Tag Archives: Nuance

Signify Premium Insight: From ‘Base Camp’, Nuance Readies for Assault on Fully Ambient Solution Peak

Nuance Communications’ recent announcement of its new AI-automated clinical documentation app is the latest in a slew of innovations from the Microsoft-backed company. 

Nuance describes DAX Express as a ‘workflow integrated, fully automated clinical documentation application’, adding that it is the first solution combining ‘proven conversational and ambient AI with the newest and most capable generative AI technology, GPT4.’ 

In a voice dictation market that has often failed to live up to hype and (unrealistic) expectation, DAX Express potentially brings the holy grail of a ‘fully ambient solution’ one step closer.  

The Signify View 

DAX Express nudges the voice dictation market further along the track. Nuance now occupies a metaphorical ‘base camp’, the peak of fully ambient solutions now tantalisingly in view. Nuance occupies this rarefied space alone, its competitors still acclimatising to the relentless pace of the race.  

Nuance says DAX Express will generate draft clinical notes ‘automatically and securely in seconds from exam room or telehealth patient conversations for immediate clinical review after each patient visit’. It adds that clinicians ‘will benefit from the seamless capabilities of Dragon Medical One, DAX and DAX Express, which are tightly integrated with EHRs, beginning from pre-visit through post-encounter, reducing cognitive burdens and addressing staff shortages’. 

If true, it will be music to the ears of a healthcare industry for whom the reality of voice dictation in the EHR workflow has yet to scale serious heights. Despite rapid technological advances and the promise that innovations like DAX Express hold in transforming EHR workflows, Nuance (and its rivals) must still convince sceptics. And there are many. 

Trust Issues 

Buyers and users Signify Research speaks to confirm that many clinicians still manually type up their own notes in the absence of what they see as viable alternatives. Some complain of ‘unacceptable’ delays between voice entry and order activation. Others state that Nuance’s Dragon software ‘isn’t strong enough inside Epic’ (a reference to Dragon’s integration in Epic’s EHR). 

Most voice dictation technology still requires substantial manual input, either by the physician or transcription service providers. Interviewees say automated transcription quality can be poor, and even when it is good, the transcript must still be ‘translated’ by a human into terminology that the EHR can decipher, and then manually coded into the EHR’s structured data fields. 

Hospital buyers say many staff will start using voice dictation tools with good intentions, but quickly fall back into familiar workflow habits and established methods, due to disappointment with solutions. And some clinicians are also reluctant to do away with medical secretaries, whose job is much more than simply typing up clinician notes. 

A fully ambient solution must not only address these barriers but also accurately capture the patient-physician conversation, and then produce ICD-10 and SNOMED codes for diagnoses, prescriptions and reimbursement claims. The real value here lies in turning ‘unstructured’ data from an encounter into ‘structured’ data in the EHR. No solution does that yet, although Nuance DAX brings it closer to fruition. 

Mission to Convert 

If anyone can convert the doubters and bludgeon their way through the barriers to acceptance of voice dictation solutions, Nuance is the strongest contender.  

Backed by Microsoft, it has the financial and technological muscle to bring sophisticated solutions to market. The company also picks its partners well – Nuance DAX is integrated with world-leading EHR vendors like Epic and Oracle Cerner and their massive installed bases. These relationships run deep: Seth Hain, a Senior Vice President of Research and Development at Epic recently said GPT4 had ‘shown tremendous potential for its use in healthcare, and it will be used to help physicians and nurses spend less time at the keyboard and help them investigate data in more conventional, easy-to-use ways.’ Such ringing endorsements reinforce Nuance’s influence and, once it comes to market, DAX Express will enter the field of play on very solid ground. 

Much Ado About Nothing? 

We wrote very recently about the prospects for AI-powered start-ups (see this Insight) in this market. We concluded that they would struggle to compete with Nuance or other leading vendors like 3M and Dolbey. Given Nuance’s snowballing dominance, perhaps the more pertinent question now is how much more of a wedge will DAX Express drive between Nuance and its nearest rivals?  

Much will depend on whether these rivals can leverage technology from the likes of Microsoft and Google via integrations, but that route is complicated as it would require using underlying technology from some of their biggest competitors. 

It will take something momentous to slow Nuance’s momentum. Having said that, DAX Express will not make its commercial debut until 2025, and that leaves the door slightly ajar for others to make their play. We’re also basing this assessment on the promise offered by DAX Express, which is partly based on the company’s marketing and the disruption, excitement and, in some cases, alarm that ChatGPT has created over the last couple of months.   

