Tag Archives: Cloud

Signify Premium Insight: Annalise.ai Enters into Nuanced Partnership

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. The content is only available to companies that have subscribed to this paid-for service. To view other recent Premium Insights that are part of the service please click here.

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

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: What to Expect at RSNA 2022 – Imaging IT and AI

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Much change is afoot in the medical imaging IT and AI sectors. Imaging IT vendors are transitioning to broader, integrated cloud-native enterprise imaging solutions, while AI vendors are increasing the sophistication and clinical value and utility of their products. Amidst these broader directions, here are our key expectations for the show.

Imaging IT and AI Vendors Will Have Lots to Share

While this year’s meeting of the Radiological Society of North America might be somewhat subdued from a modality standpoint, imaging IT and AI vendors will be ready for some significant product launches. Unlike last year when Covid-19 was still rife in many countries, and there were still considerable restrictions on travel across the world, this year’s event should see attendance figures much closer to the pre-pandemic levels of 2019. Such enthusiasm should see vendors willing to make a lager investment into the show and use it as an opportunity to promote high-profile new products.

Imaging IT vendors will be keen to highlight the progress made in developing fully featured, cloud-native enterprise imaging platforms. In some cases, this will be demonstrating additional capability that has been added to an existent platform, while other vendors may, for the first time, demonstrate how different capability across their portfolios can be integrated into a more complete enterprise imaging solution.

The event is also likely to be busy from an AI perspective, with vendors keen to promote their products’ progression from technology to solution. AI outfits will look to demonstrate new, more sophisticated solutions, which address a greater number of clinical segments and integrate more seamlessly into providers’ workflows.

Efficiency and Optimisation

Between unprecedented backlogs of patients whose procedures were delayed during the Covid-19 pandemic, a shortage of trained personnel in many key roles, and the increasing requirement for more time consuming and resource intensive advanced imaging procedures, providers are looking for ways to do more with less.

Imaging IT vendors at RSNA will be highlighting solutions that offer customers greater oversight of the operation of their medical imaging departments, their staff, and their medical imaging modality fleets. This focus will be reciprocated by providers, many of whom will adopt workflow tools as one of the nearest-term investments to enhance productivity. Such solutions also represent a sensible strategy for providers for the longer term, enabling them to better assess departmental performance, improve planning of patient care, strategize future needs and maximise resource allocation.

This is particularly important as provider networks become more complex, with centralised workflows allowing providers better oversight of increasingly decentralised networks, amidst the increasing utilisation of outpatient facilities and teleradiology service providers. This may also facilitate the expansion of provider networks through increasing acquisitions, and enable more sophisticated tools, which leverage AI, to be deployed. The interoperability offered by these holistic systems will help empower provider networks for increased automation and operational AI.

Platforms, Platforms, Platforms

Despite the greater interest and greater practical utility of AI, the young technology still faces some barriers to greater adoption. One of these barriers is a means to deploy AI into providers’ clinical workflows as providers look to scale their radiology AI offerings. The most visible method of addressing this “last-mile challenge” at RSNA will be through platforms.

Several vendors have already released platforms, including third-party incumbents such as Blackford Analysis and Terarecon, but more recently specialist AI companies, larger medical imaging IT vendors, and even hardware vendors have released platforms that support the use of many different algorithms. While plans from major international imaging vendors and imaging IT vendors have so far had the most momentum, platforms from algorithm developers themselves could also be a prominent feature of RSNA this year.

This excitement surrounding AI platforms is also likely to shape many of the conversations that AI vendors have with one another. In past years, vendors may have been looking to forge standalone partnerships with other AI vendors which offer complementary solutions in a bid to offer providers solutions more clinically valuable than either partner could supply alone. While that may still make sense in some use cases, in other cases some of the more established AI independent software vendors will look to forge partnerships with multiple prospective partnersto facilitate the development of a platform and scale their radiology AI offerings. This is especially true given that vendors are increasingly focused on enhancing their product capabilities natively, rather than leverage third parties, as may have been more prevalent in previous years.

