Tag Archives: CMS

Signify Premium Insight: Reimbursement Raises Prospects for Cardiac Plaque AI

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Cleerly recently joined the very exclusive club of medical imaging AI vendors whose solutions are now deemed eligible for reimbursement, with the CMS adding an OPPS code for AI-based coronary plaque assessments.

The move means that Cleerly’s plaque AI solution, as well as similar approved solutions from other vendors, now qualify for reimbursement of between $900 and $1,000, when used with Medicare patients scanned in hospital outpatient settings.

The provisioning of a reimbursement code means that Cleerly joins some of medical imaging AI’s most esteemed vendors, such as HeartFlow, and Perspectum, which are increasingly eroding one of the central barriers to the adoption of medical imaging AI: a clear return on investment for adopters.

The Signify View

In one of his works, playwright, poet and author Oscar Wilde once lamented “cynics” who “know the cost of everything and the value of nothing”. Given Wilde died in 1900, he was unlikely to have been thinking of US healthcare providers when he recorded such an utterance. However, his sentiment may resonate with the medical imaging AI vendors who are desperately trying to convince such providers to take a chance on their solutions.

These vendors have a challenging task ahead of them. One of the most pervasive barriers stymieing the adoption of medical imaging AI in hospitals is the questionable return on investment that some solutions offer. There are, for instance, solutions that offer limited value to providers, perhaps shaving only seconds off the completion of relatively menial tasks, or offering assistance in l low volume niche applications that are far too specialised to be commercially viable.

One of the ways those vendors which do offer clinically valuable solutions can convince hospitals of the worth of their solutions is focusing on demonstrating their value. This is a route taken by the likes of Perspectum, which recently published a study highlighting the cost-effectiveness of its LiverMultiScan software by demonstrating “significant” cost savings when the solution is used.

Other developments, however, focus on the other side of this Wildean balance, and instead of demonstrating value, aim to effectively negate, or at least minimise the cost the provider pays to use a tool.

Of Price and Value

At present, bar a handful of exceptions, providers must pay out of pocket for any AI solutions that they choose to utilise. Given the limited budgets and resources available to devote to a potentially intensive and time-consuming deployment of an AI solution, paying out of their own pocket is an unappealing prospect if they can’t be assured a return. The decision of the CMS to reimburse a solution, however, can assuage these concerns, allowing providers to enjoy the purported benefits of a solution, largely at another’s expense.

Even in cases where reimbursement doesn’t cover the entire cost of a tool’s use, such as that of HeartFlow FFR-CT, which is reimbursed at around $950 even though using the tool costs around $1,500, for a provider, paying $550 out of pocket is much more palatable than having to pay $1,500, especially given HeartFlow’s now well-established credentials.

Although Cleerly, like HeartFlow, targets cardiovascular disease, it offers value in a different way. Heartflow’s FFR-CT solution, can in some circumstances, replace an invasive diagnostic procedure which assesses blood flow within a coronary artery. Cleerly’s solution meanwhile measures the actual blockage of coronary arteries. As such, like HeartFlow, using Cleerly’s solution can avoid the need for an invasive procedure, and instead monitor biomarkers of cardiac disease non-invasively.

Now such assessment can be accomplished by providers, while being paid for by CMS, using Cleerly’s plaque solution is a clear opportunity, and one which comes without any obvious downsides.

Commercial Objectives

For Cleerly, this further bolsters its strong position in the medical imaging AI market. The vendor emerged from stealth mode in June 2021 with a $43m series B funding round, since then it secured a $223m series C round in July 2022. In the Premium Insight evaluating that funding round, we highlighted that the vendor should use that money to push for reimbursement and look to expand its commercial reach. Now, with the former objective achieved, it can better focus on the latter. Its hefty funding rounds gave the vendor the financial firepower to establish effective sales networks, while the reimbursement gives providers a reason to pull the trigger. The use of Cleerly’s tool has, after all, quickly grown from a capable solution, to a capable solution that offers a competitive return on investment.

