Multi-Billion Dollar Potential of the Ultrasound Digital Ecosystem Market Hindered by Complexities of Ultrasound Imaging

Publication Date: 19/02/2024

Cranfield, UK, date 19/02/2024 – The market potential for the ultrasound digital ecosystem is substantial, a multi-billion market opportunity. However, the fragmented nature of the market, combined with a large proportion of “captive” software applications, both on scanner and as feature-functions of wider enterprise health IT platforms, has made converting this opportunity into commercial gain for vendors a strategic challenge.

This insight explores the key themes and considerations of the Ultrasound Digital Ecosystem.

Encounters-based Versus Orders-based Workflow

For many traditional settings, ultrasound has also posed a workflow challenge, given its use in an increasing variety of settings and encounter-based workflow (EBIW). This is often also counter to the efforts for enterprise consolidation which typically evolves from radiology PACS, thereby inherently evolving with order-based imaging workflows (OBIW) in mind. These challenges also have snow-balled lately for providers, as POCUS ultrasound has proliferated into a multitude of different settings and care pathways.

Inherently, OBIW captures information associated to the order, whether that is defining the body part, procedure, as well as laterality and specific anatomical position. At present, manual intervention is required to record this information for EBIW. Without this information, EBIW creates inefficiency across an institution, such as “revenue leakage”, if all necessary information about the imaging is not captured. There is a requirement to perform the same image again in follow up appointments, due to lack of clarity on location and there is a limitation in value of EBIW imaging in post-acquisition workflow due to lack of data.

For digital ecosystem (DE) ultrasound vendors, this challenge also presents an opportunity. As traditional PACS and enterprise radiology offerings are typically weak on EBIW for ultrasound, the need for specialist workflow support and manipulation (e.g. tagging of image metadata to capture patient, imaging and encounter information to create a standardised source, automating and standardising reporting, ensuring measurements are more reproducible) can offer significant advantages for providers.

Moreover, many EBIW create missed billing opportunities. So, use of healthcare economic ROI investment can showcase to customers that the cost of a DE ultrasound solution can be offset by the billing and efficiency upsides of a more comprehensive DE ultrasound platform. This is a considerable factor for large hospital networks especially.

Role of Analytics in Ultrasound Digital Ecosystem

Analytics can be used pre, mid or post image acquisition as vendors seek efficiency and productivity solutions to address the shortage of sonographers and procedure backlog.

  • Pre-Acquisition:
    • Workflow/Scheduling (Workstation/Platform-based/ Third Party Partnership)

Operational workflow analytics support smart scheduling of exams, staff rotas and adaptive worklists, typically served by dedicated ultrasound IT offerings, or from generalist radiology RIS/imaging IT workflow interfacing with EMR’s and other operational systems.

  • Auto-tuning (Typically Embedded/Bundled with Ultrasound Modality)

Many ultrasound systems now allow users to set protocols on the ultrasound system that automatically adjusts the settings depending on the body area being scanned.

  • Mid Acquisition: Imaging Quality, Image Capture Guidance, Report Creation

Mid acquisition analytics are predominantly used to ensure the correct high-quality image is obtained. With ultrasound being one of the most technically difficult imaging procedures to perform, there is often large intra- and inter-operator variability in the images obtained. AI-based solutions to assist novice users to obtain high quality ultrasound images are increasingly being developed. Most of these solutions work by guiding the user through the image acquisition process through a series of sweeping movements with the probe, assessing the quality of the image obtained and providing feedback on steps to improve image quality. These solutions are becoming increasingly useful in POCUS, where there are novice/new users of ultrasound. However, these solutions can also be used as a training tool and for image quality assessment to identify where additional user training may be required.

