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Signify Premium Insight: Imaging IT and AI Predictions for 2022

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Co-written by Amy Thompson, Dr Sanjay Parekh & Steve Holloway

A new year has arrived. Despite the numerous new releases and innovations throughout 2021, and vendors laying foundations for longer-term technological shifts, vendors enter 2022 under similar circumstances to 2021. A new variant of Covid-19 is sweeping the world, causing disruption to both healthcare services as well as the wider economy. Providers are looking for efficiencies and must find ways to address the enormous and ever-present backlog of patients, while vendors must raise their eyes and continue to deliver on longer term strategies, without neglecting providers’ needs of the moment. Despite this uncertainty, however, there are several key trends and developments we can expect to see in the coming year.

Vendor focus will intensify on structured data aggregation 

Vendors and providers alike are increasingly understanding the potential that clinical data offers healthcare. This is true not only in a singular department such as radiology, where the use of data has, in the past, primarily focused, but throughout the wider clinical workflow, including in preclinical and clinical research, companion diagnostics and precision medicine.

To realise this potential there must first be progress in several other areas. One of the most pressing challenges will be getting standardised and machine-readable data from the radiologist reports and automating the population of the findings into the clinical workflow in the first place. Structured reporting tools will help facilitate this inclusion of standardised diagnostic data into the clinical workflow. Over the course of the coming year, vendors will continue to develop structured reporting technology, either in house, or through partnerships that help lay the foundation for a greater role of data in diagnosis. Further, data management platforms will continue to technically evolve, focusing not only on image management, but broader structured “holistic” data management of images, annotations, reports and clinical documentation.

Federated learning also looks set to be increasingly adopted by vendors. This will enable AI developers to create generalisable AI solutions without the need to host third-party data. As such, federated learning will enable AI developers to leverage healthcare providers’ local data to train their algorithms without that data leaving hospital infrastructure. This means that algorithms can be trained on larger and more diverse datasets that are more representative of local case mix, ensuring that the algorithms have a high sensitivity and specificity.

Thirdly, a host of new partnerships will be made between imaging vendors, healthcare providers and the pre-clinical sector (clinical trials, CRO’s, pharma). Demand for Real World Evidence (RWE) to support a new era of drug-development and companion diagnostics will present new commercial opportunities to leverage the vast datasets held by imaging vendors and providers alike.

 Pathology will play a greater role in medical imaging IT

The longer-term direction of medical imaging IT systems to fully fledged enterprise imaging solutions is well understood, but so far, the number of solutions that have expanded beyond radiology and into other departments is minimal; the combination of radiology and cardiology has been the primary example from vendors when displaying multi-ology functionality. This will begin to change in 2022, with digital pathology becoming a focus area for many vendors and where significant progress will be made.

Digital Pathology is being adopted in three ways: primary diagnosis, supporting pathologists’ primary reading and reporting; secondary use, including clinical consult, tumour boards and medical education; and preclinical use, in research, clinical trials and drug development. Adoption has been ramping up significantly in preclinical use. However, the limited deployment of primary use systems pre-Covid limited the scope for secondary adoption and integration into enterprise imaging.

The advent of the global Covid-19 pandemic has dramatically shifted provider focus. There has been much greater investment in diagnostics and the digitalisation of pathology with the inefficiencies of lab processes highlighted during the pandemic. Furthermore, loosening regulation for primary use in the USA has opened-up the largest market globally, while VC/PE investment in digital pathology reached record levels in 2021.

For imaging vendors, digital pathology will increasingly become a key topic and differentiator in enterprise imaging deals in 2022. For the majority, offering primary use applications will only be tenable via partnership, so we expect to see more deals announced between imaging IT vendors and specialist digital pathology vendors in 2022, following in the wake of announcements such as that of Fujifilm and Inspirata.