Could Google be one of the ‘others’ we refer to above? Not to be outdone by Microsoft/Nuance, it launched Bard, its answer to ChatGPT, just days after the DAX news. Google is actively developing products, via CareStudio and other initiatives, to try to streamline clinical note interpretation in the EHR, which it hopes can challenge Nuance in this market. Elements of CareStudio have now been integrated into MEDITECH’s EHR solution, although to-date this has focused on search functionality. However, this provides a potential springboard for Google that could challenge Nuance. Although not confirmed, it is reasonable to assume that Bard will be integrated into Care Studio if Google continues its strategy of enhancing the smart notes functionality of CareStudio. However, Google has only a limited installed base of legacy solutions and any disruptive influence from it, or other big tech, on Nuance and the voice dictation market at large, will be minimal for now. 

Dollars and Sense 

Although buyers and users we speak to are almost unanimous in their belief in the potential of ambient voice recognition, the technology will remain a relatively expensive ‘luxury’ for the foreseeable future, out of reach of many smaller hospitals and primary care practices. While there are myriads more price sensitive marketplace App Store solutions for bolt-on to an EHR, nothing beats the power of EHR integration and the ability to capture unstructured data. Deep integrations with companies such as Epic, and its ‘Hey Epic’ functionality, offer this and strengthen Nuance’s competitive position on this front.  

Cautious Optimism 

Even as DAX Express gears up to enter the market in 2025, and despite the impressive strides Nuance has made in the market to date, sentiment in the wider voice dictation market in 2023 can be best described as cautiously optimistic. 

There is an inevitability about the journey towards fully ambient.  Even those buyers and users that Signify Research has interviewed on this topic via its Decision Maker Research, whose experiences with voice solutions have been less positive to date, almost unanimously acknowledge the technology’s emerging capabilities – whether that’s ambient listening or voice activated querying and searching – or, its benefits in reducing physician burnout. 

Amid the chatter (pun intended!) surrounding voice dictation, expectations were raised to unrealistic levels. The healthcare industry must shoulder some of the blame for falling for the hype and succumbing to peer pressure. 

But perhaps, at last, the hype and hyperbole are justified. In DAX Express and GPT4 technology, Nuance is considerably upping the ante. As it waits at ‘base camp’ ready for its assault to a fully ambient solution, it is proving that, in this case at least, words are speaking as loudly as actions.  

Signify Premium Insight: Ambience Enters AI Medical Scribe Market, but Unlikely to Dislodge Nuance or 3M

A new digital dictation solution hit the market last week with the launch of AutoScribe, a fully-automated, AI-powered medical scribe tool from Ambience. The launch marks the developer’s debut in a dictation and speech recognition market yet to fully convince the healthcare industry of its true benefits.    

If it is to succeed, AutoScribe must break down lingering barriers to software adoption, and prove it can simplify workflows, save costs and, vitally for an industry battling staff shortages and burnout, ease pressure on clinicians.    

The Signify View 

With AI-powered speech recognition at its core, AutoScribe potentially has an immediate advantage over less sophisticated solutions that require more human inputs, assuming it performs as claimed. However, even then it is not the only vendor using AI to address provider pain points in relation to recording encounters. It is a strategy several others, including market leader Nuance, are following. 

However, providers largely remain unconvinced of the wider benefits of voice dictation. Or rather, they see the benefits, but these are outweighed by any number of barriers which have held back adoption. These range from resistance among staff and departments to changing workflows to accommodate new technology, to trust issues around the accuracy of the tool, and more.  

As well as trying to alter providers’ mindsets (not easy), Ambience is also late in entering a highly competitive arena. It is up against heavyweights like Microsoft-backed Nuance, 3M and other developers that already enjoy tight-knit relationships with EHR vendors. Increasingly, big tech is also attempting to compete.  

AutoScribe ticks many boxes for providers, but there are many moving parts here that will ultimately determine its success.  

Barriers to Adoption 

We have interviewed several health system buyers on this topic recently, and the majority confirm that they are interested in improved solutions and would allocate budget for one that could meet all their needs.  

Tellingly, and surprisingly, our discussions also revealed that around 80% of clinicians still type up recorded encounters, and these are manually entered in the EHR.  

This is symptomatic of the lukewarm reception voice dictation software has received in healthcare circles to date. Users often complain that software is slow, and cannot always be trusted – staff still feel compelled to manually check for errors and proof-read transcripts, or transcription is outsourced to third parties. 