The Consolidation of Data

One of the longer-term strategic directions that is set to shape imaging informatics over the coming years is the consolidation of data.

As imaging IT vendors’ multi-ology enterprise imaging strategies evolve, there is a greater need for enterprise-wide data to be consolidated into a central data management platform or the VNA. Doing so will enable providers to better leverage the breadth of data they have. While data management platforms are not a conceptually new product, vendors are beginning to assess how providers can leverage the centralised platform and explore the potential they offer. As such, there are likely to be few flashy announcements associated with the VNA. Instead, vendors will, behind the scenes, be discussing it with their customers to identify opportunities that could be realised.

This will be particularly true given the wider context affecting providers at present. The lasting impact of the Covid-19 pandemic, along with other economic pressures, such as rising inflation and spiralling energy costs mean that hospital budgets will, in many instances, be getting tighter. In such circumstances providers are going to be increasingly keen to monetize the data they have already. For providers, this could mean utilising their wealth of patient data for clinical trials or drug development, for example, or utilising their imaging data to develop AI in house. For this to be a realistic possibility, vendors need to respond and offer sophisticated platforms that properly structure and curate data in formats that allow for the commercialisation of imaging and non-imaging data, including deidentification of patient information for pre-clinical use.

There has already been progress on this front. GE HealthCare’s partnership with Enlitic, for example, emphasises this curation, while Intelerad’s recent acquisition of Life Image also shows that it is an emerging trend in the imaging IT market. While there may not be any blockbuster announcements, vendors will be keen to highlight the importance and potential of these unified data management platforms to prospects at the show.

AI Beyond Radiology

So far, the primary focus of the majority of medical imaging AI has been radiology. However, as AI is maturing, and many radiology AI solutions are becoming more sophisticated, medical imaging AI’s domain will expand beyond radiology. This will see the technology’s purview increasingly grow into adjacent areas such as population health tools that may be deployed as part of screening programmes or identifying incidental findings as part of routine clinical practice.

Such moves, forming key discussion topics for AI vendors at RSNA, represents AI’s growing maturity, and the evolution of AI algorithms into more sophisticated solutions. Such momentum stems from two distinct sources. Firstly, this evolution represents vendors’ need to continue to develop their products to create ever greater value to radiologists, and in return, drive commercial traction. More interestingly, however, is vendors’ plans to tap into the current wave of Category III CPT codes awarded for quantitative imaging AI solutions, which could be indicative of potential future reimbursement.

Many of these CPT codes announced for 2022 do not focus on the traditional domains of radiology AI such as detection and triage, but instead seemingly promote population health applications. This emphasis will entice vendors to position their solutions to leverage these codes in the hope that over the longer term they are upgraded to qualify for tangible reimbursement. But, such leanings also raise the expectation that more population health-focused codes are expected in the coming years, thereby encouraging vendors to increasingly develop population health solutions, or adapt their current solutions to fulfill a population health remit.

Summary

Medical imaging IT and AI markets are evolving quickly, and the RNSA conference allows vendors to, above all else, highlight their progress in several key areas. Of equal importance, however, is what isn’t on display, but what is said. Many providers will be looking to commit to enterprise imaging solutions, cloud strategies and AI adoption over the coming years, and vendors’ presence and messaging could help to influence their approach. Ultimately, vendors have the chance to explain to these providers how the application of their solutions can solve pertinent problems in radiology and beyond.

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Signify Premium Insight: Google Searches for Imaging Success

In its most high-profile bid to capitalise on the medical imaging market to date, Google has launched a new cloud-based medical imaging suite.

The suite is comprised of several tools, centred around Google Cloud’s image storage and Healthcare API suite, including NVIDIA’s MONAI for AI annotation and automation, BigQuery and Looker to help providers better navigate imaging datasets and Vertex AI to help accelerate the development of scalable AI models. Google says that by offering these tools in one product, it hopes to make diagnostic data more accessible and interoperable, while also readying providers for the development and implementation of artificial intelligence programmes.

While there has been significant promotion of the new suite, many of the tools were already available individually. What, therefore, does the launch really have in store?