Furthermore, we expect to see more focus on bespoke workflow tools that support the use of pathology data and reports in radiology, as well as broader multidisciplinary workflows (e.g., tumour boards and alike). Fundamentally, most healthcare providers in mature markets are still early in terms of primary and secondary use adoption of digital pathology. However, most are looking to leverage existing and future investment in enterprise imaging where possible to deploy an integrated offering that can support access to digital pathology and integrate a primary diagnostic offering. Therefore, vendors must be prepared with a clear roadmap for how to address this need for enterprise imaging capability to support secondary use, while also supporting primary use system integration. With many prominent EI deals due for renewal or tendering in 2022, competency around digital pathology could be a dealmaker or a deal-breaker.

 AI product categories will blur as Imaging IT vendors increasingly control channel

AI is still a very young market within medical imaging. As such, the technology itself as well as its application and use are evolving quickly. Leading AI tools have already progressed from being single point solutions which assess a medical image to identify a single radiological finding, into more complete and more mature solutions which offer greater value to providers. At present these more sophisticated solutions may be categorised into one of three categories, which exist alongside advanced point solutions, such as FFRCT:

– Comprehensive solutions that can identify many findings on an image and make a more meaningful difference to a radiologist’s workflow than single point solutions, whose clinical value is often limited. Additionally, they may pick up secondary or incidental findings that the radiologist may not even be actively looking for, avoiding missed diagnoses.

– End-to-end solutions, which offer care coordination and solve problems along the length of the clinical workflow, adding value beyond the diagnostic slice, for a given clinical condition such as stroke care.

– AI body area suites or workflow packages, typically provided by imaging IT vendors, which curate multiple native and third-party AI tools and other capabilities

These are currently well-defined categories, but over 2022, the distinctions between these groups will become less clear. Comprehensive solutions will begin addressing providers’ requirements outside of the diagnostic portion and expand into care coordination and clinical decision making. Third party platforms and marketplaces will combine more specialist tools from vendors into suites that are able to address many different aspects of a high value use case, by combining several single-use solutions. Workflow packages will expand beyond single use cases, creating greater value solutions for radiologist.

Beyond this evolution of the solutions themselves, however, 2022 will also see imaging IT vendors taking a more central role in the deployment of AI and enabling its broader use. This will see these vendors expand comprehensive solutions to take on an end-to-end approach. In addition to image analysis capabilities, imaging IT vendors could also leverage worklist triage, structured reporting, advanced visualisation and other workflow components in more cohesive packages creating further value for the radiologist.

 AI tools will not be sold on the basis of their technology

Until recently, medical imaging AI solutions have advertised themselves based on their use of machine learning technology and accuracy. However, in a transition that will accelerate and become more prevalent in 2022, the focus will be instead on the clinical advantages of the products. AI developers will, instead of selling a technology, highlight their solution’s ability to solve problems for providers.

Providers are becoming more knowledgeable about AI, and the number of vendors offering AI solutions has increased dramatically over recent years, so highlighting a solution’s machine learning credentials alone is no longer enough to differentiate a product in the market. Instead, vendors are having to highlight the overall value they can bring to a provider. This is a challenging task in many cases, especially as many providers currently do a poor job of measuring clinical and diagnostic outcomes accurately.

This has been seen already in stroke care, for example, where some vendors have moved away from touting the technical performance of their stroke detection algorithm, and instead positioned themselves as stroke care vendors by creating a care coordination platform, emphasising their capability across the entire stroke care pathway. Crucially, the importance of the technical specifics of these stroke care vendors’ algorithms have been displaced by a metric that providers are much more interested in; a solution’s ability to deliver the best outcomes for patients.

This trend will gather pace over 2022 and will be prevalent across acute (e.g., pulmonary embolism) and chronic (e.g., oncology) use cases. While algorithm developers will be keen to show that they are able to integrate into medical imaging departments with more thorough solutions, other companies such as marketplace and platform providers will also look to better meet providers’ needs. This need to offer solutions that solve vendors’ problems mean that partnerships continue to proliferate as AI vendors are too small or too specialist to offer the broader clinical capability to providers look to partner to bolster their value proposition.