More broadly, the reimbursement also illustrates the guiding hand of the CMS. Reimbursement has the potential to be transformative for a valuable, yet underutilised solution, instantly removing the biggest barrier to its use. As such, the CMS can offer a boost to any vendors or solutions which it believes are particularly worthy, or any avenues which particularly merit further development. It also has the power to revise reimbursement over time, upping or lowering reimbursement in line with the scale of use and relative “value” of the solution. The body must still be discerning, so almost without exception reimbursement has been granted to vendors which already have mindshare and cachet in the market, but, as it has done with Optellum, it can propel smaller, lesser-known vendors to relative stardom.

Furthermore, reimbursement not only makes certain specific products more appealing, it also can improve the prospects of particular use cases, with vendors offering solutions similar to those which have been approved likely to refine or further develop their own products in order to be able to capitalise on that reimbursement. In this way, the CMS can help shape development of the medical imaging AI market.

Heartfelt Progress

At present, this development is leaning further towards cardiac imaging than radiology. Tools that assist in cardiac imaging, from vendors such as HeartFlow and now Cleerly offer significant value to providers, changing patient care pathways, and in the case of Cleerly in particular, offering the opportunity to improve the health of entire populations. This aligns to forecasts made in Signify Research’s AI in Medical Imaging World Market Analysis 2022 – Core Report, which identifies cardiac imaging as the largest medical imaging AI segment over the forecast period.

Compared to cardiac imaging, radiology is somewhat lagging behind. This is largely a result of the nature of many radiology tools. While there are numerous radiology tools on the market, many of them represent limited value propositions. These tools may, for instance, only offer incremental gains, such as marginally increasing the speed at which findings are detected, or fractionally increasing the rate at which measurements are taken. In cardiology, on the other hand, solutions often have far more significant value, shifting a diagnostic pathway or providing earlier diagnosis for example. There are also radiology vendors with similar aims, but in most cases, the benefits are less clear cut than in cardiac imaging.

Another facet of the CMS decision to reimburse the use of Cleerly’s plaque detection solution is the fact it has assigned the vendor an OPPS code, for reimbursement in an outpatient setting. Such a move suggests the body aims to push forward the use of AI in outpatient settings. This makes sense. Outpatient settings represent an attractive setting for AI assistance and keeps pace with the growing preponderance in the US for use of outpatient imaging for non-emergency imaging a more cost-effective setting versus hospitals.

Above all though, the decision by the CMS to provision an OPPS code for Cleerly highlights an important step for the company, propelling it into the upper echelon of medical imaging AI vendors. It does, after all, offer a valuable solution with regulatory clearance, it is well funded and has won the confidence of investors, and now qualifies for reimbursement, incentivising providers to adopt it. More significantly however, it represents a milestone for medical imaging AI as a whole. In this and other recent moves, the CMS has shown that it will support vendors which offer value to providers and will incentivise the use of solutions that can materially improve outcomes for patients.

With its provisioning of a code for Cleerly, the CMS has shown that it is making a more concerted effort to forward the adoption of medical imaging AI. One might even say it has realised the importance of being earnest.

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Signify Premium Insight: Optellum’s Answer to AI’s Question of Value

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 Dr Sanjay Parekh

Optellum, a UK-based AI vendor focused on lung nodule malignancy prediction, has recently announced that the Centers for Medicare and Medicaid Services (CMS) has established a national payment rate for the vendor’s technology, under the New Technology Ambulatory Payment Classification.

The move means that health insurance claims will be able to be paid out for individuals enrolled in Medicare. This will help facilitate the use of Optellum’s tool and financially incentivise providers to adopt it, but could it also point to medical imaging AI’s transition into the mainstream?

The Signify View

Much attention and many column inches are given over to medical imaging AI’s most prominent vendors. Interest is, quite rightly, usually directed at those vendors that have secured vast amounts of funding or announced grand partnerships. However, these aren’t the only companies worth watching, with smaller, less well-known vendors sometimes providing the most impactful and market-shaping stories.

Such is the case with Optellum. It is a relatively small vendor, having only raised a small amount of funding since its inception in 2015 (we estimate < $10 million), an amount that pales into near insignificance when compared with some other recent funding activities, propelling AI vendors to total funding hauls of $250m and beyond. The vendor was also quiet in terms of regulatory approvals until March 2021, when its solution received approval from the US-FDA. So far, so normal.