The Signify View

Some well-justified scepticism will no doubt surround Google’s launch of its Medical Imaging Suite. The company has looked to expand its role in healthcare beyond feeding the imaginations of hypochondriacs several times, introducing Google Health in 2008 and discontinuing it in 2012, before rebooting it in 2018 and dismantling it again in 2021. It has, in the past also looked to develop front-line AI tools from its DeepMind division, consumer health products via its FitBit acquisition and apps for medical research among others. None of these tools, however, has yet made the significant, lasting impact that was expected by one of the world’s best-known firms.

Despite the sometimes inconsistency of these attempts, however, the company has been making headway in medical imaging with another, broader part of the business.

The adoption of cloud capability in medical imaging is still nascent, but some cloud providers, including Google, have become trusted partners for many earlier adopters. While Amazon Web Services (AWS) and Microsoft’s Azure are the public cloud providers that have seen the most uptake in medical imaging so far, Google Cloud, having reached some significant agreements with notable imaging IT vendors such as Visage, and Change Healthcare, as well as some notable and well-respected providers such as Mayo clinic, is hot on their heels.

Despite this, however, the Alphabet subsidiary’s presence in the market has been less visible compared to that of Azure and AWS. The launch of the Google Cloud Medical Imaging Suite highlights an end to this quiet and heralds the start of a more aggressive approach.

Remaining Relevant

Making such a transition has become increasingly important for the cloud provider. While Google has made progress, as AWS and Microsoft begin to pull away, Google misses its window to capitalise on the first phase of medical imaging cloud adoption. This is particularly true as Microsoft begins to capitalise on its Nuance Communication acquisition, for example, while Amazon continues to leverage its already extensive list of AWS partners.

Google will not countenance these advantages overnight, particularly given that on the face of it, its Medical Imaging Suite, which no doubt will be preferred by some customers with some specific use cases, is not a revolutionary leap. It may offer some advantages, but there is nothing truly ground-breaking that stands as a major differentiator compared to AWS or Microsoft.

That isn’t to say that there aren’t any aspects that aren’t attractive. The emphasis Google has placed on its AI offerings, for example, could swing some providers in its favour if they are looking to capitalise on their medical imaging data and facilitate its use among AI developers or indeed develop their own tools in-house. Its reputation for AI development could, in some cases aid its cause. This is especially true as many of the customers which have chosen to use Google public cloud are highly influential academic hospitals.

Reputation Management

Reputations work both ways though. While Google holds a staunch reputation for technical prowess, there are other factors that may give potential customers pause for thought. Chief among them are several high-profile incidents and agreements surrounding Google and identifiable patient data, including data from the Royal Free NHS Trust in London, and a deal with US healthcare provider Ascension. In these and other cases, Google’s actual culpability is somewhat moot, with the shadow of data insecurity, even if entirely unjustified, potentially enough to push a would-be customer in the direction of one of Google’s competitors.

Another concern for any potential customers considering turning to Google for their cloud provision is the vendors’ long-term commitment to medical imaging. While the more general aspects of Google’s cloud offering will continue to be supported, Google’s repeated high-profile salvos into healthcare, and the associated withdrawals, give the impression of a vendor that has no compunctions about pulling out of a market, reorganising its business units and ending its involvement in certain segments with little notice. Such an assessment may be unfair, particularly given that other cloud providers including Microsoft and IBM have both made equally high-profile pushes and retreats from some healthcare markets, but, with cloud representing a long-term investment, such concerns may weigh on decision makers’ minds when it comes time to signing on the dotted line.

These spectres are not impossible to exorcise, however. Google along with its peers are increasingly forging partnerships with imaging IT vendors in order to effectively create a joint sales strategy. Cloud providers, alongside vendor partners, are combining their efforts to sell to hospital networks, enabling the partners to highlight the benefits associated with a public cloud deployment, while also utilising the expertise from the imaging IT vendor in radiology.