Operational workflow’s importance will only grow and increasingly influence business models

There were several releases of operational workflow tools in 2021 as imaging IT vendors sought solutions that could improve the efficiency of their customers. These vendors have focused on developing solutions which grant providers better oversight of the operation of their medical imaging departments, their radiologists, and their fleets of medical imaging equipment. The continuing development of these solutions will allow these providers to attend to more patients and more precisely manage their patient’s care pathways.

The development and inclusion of these tools are, in the longer term, also set to give providers better oversight of their departments and generate data about their operation, which will lead to better planning capability, and improve their ability to strategise. This will become particularly important as acute providers utilise teleradiology or outpatient imaging centres for additional reading, or as provider networks grow through M&A activity and visibility over multiple sites is required.

To make the most of this demand for operational tools from providers, vendors will focus on ensuring their solutions are, for the most part at least, vendor agnostic. This will enable these vendors to sell their solutions into any provider, regardless of which other imaging IT systems they use, and grant the vendor an entry point into providers served by competitors. However, the incumbent imaging IT vendor is still best placed to offer providers the richest feature set, making it the most likely to be chosen by providers.

The importance of such solutions will be highlighted in 2022, but different vendors will take different approaches. Vendors which specialise in imaging IT and are targeting the development of enterprise imaging systems will focus on worklists, triage and departmental or operational analytics, while the vendors which also offer hardware will ensure that the use of their modalities, particularly those that are more time consuming such as MR and CT, can be optimised and departments can maximise the use of their resources. These vendors will look to hone functionality such as virtual image acquisition, automatic patient position and protocol efficiency.

The intensified focus on workflow will also present more opportunities for layering on professional services to operational workflow deals, placing vendor specialists within a provider organisation to support improving operational efficiency and workflow evolution. This will be the first step towards tighter vendor-provider relationships and the advent of contracting and business models based on specific performance indicators and operational targets. While a significant risk for the vendor, providers are already coming round to “performance” focused contracting, thereby ensuring a level of service and operational competency while de-risking capital investment. Therefore, providing analytics and workflow tools that identify inefficiency within radiology service-lines will no longer be enough, providers will expect their vendor partners to help solve these problems and support more efficiency care delivery.

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Signify Premium Insight: Rads to Take the Lead in Visage’s Videos

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Among the Imaging IT vendors announcing new capability at RSNA was Visage Imaging, which announced the inclusion of radiologist video reports as a standard feature included in the latest version of the Visage 7 Enterprise Imaging Platform.

The update is focused on facilitating the communication between radiologists and patients, enabling them to record a report of approximately one minute in length in order to explain key findings to patients in “plain speak”. However, Visage has stressed that these reports aren’t designed to be comprehensive in nature, nor are they meant to replace the traditional radiology report for referring physicians. According to Visage, it is easy for radiologists to create the videos, which can include 2D and 3D image manipulations, directly within Visage 7, while patients are able to access the video reports at home or on mobile devices via their electronic health record.

The Signify View

The role of the radiologist has always been conceptually very simple. While the profession requires a great deal of knowledge, skill and insight, radiologists are fundamentally tasked with interpreting medical images and passing their findings on to other physicians. If Visage’s new feature gains traction, this job could undergo an essential change and radiologists may also be charged with explaining their findings directly to patients. Forcing radiologists away from the learned language of radiology, and the comfort of its specificity and clarity may prove difficult for some. This reshaping of a radiologist’s role and the challenges it presents, is not necessarily a problem for Visage and the providers that it will serve, but that is also dependent on how much of a difference the additional feature makes. The development of the video reporting concept was made in partnership with a specific customer, NYU Langone, but now Visage believes it is viable in other customer settings. Several vendors in different areas are focusing on improving patient engagement. In doing so, and by keeping patients more involved in their treatment, they hope that patients can be more invested in their own care, avoiding appointment no-shows and avoiding unnecessary care, for example, and resultantly enjoy better outcomes. Visage will hope for similar benefits in making radiology reports more accessible to the patients themselves.