Where interest may start to be piqued, however, is when the nature of Optellum’s tool is looked at more closely. Many vendors offer lung cancer detection and quantification AI tools for CT imaging, including large medical imaging vendors such as Siemens (AI-Rad Companion Chest CT) and Philips (DynaCAD Lung), and smaller specialist vendors such as Riverain Technologies, Aidence, and Infervision.  But, where Optellum sets itself apart is its focus on malignancy probability, with the vendor’s solution able to predict the likely malignancy of a lung nodule. Instead of simply assisting or providing additional information to a radiologist, the tool should enable a radiologist to work more efficiently and effectively by prioritising those that are more likely to have malignant, rather than benign nodules.

Popular Algorithms

Lung cancer is a pathology for which early detection can have a particularly significant impact. A lack of screening programmes means that often, early detection isn’t happening. Optellum could be useful in direct screening programmes, but, more significantly in the near term, the solution could be used for incidental screening, being used on every chest CT conducted, and drawing attention to those that look likely to be malignant. Optellum’s use transcends being applied solely to individual patients and is also applicable in a population health context.

Most of the recent CPT codes that have come into force (which itself is a significant step forward in allowing the use of certain tools to be tracked) were for quantitative assessment. Some vendors may leverage these CPT codes for their solutions that improve workflow efficiency, but these solutions may not necessarily have the same population health benefits.

Optellum has successfully demonstrated that its Virtual Nodule Clinic solution qualifies for 0721T (or 0722T) for quantitative CT tissue characterisation as it measures the likelihood of lung cancer on CT imaging. Its ability to predict lung cancer, a capability lacked by many other AI vendors with lung nodule solutions, is the reason why Optellum’s lung cancer prediction technology received reimbursement, when other solutions which have recently been provisioned Category III CPT codes have not.

For instance, the very same CPT code for CT tissue characterisation, could also be applied to coronary artery calcium (CAC) scoring from vendors such as Cleerly, or Nanox.ai (formerly Zebra Medical Vision). However, CAC scoring could be indicative of coronary artery disease, but it is not directly linked to that pathology. Optellum’s solution, conversely, directly assesses the probability of the patient having the pathology itself, rather than a biomarker of disease that indicates a patient may have or is at risk of said pathology. By focusing on driving improvements in a care pathway rather than incremental increases in diagnosis efficiency or accuracy, Optellum’s solution will also be favoured more by value-based care health systems, such as single payor markets, or government-driven programmes such as Medicaid. Moreover, it will also certainly raise the eyebrows of private payors as a potential disruptive and competitive influence on traditional care models.

Further, the fact that Optellum’s solution has already received reimbursement, despite it only being granted a Category III CPT code (typically, with potential for, but no guarantee of reimbursement) adds further credibility to its value and perceived impact it will confer. Breast cancer CAD solutions (computer-vision and basic machine learning) were the first wave of software tools to receive reimbursement. Providers used these tools to claim the reimbursement despite many of them not performing as well as expected or not providing real clinical value, by returning high rates of false positives, for example. The provision of Category III CPT codes without reimbursement helps prevent this, with providers only using the tools that they see value in, regardless of whether it is reimbursed or not. Adoption and usage of these tools will, ultimately, result in the Category III CPT codes being upgraded to Category I, which is assigned obligatory reimbursement. Given that Optellum’s solution already receives reimbursement, suggests it has overcome the “value” threshold, with the CMS only offering reimbursement on tools it is confident provides an advantage.

Joining the Ranks

Optellum’s reimbursement also represents a positive change for the broader medical imaging AI industry.  In the first instance, the reimbursement shows what other vendors must demonstrate to secure codes and reimbursement for their own solutions. Those which already qualify for the new wave of CPT codes will look to demonstrate, as Optellum has done, the same or equivalent value, while those which do not yet qualify for CPT codes will also use Optellum’s progress to push for the CPT codes, which will represent the first steps on the road to reimbursement. A clear example of this is ScreenPoint Medical, which offers quantitative mammography tissue characterisation; a tool very comparable to that of Optellum, albeit in a different modality for a different cancer. At present there is no CPT code that ScreenPoint can utilise, but Optellum’s success will give ScreenPoint greater incentive to pursue the same, especially as it looks to enter the highly competitive US market.