There are other, wider barriers to adoption. One is that most providers still just want speech and voice recognition as a ‘plug and play’ add-on to the EHR. But this can hamper integration with legacy EHR systems (more so where IDNs/ACOs and ICSs have multiple EHR systems in use) or proprietary software. 

Then there is ‘cultural’ resistance to change. A clinician might be reluctant to stop using the services of a medical secretary, who do more than transcription and inputting, in favour of the narrow capabilities of technology. Others may be unwilling to adjust established working patterns, especially more senior doctors who may be less prepared than junior colleagues to embrace new technology. 

There is also frustration with alternative solutions offered. One health system interviewee called delays between voice entry and order activation ‘unacceptable’ and said they would implement technology only when the time lag is significantly reduced. Other buyers expect the technology to be part of the EHR package they have already paid for.  

As a result, voice dictation software will not be a top priority for many providers until the technology can match the performance promise. They see it as nice to have (if it works well), but do not see it as a gamechanger. And in the current economic environment, they would rather invest in other elements of healthcare IT.  

Strategic Shift 

So where does this leave Ambience?  

It will take heart in the fact that IT procurement in IDNs and physician practices is becoming more centralised. Historically, different health system departments bought dictation solutions to meet their specific workflow needs, and it is not unusual for a health system to have five or six different solutions. It is no secret that some solutions work better with certain workflows – for example, Winscribe and BigHand are good for clinics and writing letters while Dragon Medical One is better for the direct entry of text into EHR (mainly due to its use of AI).  

However, providers are often tied into long-term contracts with these existing vendors, and cannot easily switch to a new solution. This is another limitation for Ambience.  

But with centralised procurement comes more strategic software purchasing across different settings, and Ambience will argue that AutoScribe aligns well with this trend. 

It will also be encouraged by the fact that 80% of those organisations we interviewed would be prepared to invest in new real time speech recognition software (with most also stating that they have budget available) if the solution met performance expectations. 

Although AI claims high accuracy when capturing clinical notes, coding support (e g ICD, SNOMED, Medication, Reimbursement, Quality Control etc) is high on any provider’s wish list when considering a voice solution, especially in the US reimbursement environment. Very few vendors provide a strong solution for automated coding alongside automated clinical notes/transcription. However, this is where real value can be added in terms of provider workflows. IT buyers we’ve interviewed indicate that this would be a game changer. If Ambience can use its AI technology to support this, it would be in a much stronger position to challenge the market leaders.  

Evolution of Dictation Solutions Toward ‘Fully Ambient Solution’ 

Nuance DAX comes closest in terms of supporting automated coding, and is one solution that Ambience will now be pitting itself against. It is a highly competitive playing field dominated by Nuance, 3M (which bought M*Modal) and Dolby, and where relationships and EHR integrations are paramount. Voice technology/speech-to-text commands between most EHR systems and digital dictation solutions are still considered ‘clunky’. A vendor offering a dictation solution with a good interface with as many EHR systems as possible is at a distinct competitive advantage. 

Nuance has this. Its Nuance DAX tool powers Epic’s Hello Epic ambient listening solution. By contrast, Ambience’s EHR ecosystem lacks the really big-name EHRs, although to be fair its integrations with primary and ambulatory care EHR/EMR vendors AdvancedMD, Dr Chrono, ElationEMR, athenahealth, adracare and eClinical Works are a solid combination. 

Winning Hearts and Minds 

It is not just the IT buyers within provider organisations that Ambience will need to convince of its credentials. Clinicians hold considerable sway with procurement teams, and their opinions carry a lot of weight during decision-making. Even as health systems move towards centralised IT procurement, clinicians will be influential in advocating single solutions across multiple hospital settings. 

There is no doubt that AutoScribe, along with the latest, most sophisticated solutions from other vendors, address some major pain points identified by IT buyers and providers. As health systems seek to reduce costs and plug manpower gaps, AI solutions align well. 

Some buyers we speak to say they are ‘excited’ about ambient clinical intelligence, and are realistic that it will take time for voice recognition to be reliable, add value and be worth the investment. 

The biggest immediate challenge for Ambience will be persuading providers (and particularly clinicians) that speech and voice recognition tools are now a necessity rather than luxury. Prevailing economic conditions are already changing mentalities in this respect and, along with Nuance DAX, AutoScribe might just be a solution that changes the game. 