  • Post Acquisition: Interpretation, Primary Read, Secondary Read (Workstation/Platform-based/Third Party Partnerships)

Workflow automation and image analysis tools allow effective and efficient analysis of the ultrasound image, reporting to other departments and storage. The introduction of deep learning in recent years has spurred a new wave of AI start-ups and scale-ups developing algorithms for ultrasound. There is now a growing range of software applications for a variety of body areas. The value of these tools is somewhat limited as any gains in productivity and clinical outcomes tend to be incremental rather than transformative. Furthermore, many image analysis tools have narrow focus and automate specific measurements, whereas most users require a more comprehensive solution that can automate many different measurements.

Overview of the Role of Analytics in the Ultrasound Digital Ecosystem

Source: Signify Research

Clinical Applications – Digital Ecosystem Nuances

Clinical applications for ultrasound play a significant role in determining the strategic approach for IT product portfolios. The diverse nature and range of use-cases has typically limited many vendors from bringing comprehensive digital solutions to the market.

There is some commonality in terms of basic requirements for reporting, image analysis, workflow, billing and other processes across each clinical application However, in reality each is a unique segment influenced as much by the wider ecosystem in terms of IT. These can include:

  • Specific care pathway software and/or modules used from leading PACS or EMR vendors.
  • Local, regional or national reporting guidelines.
  • Centralised IT procurement strategy (such as enterprise imaging) and minimum integration standards.
  • Education and willingness of users/owners to pay additionally for software (clear ROI).
  • Adoption maturity of other clinical and operational systems (EMR, enterprise imaging.
  • Key strategic priorities of healthcare provider, such as missed billing, improved multi-disciplinary diagnostics, data consolidation and harmonisation, centralised operational resource balancing etc.

The specific context of each clinical segment and healthcare provider setting therefore makes it very challenging for ultrasound vendors to design ultrasound software that is flexible to this complex array of uses, but also adaptable to the strategic needs of each deployment.

Influence of AI on Digital Ecosystem Strategy

As was outlined in our previous “Ultrasound in AI” report, there are four main categories of ultrasound AI:

  • Image Capture (probe placement, auto-capture, QA)
  • Workflow Automation (Auto detect anatomy, auto-labelling, auto pre-sets, auto-segmentation, auto reporting)
  • Image Analysis (feature detection of lesions, nodules, anatomical structures, feature quantification)
  • Decision support (feature classification, risk stratification etc.)

The deployment method of AI solutions depends on several factors, such as the category the AI solution is in, its clinical use and on the location/work setting of the user. AI solutions for image capture can only be deployed on the ultrasound device, however AI solutions for workflow automation, image analysis and decision support can also be deployed on a workstation or in the cloud.

In the context of the wider ultrasound digital ecosystem, the deployment of AI is impacted most by variety of setting and application type. Vendors should also assess if AI is a differentiator versus competitive products, offering a significant opportunity for upsell of specific AI “add-on” software, or a differentiator from a scanner vs scanner feature perspective. The latter is typically more readily commoditised. A summary of the key advantages and disadvantages is outlined below:

Changing Competitive Dynamics

As a truly “multi-application” modality, the breadth of ultrasound use also brings with it a more diverse competitive ecosystem. Traditional scanner-vendors, especially market leaders, have two main key digital strategies, “defend and deploy”. Defending equipment installed base via digital feature differentiation, and deploying new digital software assets that offer commercial upside or a way into new customers.

At the same time, imaging IT vendors are expanding the reach of traditional radiology IT offerings such as PACS into wider “enterprise imaging” offerings. This includes the ingestion and management of ultrasound images, reporting and workflows, in part attempting to “de-couple” some digital features from modality vendors. Throw in new hand carried ultrasound scanner vendors with proprietary digital ecosystems, EHR vendors and a host of best of breed niche independent vendors, not to mention a new generation of ultrasound AI start-ups, and its “clear as mud” for some providers in terms of where to partner.