As much as these video reports could offer clinical advantages, they could also improve a patient’s care experience. With the growing trend toward outpatient imaging and the proliferation of smaller imaging centres all competing for a patient’s patronage, this is an important consideration. If patients feel comfortable, valued and involved in their diagnosis, they are  more likely to return to, and recommend an imaging centre and radiology group, whether that is selecting one outpatient centre over another, or an outpatient centre over a larger IDN. This could be particularly pertinent given the increase in telehealth adoption during the coronavirus pandemic, with patients becoming more used to accessing healthcare on their phones or computers. Payers are also increasingly aware of the higher costs of in-hospital imaging versus outpatient settings (exemplified in the recently announced study from John Hopkins: Commercial Negotiated Prices for CMS-specified Shoppable Radiology Services in U.S. Hospitals: Research Letter).

It is unlikely this capacity for improved ‘customer service’ alone will be enough to make providers choose Visage’s imaging IT software over competitors, but it will add another measure to the balance. This will be particularly true if imaging centres find they can charge patients an additional fee for a video report.

Setting the Stage

The success of video reporting may also depend on the setting in which it is used. The functionality has been developed and tested at a provider known for its preference for multimedia-enriched radiology reports. Academic providers such as this have the resource and inclination to incorporate such reporting developments, but for other providers the demands placed on radiologists may be too great.

With acute and worsening shortages of radiologists in many countries, and general increases in both the volume and complexity of medical imaging, expecting radiologists to devote an additional two minutes to record a video report may prove unfeasible. These two minutes would be particularly impactful on less complex images that are more quickly read. Guidance from the Royal College of Radiologists in 2012 suggests radiologists could (with no confounding factors) read 3-6 CTs or MRI scans per hour. An additional two minutes to record a video report on each of these scans would therefore represent the loss of almost one hour of reading time per day.

A Star Upstaged

Another challenge facing the adoption of video reports is that it could somewhat undermine the role of the referring physician. Presently, the referring physician interacts with the patient, explains his condition, details the radiologist’s findings, conveys details of his case, and addresses the patient’s concerns and questions. Increases in the prevalence of video reporting could somewhat devalue the role of the primary physician, with the radiologist breaking down findings for the patient. This could also be the root cause of some issues further down the line.

These could be as simple as disagreements or inconsistencies between the radiologist and the referring physician, if the referring physician has additional or supplementary information about the patient’s lifestyle, for example. More seriously, it could open a provider up to legal challenges. Language in radiology reports is, by necessity, subject specific, mostly very precise and unambiguous. Common language, in contrast, can be vague, have multiple meanings and be figurative or rich in analogy. Such ambiguities could leave a patient uncertain as to the severity of a diagnosis or unclear about the prognosis, potentially leaving a provider open to lawsuits and litigation.

The Critic’s Choice?

Despite these headwinds, there is still intriguing potential for video reporting. Perhaps it will not be suitable in all situations – receiving news of a terminal cancer via a video on a mobile phone, for example, is a possibility that doesn’t bear thinking about. But for the right provider, if the technology is handled sensibly and utilised carefully, and radiologists given the right training, the innovation could be a powerful competitive differentiator. Patients could be bestowed with a feeling of control over their care and ultimately given a far better experience.

What’s more, the inclusion of video reporting shows that Visage remains willing to innovate and, alongside advanced academic partners, is both trying to push enterprise imaging forward, while also supporting innovation in radiology. Developments such as video reporting may not gain traction and be forgotten as a novelty, but, Visage’s willingness to explore it ensures that it retains mindshare far larger than its market share warrants.