Ambience nonetheless faces an uphill battle to shake Nuance’s foundations, especially in hospitals where the greater emphasis is on EHR integration. Perhaps it may find more fertile ground, initially, in primary care where providers have more flexibility to choose their real time dictation solution based on their clinical workflows. Costs may be prohibitive for some of these providers, however, but in a market that is only going to get more competitive, this might offer the path of least resistance for now.

Signify Premium Insight: Annalise.ai Enters into Nuanced Partnership

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Medical imaging AI vendor Annalise.ai and Nuance Communications, a vendor which specialises in reporting and ambient clinical intelligence tools, have announced a partnership which will connect Annalise.ai’s diagnostic support solutions to more than 12,000 healthcare facilities currently on Nuance’s Precision Imaging Network globally.

With the agreement, Annalise hopes to gain exposure to a greater number of sites, allowing it to scale rapidly, while Nuance can utilise Annalise’s solution to enhance its growing Clinical Analytics Platform and complement its Natural Language Processing tools.

The Signify View

Medical imaging AI vendors are keen to extol the virtues of their partnerships. While these vendors are often quick to boast that their algorithms are being hosted by one of a growing number of AI platforms, the truth is that these platform providers are sometimes not very discerning. Some platform providers aim to simply give customers the broadest range of solutions possible. Sometimes these are bundled into clinical suites or workflow packages, but the breadth of solutions on offer is usually of paramount importance.

The approach of Nuance, bolstered by its recent acquisition by Microsoft, is subtly different. The partnerships it has fostered do help offer a range of capability to customers, but above that ambition, Nuance has been more discerning, only partnering with vendors which deliver solutions that offer providers significant clinical value. It is essentially only interested in collaborating with the vendors it deems the leaders in any product category. This marks a divergence from its original platform play, which took the form of a more conventional ‘marketplace’ approach aiming to offer a wide variety of tools to the end-user, but that platform, like many of the early marketplaces, failed to gain significant traction.

Annalise.ai, as well as Nuance’s other announced partners, Densitas and Perspectum, embody this ‘quality over quantity’ approach. In the case of Annalise, which can be regarded as a market leader given the sophistication of its comprehensive solution, the clinical value it has the potential to offer and the funding and clearances it has secured, the adoption of a comprehensive solution eschews the need for Nuance to adopt and integrate solutions from multiple providers for the same body area modality combination. Nuance’s orchestration capabilities mean that customers on its Precision Imaging Network can leverage Annalise’s strength to identify a multitude of findings, before findings are pushed to their reporting solution, ensuring they can more readily be utilised in clinical workflows.

Historic Improvements

In addition to this, however, Annalise.ai’s solutions could be used in synergy with Nuance’s strength in natural language processing (NLP). Nuance’s NLP could mine historic radiology reports to identify reports of interest. These reports could then be analysed by Annalise to identify incidental findings. While this would, in the first instance, enable providers to improve patient outcomes, it would also have broader implications, allowing the health of entire populations to be more effectively managed overall.

As well as having a presence in almost 80% of US hospitals (according to the vendor) Nuance’s network connects radiologists, providers, health-plans, self-insured employers, life sciences companies and other imaging stakeholders. The two vendors will hope that this breadth will enable such retrospective analytics to deliver value to providers beyond the clinician, and identify other areas where additional value can be delivered.

This highlights the difference between Annalise and Nuance’s collaboration, compared to other comparable partnerships. Where often vendors in partnerships essentially co-exist harmoniously, Nuance and Annalise hope to collaborate synergistically. Working together they hope to enhance the quality of reporting and efficiently enrich the quality of reports with data directly from the algorithms.

Regulation Restrictions

Wider trends in the medical imaging market also emphasise the potential offered by the partnership. Annalise has, as noted in past Insights, been progressing quickly in Australasia and Europe. However, its progress in the US has been stymied by the US-FDA’s reluctance to approve comprehensive solutions, treating the detection of an individual finding as though it were assessing a separate tool. Such an approach effectively prevents Annalise, which claims its CXR chest X-ray solution can identify 124 findings, from gaining regulatory approval in the US. Resultantly, Annalise has, been forced to break up its solution in a bid to secure approval for smaller subsets of the solution. Further, to accelerate the pace of crossing regulatory hurdles and forge an installed base in the US, the vendor has also been forced to settle for its tool’s use as a triage and notification solution, rather than one that can be used for diagnosis.