Therefore, the nature of ultrasound as a modality, and its constantly evolving and fragmented competitive make-up, add to the difficulty in creating scalable, high-growth commercial digital platforms. While the market potential is a multi-billion-dollar opportunity, realising this potential is far from easy. The leading scanner vendors have first-mover and scale advantages, but heading off commoditisation and a changing competitive landscape mean success is far from assured.

Platform Versus On-Device: Integration

Integration remains one of the leading challenges facing the ultrasound digital ecosystem. While DICOM standards for ultrasound have existed for decades, the diverse and specialist nature of ultrasound output, analysis and reporting means that many existing installed systems still output less advanced standards capability, limiting integration.

Additionally, scan settings for ultrasound have proliferated, changing the demand for the type of information required to be communicated and the broader enterprise systems and stakeholders that require access to information generated from ultrasound software.

Today, these factors have meant that ultrasound software is one of the least advanced in terms of integration, with proprietary software common. Basic functionality (basic reporting, image communication, HL7 messaging, worklists) are near-universal; however, support for more advanced analysis, multimedia structured reporting and quantification for advanced diagnostic tools remains far less mature from an integration perspective. Newer market entrants in the teleradiology and AI segments have also been relatively weak on integration capability, adding an additional barrier to adoption.

The recent emergence of new handheld/point of care ultrasound scanners in new settings, often with dedicated scanner-bundled software offerings, has also increased attention and speculation on ultrasound software integration. While many of these new vendors offer their own cloud-enabled platforms for exam management and report generation, the report output is typically a pdf. Tools to support exchange of ultrasound exam data (encounter-based or order-based) with larger enterprise health IT platforms also remain weak. While the need for full integration of all exam data may not be required in every setting, the growing focus from providers and payers on longitudinal data access for patient records (and growing focus on patient access) means these vendors will need to develop these offerings further to penetrate the market further. This is also intensified as consolidation in the outpatient market continues (especially in the United States) with larger enterprise networks focused on IT software consolidation and improved central access to patient data.

Customer perspectives and expectations around integration are also changing, with proprietary software requiring extensive IT resources to interface becoming a growing factor in purchasing. Further, with the proliferation of AI, many healthcare providers are viewing large volumes of curated imaging data and reports as an increasingly valuable asset for development of the next generation of diagnostic and clinical tools. Consequently, ultrasound software offering more harmonized standards and streamlined integration with enterprise IT is While specialist ultrasound software is responsible for most service line processes in today’s market,   an increasing proportion is expected to be through imaging IT platforms in the future.

Related Research

Ultrasound Digital Ecosystem Report

“Ultrasound Digital Ecosystem Report” assesses the landscape within the sub-sectors of Ultrasound IT, such as in reporting and analysis, integration, fleet management, analytics and collaboration. The report will quantify the size of the ultrasound IT segment and discuss the future direction of the market.

About The Author

Mustafa joined Signify Research in 2020 as part of the Medical Imaging team which covers areas such as ultrasound, general radiography and machine learning in medical imaging. Prior to that he obtained a PhD in Pharmacy and Physiology from the University of Kent and has three years of post-doctoral experience working on optimising healthcare for genetic Cardiac diseases. In his spare time, he has a passion for sport and fitness and spending time with his wife and family.

About the Medical Imaging Team

Signify Research’s Medical Imaging team formulates expert market intelligence for some of the leading Ultrasound, CT, MRI, and X-ray vendors. Combining primary data collection and in-depth discussions with industry stakeholders, our thorough research approach yields credible quantitative and qualitative analysis, helping our customers make critical business decisions with confidence. Furthermore, our commitment to seeking a plurality of perspectives across the markets we cover guarantees that our insights remain independent and balanced.

About Signify Research

Signify Research provides healthtech market intelligence powered by data that you can trust. We blend insights collected from in-depth interviews with technology vendors and healthcare professionals with sales data reported to us by leading vendors to provide a complete and balanced view of the market trends. Our coverage areas are Medical Imaging, Clinical Care, Digital Health, Diagnostic and Lifesciences and Healthcare IT.

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