Alternatively, video reporting could prove popular and win the vendor business. Given the comparatively low technical barriers, other vendors would surely add the functionality to their own products. Video reporting could, in time, become a standard feature, patients could become more engaged and the role of radiologists could be fundamentally changed forever.

The reality, as is usually the case, will likely fall somewhere between the two extremes, but the potential rewards mean that Visage would be remiss not to take the chance.

 

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Signify Premium Insights: Structured Reporting – Radiology’s Most Overlooked and Undervalued Opportunity

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here.

Co-written by Amy Thompson and Steve Holloway

Limited radiologist resource has been a long-standing industry concern. While there are an increasing array of products and technologies that are available to offer significant efficiency and workflow improvements to the radiology workflow, some have enjoyed far less commercial traction than their capability warrants. As detailed in Signify Research’s latest report from its Imaging IT Market Intelligence service, structured reporting is one such innovation.

Structured reporting offers radiologists and healthcare providers numerous benefits. By using structured reports, radiology departments can improve the efficiency of their reading and standardisation of report content. The removal of ambiguity in reports supports collaboration across teams and supports improvements in care quality, an ever-greater priority as providers form multi-disciplinary teams to facilitate better patient care and diagnosis.

Beyond improving reports the adoption of structured reporting will also help bestow healthcare providers with a wealth of clean, standardised healthcare data that can be used to improve and develop new diagnostic techniques. As this quantity of data available to providers grows, there will also be opportunities to support the use of precision medicine or further develop and refine AI algorithm development. These benefits will become greater as providers adopt structured reporting at scale, with full enterprise-wide deployments necessary for the maximal advantages to be realised.

Using structured reporting can also have a positive impact on providers’ finances too. Adoption of the technology can, for instance, reduce the risk of missed revenue associated with incomplete reports. More simply, the adoption of structured reporting will also help providers to operate more efficiently across diagnosis and treatment, and as such, save providers’ resources. The potential of federated diagnostic data, enabled with structured reporting, also has substantive commercial value to providers, with the pharmaceuticals and clinical trial sectors especially interested in obtaining high quality, annotated radiology data.

Slow to Bite

Despite these advantages and the potential of the technology, adoption has so far been sluggish. This is, in short, because customers have been slow to demand structured reporting, making it a lower priority for imaging IT vendors to advance past voice recognition or basic reporting templates. There are also some more specific barriers such as the lack of national frameworks for reporting standards, overcoming traditional free-form reporting culture within radiology and the relatively complex integrations required to embed structured reporting across all radiology reporting workflows.

Best of breed vendors and some imaging IT vendors have started developing advanced structured reporting tools using integrated AI and NLP technology to support “no-click” report generation to  overcome these barriers. However, from an imaging IT vendor’s perspective, the customisability and complexity of such tools mean they are relatively demanding of resource to develop, implement and deploy. This is exacerbated by the lack of a standard framework of how reports should be structured, therefore each customer requires the product to be reconfigured. For a midsize vendor, this requires R&D technical investment that it can ill afford to spend, especially when broader focus and resources are increasingly geared towards bidding for larger enterprise imaging or PACS contracts in order to maintain presence in the increasingly competitive and consolidated market. Consequently, the cost of developing a structured reporting add-on cannot be justified in many markets, as the return on that outlay will not be felt for several years with mainstream adoption in mature markets not expected for 5-7 years. Furthermore, structured reporting integration  is rarely a customer “deal-breaker” for major contracts.

The prioritisation of R&D for imaging IT vendors is complex, with many competing investments needed across the core imaging platforms, as outlined in figure 1 below. Vendors are being led by customer needs, which at present are centred around the transition to cloud, enterprise imaging strategies or the integration of AI, all of which are deemed to offer a greater return.

Figure 1: Structured reporting alongside other R&D areas of focus for imaging IT vendors, with our view of when, based on mainstream adoption, renewal cycles and product readiness, vendors can expect ROI from their investment.