These barriers mean that Annalise would be facing a long, hard road to gain ground in the US, especially in the face of other vendors which have gained success with a single solution before expanding out to encompass increased clinical requirements. Partnering with Nuance, and gaining access to its vast installed base, immediately ameliorates that difficulty. The scale of Nuance, as well as its integration into providers’ workflows, means that for the time being, the lack of regulatory approval for detection won’t severely hinder Annalise, enabling it to be valuable as just a triage solution, albeit for a smaller number of its CXR solutions. Further, if the US-FDA does eventually rethink its approach to comprehensive solutions, it will be well placed to dramatically capitalise.

Even at present, though, both companies stand to benefit, while also granting their customers new opportunities. This is particularly true given that Nuance’s workflow integrations will help tackle another of the hurdles facing providers hoping to utilise AI for historic analysis; how to bring the analysis of historic data into current clinical workflows. Annalise needs to be able to access the data harboured by Nuance’s 12,000 care facilities, which depends on that data not only being made available, but also being formatted into a unified manner, where NLP and image analysis can be leveraged.

Patient Finding

The fruits of overcoming this challenging, in private markets at least, can be substantial. Providers connected to Nuance’s network who choose to use Annalise’s solution on their historic data could identify significant numbers of patients with incidental findings, missed findings or even misdiagnosis. In doing so, if these patients can be incorporated into hospital’s workflows, and assigned treatment pathways, they represent additional sources of revenue for providers. By utilising the collaboration between Nuance and Annalise, providers should be able identify patients that will benefit from interventions, which they themselves can charge for, while also improving outcomes for the patient.

Further, the purported access to data granted by the agreement with Nuance will also give Annalise another longer-term advantage, with the vendor being able to utilise the data as it continues to refine its algorithms and presumably expand into other clinical areas, as well as validating its solutions to increasingly convince providers and regulators alike of its merits.

Even with the apparent strengths offered by the partnership, there are several questions whose answers will be revealed over time. How invested in medical imaging is Microsoft and Nuance, for example? One of the motivations driving investment in medical imaging by cloud infrastructure providers is simply to sell more cloud services. This is likely one of the reasons for Microsoft’s acquisition of Nuance in the first place. The partnership with Annalise and other AI vendors will, if successful, aid in this regard, helping convince providers to transition to the cloud. However, Nuance’s heritage and strategy suggests this is not the sole motivation. Another question raised is why Annalise hasn’t developed its own platform? AI scale-ups offering their own platforms is fast becoming a developing trend, and Annalise are well placed to make such a move. However, the opportunity to scale with Nuance is too significant to ignore, especially in the US, and Annalise will hope to use it to “leapfrog” algorithm developers that natively developed platforms.

These are, however, relatively small matters in what is a grander ambition. The volume of platform launches throughout the year has increased dramatically, but against this backdrop, Nuance’s partnerships with Annalise, Densitas, and Perspectum have brought something different. Sophisticated AI solutions, AI orchestration expertise, a large global footprint of potential sites, backed by a global cloud technology behemoth with very deep pockets; a combination which could prove a recipe for success.

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Signify Premium Insight: Amazon in Prime Position with HealthLake Plans

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Last week Amazon made clear its intentions in medical imaging, announcing two new capabilities in HealthLake focused on medical imaging and analytics.

The Seattle-based tech firm says that the abundance of data created in medical imaging is slowing down decision-making in hospitals. In response, the cloud vendor has launched Amazon HealthLake Imaging, which is designed to expedite medical imaging retrieval in clinical workflows, as well as powering existing medical viewers and analysis applications. This, the vendor claims, can result in considerable cost savings.

However, with Microsoft’s Nuanced-derived healthcare expertise, Google’s recent moves into medical imaging, and Oracle’s inherited incumbency via its Cerner acquisition, has Amazon done enough to win the interest of providers?

The Signify View

Tech giants’ interest in healthcare is nothing new. Amazon, like other Nasdaq darlings, has made various approaches to different healthcare markets over recent years, from the launch, and subsequent shuttering of Amazon Care, a primary care service, to its Amazon Pharmacy play. Recently however, several of the world’s biggest tech firms have redoubled their focus, setting medical imaging firmly in their sights. After Microsoft’s acquisition of Nuance, which closed in April 2022 and Google’s recent launch of its Medical Imaging Suite, Amazon has become the latest tech firm to make a concerted imaging effort.