Broader Responsibilities

Such evolution in sales strategy is also being mirrored in service provision. Along with the broader medical imaging market, deals are increasingly transitioning to managed service agreements. In terms of cloud deployments this is beginning to manifest as public cloud providers managing deployments much more closely, with for example, infrastructure and costing falling under the cloud provider’s remit.

Whether any of these factors are enough to sway a decision towards or away from Google, and indeed what influence they ultimately have on a providers’ choice of public cloud vendor, is still overarchingly dependent on individual deal context.

Google’s new Medical Imaging Suite will make the firm’s solution more attractive to many vendors, but any advantages will likely be overshadowed by much more significant influences. A deal’s locality, for example, may be a far more important factor in a provider’s decision if that provider is in a country which stipulates that cloud providers must have datacentres within-region, for instance, or if it is in a market sector that already has a preferred supplier.

As such, there are in most cases considerations far more significant than the differences between comparable cloud competitors. That, however, does not mean that Google’s latest efforts do not represent a significant step.

While the launch of its Medical Imaging Suite is unlikely to reverse the lead that AWS and Microsoft’s Azure have for public cloud departments, it does show Google’s intention. It highlight’s the vendor’s ambition in the space and lays the foundation upon which it can build over the coming years. Moreover, the launch also enables Google to remain competitive as other cloud providers such as Oracle and IBM which have already made their intentions clear, begin to more aggressively promote their own solutions.

Or, to put it another way, Google’s launch ensures it remains on the first page of search results, but, it has not yet offered anything to warrant rapidly climbing through the rankings.

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Signify Premium Insight: Sectra Believes Future Success Lies in its Genes

Last month, Sectra revealed that it is launching a new business unit to drive innovation and develop new products within the area of genomics. The Swedish enterprise imaging vendor will, in the future, extend the capability of its diagnostic platform to integrate genetic information. This multidisciplinary approach, the vendor hopes, will enable improvements in cancer care and increasingly allow providers to deliver on the promise of precision medicine.

Sectra also announced a collaboration with the University of Pennsylvania Health System, a partnership initiated to facilitate the vendor’s development of an effective clinical IT solution for the new unit.

The Signify View

Healthcare technology vendors have, for several years, discussed the benefits that precision medicine will be able to offer. Those in the industry have promised more personalised care, enabling doctors to make better decisions about treatments, ensuring they are optimised for individuals and ultimately promising better outcomes for patients.

All too frequently, however, such ambition has resulted in precious little material benefit, with precision medicine, for the most part, remaining an ambition rather than a reality. Sectra’s new initiative in genomics aims to address this shortcoming, and improve the discipline’s utility in clinical care. By adding another layer of clinical information into a provider’s enterprise imaging platform, and enabling genomic data to be used alongside radiology and pathology, Sectra hopes to improve diagnosis and treatment of complex diseases, including, as one of the first focuses of the advancement, cancer.

This has been an expected direction of the market for some time, and was highlighted as one of the upcoming areas set to be integrated into enterprise imaging in Signify’s Imaging IT Core Report – 2021:

Sectra is among the earliest vendors to commit to such integration, although others do also note their longer-term interest in the space, harbour isolated sequencing platforms or have made moves on the research, rather than clinical use cases. For Sectra, this grants a potential early advantage in the clinical market, which it hopes to capitalise on as it has done in digital pathology; an area which it has already successfully integrated into its EI platform.

Experiential Experimentation

To make this integration useful, however, will not be easy. Unlike many other adjacent areas which have been integrated into EI solutions, many providers have no legacy of utilising genomic data alongside medical images. As such it would be easy for Sectra to focus on less important genomic information, or attempt to integrate too much genomic data, resulting in an abundance of erroneous information and a subsequent slowing of diagnosis. For this reason, the Swedish vendor’s partnership with Pennsylvania State Hospital is sensible. It offers the opportunity for Sectra to take guidance from a top academic hospital and refine its solution accordingly.