The awarding of reimbursement, and particularly the pace at which it was given, also offers insight into the type of population health tools that the CMS will look to reimburse. Such a move therefore makes it look more challenging for tools that are only capable of ‘detect and triage’ to make the same progress because they don’t offer the same value proposition for clinicians and providers or the same benefit to patients.

Population health tools in contrast, whether used to pick up incidental findings or in screening programmes, can offer earlier detection leading to significant improvements longer-term patient health and ultimately better outcomes at lower costs. The CMS is effectively looking to guide the medical imaging AI market through its reimbursement and in effect remove one of the biggest barriers to AI adoption, allowing these population health solutions to prosper.

Risk and Reward

In removing, or at least mitigating the cost of certain AI tools, the CMS is significantly reducing the financial risk a provider takes in adopting an AI solution. Instead of providers having to derive a return on is investment at some indeterminate point, when an image is read fractionally quicker or a different diagnostic procedure is chosen at some point in the future, reimbursement means healthcare providers can capitalise on the availability and use of AI tools

More significantly, by facilitating the direct financial reward for use of AI tools for the likes of Optellum, as well as other vendors and solutions which have also secured reimbursement such as the stroke tools from the likes of Viz.ai, RapidAI and Aidoc for example, and the ultrasound guidance tools from Caption Health, the CMS is helping AI on its march to mainstream adoption. Such AI tools, which deliver greater value to radiologists, and in turn are rewarded by the CMS (in the US market at least), demonstrate a very powerful sales proposition and facilitate their use at ever greater numbers of sites.

This also heralds a new model for assessing market leaders. Instead of indirect methods for assessing a company’s place, such as its ability to fund raise or its ability to secure FDA approval, reimbursement is a more direct metric, showing clearly which solutions are being deployed and used clinically. By this metric, Optellum is punching well above its weight, with its funding deficit not necessarily a barrier to its rise to AI’s top table.

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Signify Premium Insight: Intermountain Subsidiary Leaves Hospitals Behind

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Amid growing pricing pressure on medical imaging in the US, Intermountain Healthcare recently announced it is launching an outpatient imaging subsidiary under the Tellica Imaging brand name. The first three locations of the new chain of standalone outpatient imaging centres are set to open in late 2021, with five more set to follow in 2022.

As well as operating under a new brand name, the outpatient imaging centres will also offer MRI and CT scans at flat-rate prices which are lower than the same imaging exams in a hospital-based setting.

The Signify View

Some types of imaging examinations will always need to be performed in hospitals. The nature of emergency or interventional imaging, for example, negates the possibility of it being performed elsewhere. For many non-emergency diagnostic imaging exams, however, there is a growing trend for some exams which would typically have been performed in a hospital, to increasingly be taken on by outpatient imaging centres.

The Covid 19 pandemic has been one factor in this shift, with providers trying to keep patients out of hospitals wherever possible in order to minimise their potential exposure to the coronavirus. However, in a bid to rein in healthcare spending in the US, payors have also been increasingly pushing their customers towards outpatient imaging centres, where the cost of imaging exams can be significantly less than in a hospital setting.

More broadly, changes to reimbursement brought about in the latest fee schedule from the Centers for Medicare and Medicaid Services (CMS) is also set to alter the complexion of the medical imaging market. There is a growing body of evidence that suggests the changes brought about in the fee schedule are going to affect single site imaging centres most severely. These smaller independents will therefore find it increasingly difficult to compete with the larger outpatient imaging networks, which can leverage the economies of scale to be more aggressive on pricing. This is one of the factors driving consolidation in the outpatient medical imaging market, which, to an ever-greater degree, is being dominated by large outpatient networks.

An Equal Fight

Hospital groups will be loath to lose business to these imaging groups, and so, in Intermountain’s case, establishing an outpatient network of its own makes a lot of sense. The newly formed Tellica will be able to compete for outpatient imaging business on an equal footing with the other outpatient networks. It will, like its competitors, be able to offer lower cost imaging than in Intermountain’s hospitals.