Like Google’s launch before it, the launch of Amazon AWS’ HealthLake Imaging suite is not festooned with brand-new, never-before-seen capability. Instead, many of the tools and partnerships included in the package have been available previously in various guises. However, the new packaging highlights Amazon’s increasing focus on selling cloud services to acute and outpatient providers as interest in, and understanding of the technology increases. While many of the tools have been previously available, it would likely have taken an already knowledgeable user at a provider to capitalise and work out how best the range of tools offered by Amazon could be applied to their own imaging departments. The packaging and positioning of Amazon’s latest effort, however, should help providers more clearly appraise the potential of cloud adoption for their imaging departments, easing the transition for more mainstream providers.

Such positioning, however, is only enough to make AWS more accessible. What Amazon hopes will encourage providers to commit, is its boasts about price. In its blog detailing the new solution, Amazon estimates that HealthLake Imaging helps reduce the total cost of imaging storage by as much as 40%.

The Cost of Delivery

This figure, as is often the case with those used in marketing materials, should be taken with a pinch of salt. No doubt Google, Microsoft and other cloud providers harbour some technologies which are also designed to help reduce the cost of storing images on the cloud. However, the fact that Amazon has publicly stated the savings that providers can expect indicates the vendor’s confidence in its ability to offer providers an affordable option.

Cloud adoption, can, after all be stymied by the cost, or at least perceived cost, of making the transition. While this is less of an issue for flagship academic providers and the premium they are willing to pay to have the latest and most experimental technology, for the acute and outpatient providers, cost is a far greater barrier. If Amazon is to truly capitalise on the revenue-making potential that cloud provision in medical imaging offers, however, this mass market is ultimately where the vendor must target.

By highlighting the cost-savings providers can expect to make if they adopted Amazon’s imaging cloud solution, even if the actual savings delivered are not quite at the quoted 40%, the vendor hopes to overcome the perception that cloud is prohibitively expensive, and at least engage mainstream providers in a conversation.

Even with such savings, cloud could still prove too expensive, depending on the volume, complexity and standards of the data held by the provider, but, crucially, these factors stem from providers’ individual circumstance. Moreover, the shift to cloud for imaging can also require substantial investment in network infrastructure (e.g. local bandwidth) to leverage the benefit of cloud-based performance.  While there will be providers for whom AWS’ HealthLake Imaging product is still too expensive, the advertised and expected cost savings, will likely be enough to convince some providers, particularly when other factors, such as cybersecurity or the requirement to deliver capability across complex outpatient networks, for example, are considered.

Choosing Between Sellers

At present, the key differentiators between cloud providers are still minimal. While different providers may have different strengths, individual niches where they excel and particular partnerships that will ease certain use cases, any of the major cloud providers can, in essence, offer almost the same broad capability in cloud services for imaging. However, despite this comparability, leading cloud vendors are still beginning to better arm themselves and shape their identities in an attempt to build links to certain customer bases. Amazon’s focus on efficiency and the cost savings it offers is one such strategy, a play that, as highlighted, stands to place cloud capability firmly in the reach of acute and outpatient providers.

Other cloud providers also have their own strengths, however. Microsoft’s Azure finds itself in a particularly strong position, largely thanks to its acquisition of Nuance. Most obviously, that acquisition gives Microsoft a direct line to a claimed 77% of hospitals in the United States. However, that acquisition also fits in with Microsoft’s broader portfolio. It is, after all, not difficult to see the possible synergies with Nuance’s Powerscribe solution (and nascent, yet impressive DAX ambient reporting), combined with Microsoft’s ubiquitous tools, including Teams videoconferencing. This could bring ambient listening to all consultations and telehealth visits, leaving essentially every interaction structured and stored on the cloud along with relevant medical images.

Google, meanwhile, may lack the Nuance play that Microsoft can lay claim to, and it may lack the relentless operational focus that Amazon has developed through its commerce heritage, but its expertise in search, AI and broader image analysis, will give its own strengths, making it, for example, an attractive provider for leading academics focused on using their data libraries to develop their own AI algorithms.

Expected Arrival

In most cases though, these are concerns for the future. At present many providers aren’t considering long-term population health-focused imaging data repositories in the cloud, or developing their own AI tools. Instead, most providers are looking to the cloud for improved accessibility, efficiency, security and cost.

With these basics amply covered by all leading cloud providers, at present, which cloud provider hospitals choose is likely to depend more on customer-context, rather than unique capabilities. It doesn’t necessarily matter, for example, if a radiology department harbours a desire for an AWS imaging IT platform deployment if it is part of a large hospital network, which has just agreed an enterprise-wide deal with Azure. Almost all leading Imaging IT software vendors have some degree of flexibility on cloud-provider for hosting their applications, making cloud adoption often an enterprise, as opposed to departmental, decision.