This is in addition to the considerable technical barriers that any enterprise-wide genomics implementation will present. Chief among these is the sheer volume of data created by genome sequencing, with each human genome sequenced approximately 120GB, orders of magnitudes higher than other types of medical image. As highlighted in several past Insights, imaging IT systems will, over time, shift to the cloud, so it makes sense that a new business unit established by Sectra is cloud-native from the outset, but this also offers considerable challenges. Aside from the cost of storing such a potentially enormous volume of data, the vendor will have to develop an effective strategy for managing this data.

In typical cloud deployments, Sectra works in partnership with public cloud vendors which host the data, while the Linköping-based company manages the service element of the deployment. For genomics, Sectra will need to work with both the providers and public cloud vendors to ensure the cost-effective management of storage, discovering which parts of genomic sequences need to be accessed regularly and therefore benefit from the more-costly “hot storage”, and which sections can be relegated to cheaper “cold” or “glacial storage”.

The work Sectra is doing with Penn State University will help inform this process, but the inexperience of both Sectra, and providers themselves, will make effective implementation of genomics data into EI workflows challenging, not to mention the overall burden such an implementation can place in terms of network infrastructure and load on the broader performance of the network.

Time to Grow

Fortunately for Sectra, these challenges do not need to be dealt with immediately. The integration of genomics into enterprise imaging platforms is, most likely, several years away from a commercial launch, so the vendor has time to work with Penn State University and any other partners it may make to refine the service.

Sectra would also be wise to take a sensible approach with regards to not over committing itself. When integrating other areas such as digital pathology into its enterprise imaging platform, Sectra was careful to focus on areas in which it harboured expertise, focusing on the viewer and the ability to visualise pathology slides alongside radiology imagery for effective collaboration. They, in essence, focused on developing the architecture which allowed the vendor to bring in pathology data and enable doctors to usefully interact with it, rather than focusing on the minutiae that other, niche best of breed vendors are likely better equipped to manage.

A similar approach is likely to be taken in genomics. Sectra will allow specialists to provide the research foundation that underlies the value in utilising genomic sequences in patient care, while itself providing the architecture for that foundation to be leveraged in a clinical setting alongside medical images and other sources of diagnostic information.

In such a way, Sectra will be able to expedite the commercialisation of its genomics products. This could help the vendor win mindshare and, ultimately, custom at leading academic and research hospitals. For these sites, genomic integration will not, at present be a deal breaker. But, given the length of medical imaging IT contracts, and the lengthy development processes effective integrations can take, Sectra’s early move and public road mapping could appeal to leading providers as they begin to consider their approach to the inevitable adoption of genomics.

When Delivery is Due

Over time, depending how efficiently other enterprise imaging vendors can develop and commercialise their solutions, a similar impact could be felt at more mainstream hospitals and provider networks, as they themselves begin to consider their options. Now Sectra has launched an opening salvo, other vendors who don’t want to fall behind must react. They do not need to develop solutions immediately, but they should at least begin to convey their plans to their customers, giving providers the confidence that when genomic integration is more mature, their chosen vendor will be ready to deliver.

In the meantime, Sectra must be careful to avoid spreading itself too thinly. Targeting cutting-edge segments and working with prestigious academics gains mindshare and helps reinforce claims of technical prowess, but the vendor must not take its eye off more lucrative deals. Opportunities to displace rivals are few and far between in imaging IT, so the vendor would be loathe to miss a lucrative contract with a large provider for the sake of a development project. Moreover, on the tail of some big marquee wins for EI that are going through implementation and additional phases of go-live, Sectra does not want to risk damaging its reputation for strong client service and support.

That aside, the move represents a sensible strategy for Sectra. The vendor is, and will become increasingly, disadvantaged compared to some of its larger peers due to the limitations of only offering software, as managed service deals including modality hardware proliferate. By innovating in adjacent areas, Sectra is somewhat able to offset this, claiming for itself more significant mindshare, and market share than it might otherwise warrant. There are challenges, as an early mover. Sectra doesn’t have the benefit of learning from another’s mistakes as will help other vendors in the future, and the returns on its move will not be enjoyed for several years to come, but, by helping to bring the abstract into the concrete, the Swedish company has now laid for itself a clear path to follow.

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