Payers in the broader market have also played a substantial shift towards outpatient imaging focus, with a number, such as Anthem and UnitedHealthcare, now refusing coverage for non-emergency hospital-based imaging, such is the current discrepancy in price between in-hospital and outpatient-based imaging.

There are many reasons for the discrepancy. Outpatient groups can focus solely on imaging, so are able to tailor their services to efficiently addressing less complex, higher volume imaging exams. In contrast, hospitals must maintain the ability to conduct a broader array of exams and more advanced scans, even if it means purchasing more expensive equipment that is infrequently used and facing the additional staffing costs that comes with more specialised doctors.

Tellica’s spending can also be more focused. The provider will not, in most cases, have to stretch to purchasing the most premium specialised imaging equipment, and instead invest in imaging solutions that can expedite its workflow and enable it to attend to patients more efficiently. Increasing volume and capacity of imaging can also offset the lower reimbursement rate per scan, while also creating opportunity for the health system to bring in new patients. The deployment of AI tools in the outpatient setting may also have a material impact in terms of efficiency and care quality for the provider given its much more myopic focus, with the outpatient setting expected to experience faster adoption of AI versus the hospital setting.

More, and More Affordable

The effects of this shift to outpatient imaging will ripple out across the medical imaging sector. Modality vendors are likely to see an overall increase in the volume of medical imaging equipment being sold. However, this will be balanced by a fall in the premium models as hospitals, which typically purchase the more advanced products, will require fewer systems. Conversely, there is set to be an increase in mid-range ‘workhorse’ models, which will, in most cases, be an outpatient centre’s preference. As such, the market average selling price of systems will fall. This change in the complexion of the market could also see sales leak from premium international vendors, to other cost-competitive vendors, such as United Imaging, which may not be able to compete in the upper echelons of the imaging market but are competitive in the mid-range and keen on pricing. This will move the focus away from top end features, forcing vendors to highlight the fundamental value and efficiency of their systems more clearly.

These changes are also set to have an impact in the imaging IT market. Providers such as Tellica, which grew out of a hospital network, will likely become license extensions opportunities of the  original hospital network’s imaging IT system, utilising the same vendors and the same solutions. This may give the likes of Tellica an advantage from a deal size perspective, enabling them to take advantage of their larger buying power.

There are still some benefits unique to specialist outpatient imaging networks. The opportunity for imaging IT amongst these newly formed networks, is from their nimble structure, allowing them to be reactive to shifts in the market quicker than larger hospitals. In a similar vein these providers are also typically more innovative in adopting new technology, due to the drive for efficiency to remain competitive and profitable. These growing outpatient imaging networks  are therefore likely to be among the first providers to take advantage of informatics vendor’s efficiency-focused products. This could be particularly true as products are increasingly tailored to address the needs of outpatient imaging providers, such as GE’s recently released TruePACS system, for example.

Scale and Efficiency

Intermountain’s launching of Tellica fundamentally represents a hospital network responding to the changing tides in the medical imaging market, and effectively cutting its pricing in the outpatient space to maintain competitiveness. Intermountain is not the first to make such a move but it does highlight the increasing interest in the space. As this interest in outpatient imaging centres grows and more providers look to compete in the space, prices will continue to fall, and margins will  tighten. This will ensure consolidation continues, with it becoming increasingly unfeasible for small independent imaging centres to thrive given they will be unable to capitalise on economies of scale or take advantage of larger, network-wide plays to adopt tools to drive efficiency forwards.

Resultantly, smaller imaging IT vendors will also find it more difficult to compete. Many of their customers are the smaller, independent outpatient imaging providers; as these are replaced by larger outpatient networks with much larger and complex network-wide deals, some of these smaller imaging IT vendors could falter.

Intermountain’s creation of Tellica shows it is willing to adapt to a changing market. It has entered an increasingly competitive and rapidly consolidating space and is hoping to go toe-to-toe with some of fastest growing providers in medical imaging. It can utilise its broader buying power, and the nimbleness that a new brand affords, but key to this success will also be its ability to scale rapidly. The outpatient imaging market is one where scale and efficiency bring success. If Intermountain’s Tellica can achieve both, then it has a strong future ahead.

 

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