By a similar token, hospitals in regions where there are restrictions on public cloud provision, where there is a preferred partner or a requirement for in-region datacentres, for example, have needs that trump any smaller local preference for individual cloud providers.

Despite these considerations, there is one area where AWS might have an advantage. AWS has arguably worked its way into a broader group of informatics partners (and larger market share) as “preferred” cloud provider, than some of its chief competitors. While some providers will disregard the partnerships their IT vendors have fostered, for many, simply adopting their imaging IT vendor’s preferred cloud provider partner will prove to be the most straightforward route to transition to the cloud, and as such, all else being equal, will be the one that is chosen.

There are some factors that will become increasingly important over time, such as the ability to manage and retrieve unstructured data, the ability to offer analytics so providers can use their cloud resource most efficiently, and even the adoption and ingestion of different data standards from across an enterprise imaging platform. However, in the near term, such subtleties are far from a provider’s priority.

In the near-term one of the main priorities, particularly for many mainstream providers, is cost. As such, Amazon’s claims of cost savings along with its repackaged and repositioned offering may make it an obvious choice for some. And for now, when fresh, first-time opportunities abound, that should be enough for the Seattle-based tech giant to deliver.

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Signify Premium Insight: IBM Watson’s Path From Jeopardy to Jettison

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IBM proved right well publicised industry rumours last week in announcing that it is selling its healthcare data and analytics assets, which currently fall under the Watson Health business.

The assets have been purchased by investment firm Francisco Partners, and include extensive data sets, products, and image software offerings, including the Merge product line and imaging AI products. Financial details of the deal have not been disclosed, although Bloomberg places the value of the sale at more than $1bn.

The deal is expected to close in the second half of 2022. Existing customers will continue to be served by the new independent company, while the current management team is also expected to remain in place.

The Signify View

The news that IBM is pulling out of healthcare might, at first, seem incongruous given that other recent stories have seen tech companies doing the opposite. Last April Microsoft acquired radiology transcription specialist Nuance for almost $20bn, while more recently Oracle announced it was buying up EHR vendor Cerner for close to $30bn. Other rumours, meanwhile, such as those suggesting that Amazon is looking to establish a presence in healthcare with an acquisition, potentially of M*Modal, also contribute to the overall sense that healthcare presents a significant opportunity for tech vendors.

IBM’s divestiture, however, brings its strategy more closely in alignment with its peers than news of a sale would suggest. What has changed is that, like Microsoft, Oracle and others, IBM is no longer trying to capitalise on departmental healthcare, and is seeking to derive revenues instead from the provision of cloud architecture and technical support for AI development, a path that promises a  larger return on investment. As highlighted in our previous Premium Insights, Microsoft’s move on Nuance, and Oracle’s move for Cerner, are deals which, in essence, give the technology firms an expanded customer base in which to sell their core cloud products. IBM will now be able to bring the same focus to the healthcare market as its cloud competitors, providing the architecture and environment for healthcare-specific vendors to develop cloud-based products, without developing and selling imaging IT products itself.

Solving Problems With Spending

This indirect approach to healthcare, which sees the industry simply become one of a number of potentially lucrative markets for IBM’s broader cloud offering, does however represent a marked shift in strategy. In 2015, when IBM launched Watson Health, it almost immediately began buying up companies, including Phytel, Explorsys, Merge Healthcare and finally, Truven Health Analytics, during its first year of operation. Overall, reports suggest IBM spent around $4bn in establishing the new unit, which is, at present, bringing in around $1bn in annual revenue. A figure that shows no significant change compared to the combined revenues of the constituent vendors when they were acquired.

When these vendors were acquired, IBM’s vision was to revolutionise healthcare, and utilise the power of data to solve some of the biggest challenges facing healthcare. These ambitions were never realised. While the vendor has released some innovative technology and enjoyed some small successes, it ultimately failed to live up to IBM’s own, considerable hype. New initiatives, such as Watson for Oncology, failed to live up to expectations and were mothballed.  Not only was healthcare not revolutionised, but IBM seemed, in many instances, to underperform in more established product sectors relative to its competitors. The legacy Merge imaging IT business has hung on to some key customers but has struggled to grow share or win new customers in core markets in the face of stiff competition from vendors such as Visage and Sectra. In emerging technology product sectors, IBM has also faltered. When it launched its AI marketplace, for example, not only was it behind several other imaging IT vendors, it featured algorithms from just five partners. Similarly, with its Imaging AI Orchestrator platform release; with just one confirmed partner and only a small number of other potential partners, the release was relatively underwhelming compared to IBM’s AI promise.

