT exam in six months.”  Incidents requiring follow-up are summarized in a “dashboard” presentation to enhance the ability of imaging services to coordinate with the necessary clinical services to ensure that the follow-up recommendation is followed through.  While not as “sexy” as an AI image processing algorithm, it may have just as much if not more impact on imaging services’ efficiency.

AI will influence imaging in another way by fostering greater use of the cloud.  To maximize availability and accessibility, the cloud appears to be the major means for the deployment of AI applications.  Some vendors are also increasingly moving to the cloud for their entire enterprise imaging informatics applications.  Such non-traditional players as Intel and Google are becoming a greater factor in terms of how imaging is secured and managed, and AI appears to be an influencing factor. 

Clinical Decision Support – the not so obvious

While major emphasis was on AI, less emphasis seems to have been given to Clinical Decision Support, and the associated mandates.  The Protecting Access to Medicare Act of 2014 (PAMA) originally directed CMS (Centers for Medicare and Medicaid Services) to require Appropriate Use Criteria (AUC) consultation for Advanced Diagnostic Imaging procedures beginning Jan 1, 2017.  The mandate has now been delayed to January 1, 2020, which isn’t that far away!

Imaging companies correctly point out that clinical decision support will be more a function of the electronic health record (EHR) system, and they don’t seem to be particularly concerned with how it will impact imaging applications, with a few notable exceptions.  Change Healthcare (https://www.changehealthcare.com/) has been reformulated over the past few years from a “back office” services company to one encompassing imaging through the acquisition of McKesson’s imaging business.  More recently, Change acquired National Decision Support Company (http://nationaldecisionsupport.com/) to address the PAMA mandates by means of synergy between its product lines. 

Similarly, Siemens Healthineers acquired Medicalis, which was also focused on clinical decision support tools.  Collectively, these two vendors seem most aggressive in addressing the intersection of imaging services and the changing landscape of healthcare management.

Value-Based Care – another not so obvious

Healthcare providers are moving away from fee-for-service models to value-based care models of healthcare delivery.  These changes will ultimately impact imaging services, yet there appeared to be little direct emphasis amongst exhibitors. 

Part of this conundrum may be the perception that much of the informatics needed to address value-based care will be encompassed within the EHR.  On the other hand, imaging vendors seem to be more focused on the “mechanics” as opposed to the topic of value-based care.  For example, analytics tools and intelligent worklists are mechanisms that will help enable radiology to support value-based care, but they are not necessarily emphasized as such.

Consolidation and New Players

The industry continues to be a study in competitive dynamics, in that certain segments demonstrate further consolidation, while other segments continue to expand.  The area of workflow orchestration has seen a transition from “incubator” companies such as Clario, Primordial, and Medicalis to complete absorption by large imaging vendors.  Siemens Healthineers previously acquired Medicalis, and Nuance acquired Primordial.  The surprise announcement at this year’s meeting was the acquisition of Clario by Intelerad (https://www.intelerad.com/en/press-releases/intelerad-medical-systems-acquires-clario-medical/).  This now means all three of the key workflow orchestration vendors are part of larger imaging informatics organizations, and can leverage those capabilities as part of their offerings.

On the other side of the spectrum was the dramatic introduction of United Imaging Healthcare (https://usa.united-imaging.com/united-imaging-healthcare-makes-u-s-market-debut-at-rsna-2/) into the U.S. market.  United made their entry with one of the larger exhibits, and a dramatic first-day unveiling.  While operating in other world markets prior to this year, United has made a large investment by establishing a U.S. presence.

For a number of years, the imaging industry has lived in the shadow of the EHR, as providers scrambled to address government mandates for electronic health records.  Now that much of that infrastructure is in place, it appears that imaging informatics may be well-positioned to capitalize on further investment to support the EHR.  AI appears to be the first recipient of that emphasis.  From my vantage point, there will need to be a further shift to emphasize applications and solutions that support consolidation and value-based care trends.  It will be intriguing to see if these areas receive more emphasis at RSNA 2019!

 

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