A Base on Which to Build

The irony of this lack of prioritisation is that structured reporting could contribute significantly to the other, higher priorities that are on vendors’ roadmaps. Structured reporting for example, provides a centralised access point for AI integration directly into the workflow with the key findings being pre-populated within the radiologists’ report. For operational workflow and BI, it helps automate and streamline the workflow with the findings enabling deeper insights across both clinical and operational metrics. The value of structured reporting, is not only in the tool itself but its ability to advance, connect and support the wider enterprise.

The development of structured reporting tools will accelerate as providers begin to recognise the value outside of niche departmental applications. Although structured reporting is readily used in departments such as neurology, surgery and invasive cardiology, these are typically only partial rather than comprehensive solutions closely aligned to procedures as opposed to broader diagnosis. The wider adoption of enterprise imaging strategies at healthcare providers will help heighten awareness of the benefits of structured reporting.

Locally Led

There will also be regional differences in the rate of adoption of structured reporting. Some regions such as the UK and DACH are relatively advanced in terms of uptake. This has been catalysed by technical considerations, such as the availability of structured reporting tools and integration into best-of-breed RIS  workflow components, as well as expanding capability to digest AI and AV findings.

Adoption also varies by provider type. Although some hospitals with stretched budgets will be keen to take advantage of the solutions, particularly on the back of the economic disruption caused by COVID-19, most customers so far have been large academic hospitals. This is primarily because of additional research capabilities that structured reporting will facilitate, with the vast amounts of data it brings offering opportunities in everything from clinical practice to AI development.

Other types of providers, such as outpatient centres have been more reluctant, with the tools, at present, offering them less upside and limited use cases demonstrating the efficiency these products create. To date there has also been little evidence to suggest public or private payer-driven markets will adopt more quickly; while the population health benefits of structured reporting could support public health initiatives, most publicly driven imaging IT deals are focused more heavily on cost and reducing complexity, threatening the potential for widespread structured reporting adoption without widespread case studies outlining the ROI. In the private sector, there is arguably more potential near-term given the care quality benefits and growing commercial value of richer imaging datasets. However, until vendors can provide evidence of the operational, monetary savings or care quality benefits, adoption will be limited to the top end of most markets.

Building Momentum

Adoption will increase, but there is still a long way to go before widespread adoption is common. Vendors should take stock and focus on structured reporting competency as a clear differentiator competitively, even swallowing the near-term cost of development in order to lay a foundation for longer-term ROI and deal success. Case studies of successful deployments will also be crucial to prove the advantages of their solutions and allow them to categorically quantify the impact their tools had on their existent customers. Over time, providers will increasingly stipulate structured reporting capability in their tenders, so those that invest in the technology earlier will benefit as customer demand catches up.

However, it is the broader impact of structured reporting that should be most compelling to vendors and providers alike. As AI adoption gathers pace, structured reporting will be at the intersection of ensuring AI-driven results are embedded into the radiologist workflow without slowing reading. Furthermore, broader research, care quality and population health initiatives will increasingly rely on real-world evidence from the federated output of structured reporting.

Healthcare providers may have limited capacity to undertake substantial changes to radiology reporting workflow and care practices currently as they battle the tail-end of the COVID-19 pandemic and resources are stretched. Before long however, the penny will drop that structured reporting deployment can have substantiative benefits in radiology and across the care continuum. Some vendors are gambling this will happen far into the future. Based on Signify’s recent research, however, we believe the realisation of the importance of structured reporting might occur much more quickly given its foundational impact on the success of next-generation imaging IT. In a market where competitors are clawing for differentiation in a commoditised market, structured reporting is today perhaps the most overlooked differentiator of all.

 

About Signify Premium Insights

This Insight is part of your subscription to Signify Premium Insights – Medical Imaging. This content is only available to individuals with an active account for this paid-for service and is the copyright of Signify Research. Content cannot be shared or distributed to non-subscribers or other third parties without express written consent from Signify Research. To view other recent Premium Insights that are part of the service please click here