Resultantly, instead of heralding a revolutionary new era in healthcare, Watson Health started to become a disappointing distraction, diverting attention and resources away from IBM’s other interests, even potentially impacting IBM’s reputation. Despite all the original promise and potential, when viewed in such a light it is no surprise that IBM has sought to cut its losses and shed the unit. Although arguably on a more significant scale, IBM isn’t the only technology company to have failed to revolutionise healthcare, with Microsoft, Google and others also having to renege on earlier promises and pull back from well-publicised healthcare investments spectacularly.

Where Next?

As well as highlighting IBM’s strategy, the sale also raises questions as to the future of the divested assets. In this regard, Francisco Partners has several options. One scenario would see the new owner try to succeed where IBM hasn’t. This is unlikely, although Watson Health’s new-found distance from one of technology’s longest-established giants may offer it a new level of agility and freedom to focus, while Francisco Partners may be keen to invest into it. A second option could see Francisco Partners maintaining the vendor as essentially a managed asset. Watson Health’s constituent vendors were, after all, individually successful before they were combined, Francisco Partners may choose to streamline where possible, but otherwise allow its new acquisition to continue delivering revenues, safe in the knowledge that it is relatively secure investment in a stable and saturated market.

A third, more active option, would see Francisco Partners paring off the imaging IT part of the business, which was formerly Merge Healthcare. Not only does this segment sit apart from the rest of the divested assets, Watson Health’s imaging IT business could be an attractive proposition for the right buyer. As well as a market share of around 7% in the US radiology IT market in 2020 (and just under 4% globally), the unit brings a fully featured enterprise imaging solution to a new owner, with platforms to target acute care, outpatient imaging sites, a cardiology solution, the recently released workflow orchestration solution, AI capability and a large amount of valuable data.

Several vendors could be interested in such a package. Intelerad would be among the obvious candidates, with the additional market share taking the vendor straight into the top five of imaging IT vendors in the US. IBM’s technology would also strengthen Intelerad’s offering, creating an opportunity for Intelerad  to retire or replace its legacy PACS component and bolster its larger data management capability, one of Intelerad’s present omissions. Intelerad is also in the midst of a particularly aggressive acquisitive run, having recently purchased Ambra, Insignia Medical Systems, and Lumedx among others. Moreover, IBM has a substantial customer base in the large acute hospital market, an area for which Intelerad has been actively pursuing. With the might of its private equity owners HG Capital, and an obvious appetite for acquisition, Intelerad could be a good match.

The imaging IT market in the US is one which is well-established and saturated, providing very little in the way of organic growth opportunities for vendors. With this being the case, the prospect of an additional 7% market share in the US could also appeal to other vendors. There are a limited number of potential suitors that have both the available funds to make such an acquisition, and the business strategy to acquire and integrate rather than natively build. This still leaves some big names, such as Siemens Healthineers which has been losing share in the US market, or Fujifilm, which may be attracted with the prospect of an instantly increased footprint, or even a smaller vendor, such as Mach7 Technologies, looking to boost its presence and portfolio as possible buyers should Francisco Partners decide to sell. Ultimately, the imaging IT market in the US has long been on course for further consolidation, especially as deal volumes fall, deal sizes increase and contract terms lengthen. Assuming Francisco Partners have been robust in its due diligence and market analysis ahead of the deal, it will know the IBM Merge business line could be a tempting asset for a vendor with ambitions of playing at the top table of imaging IT.

Back to Reality

The sale of Watson Health is the long-expected end to one of the most ambitious projects in imaging IT and wider healthcare. This end was, however, somewhat ingrained in the start. IBM committed to healthcare, but, like some other large tech firms, did so with the boasts and bravado that may please investors but fail to acknowledge the complexity of the healthcare market. Instead of looking at the nuance, the finer detail and clinical intricacy of healthcare, IBM purchased capability and gave itself impossibly broad targets. Making progress in healthcare is hard, it is slow, and what’s more, it isn’t necessarily all that profitable. The humbled IBM will now have a much better appreciation of that.

For the divested imaging IT unit meanwhile, although the future is uncertain, it harbours a lot of value. It has a sizeable market share, competent technology, and continuing development as illustrated by its releases at RSNA 2021. Freed from Big Blue’s orbit, the business formerly known as Merge now has the chance to focus on the detail and the nuance. It may never revolutionise healthcare, but the chance to work on smaller, more tangible problems means that its future could be bright nonetheless.

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