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Cranfield, UK, 8th August 2024, Written by Vlad Kozynchenko –
The recent proposed acquisition of Augmedix by Commure marks the beginning of market consolidation within the ambient listening sector. This development raises important questions for healthcare IT vendors regarding its implications, future developments, and the overall outlook for the market. These inquiries are also relevant to adjacent industries within healthcare, making this analysis valuable not only for those closely following the ambient listening space but also for anyone interested in AI in healthcare.
This article seeks to address these questions and more, structured into two broad sections: the current state of the market and the potential long-term outcomes. While this piece is more extensive than the usual 1,200-word standard, the length is justified by the breadth of critical issues that need to be covered.
Current Market
Medical scribes have a relatively recent history in healthcare. The concept emerged in the early 1970s as a solution to improve physician efficiency, but it gained significant traction in the early 2000s with the widespread adoption of electronic health records (EHRs). As healthcare documentation requirements became more complex and time-consuming, medical scribes were introduced to alleviate the administrative burden on physicians. Today, medical scribes are an integral part of many healthcare teams, helping to enhance patient care by allowing providers to focus more on direct patient interaction and less on documentation tasks. Today’s market can be divided into three segments: Human Medical Scribes, Incumbent Players, and AI-native solutions.
Traditional human medical scribes include the following examples:
As we can see, two of the vendors have launched AI alternatives to their solutions, which are more scalable and currently have higher margins relative to their human counterparts; however, they are cheaper than a human scribe; hence, if you are chasing revenue as your main KPI over profitability, the business may not appreciate this transition, as despite likely medium-term profitability growth, it would be highly probable that the revenues would grow slower/decline, and even real-term profits could be potentially lower.
Incumbent Medical Scribe Players
There are three leading players: Nuance, Augmedix, and Solventum, with Dolbey also participating as a smaller vendor.
Nuance, announced the sale of its HIM Transcription and EHR Go-Live Services Business in 2020. This enabled Nuance to focus on its conversational AI market leadership with its Nuance Dragon and DAX Copilot offerings. Before Microsoft’s acquisition in 2021, Nuance reported revenues from the healthcare segment at approximately $800 million.
Launched in 2012, Augmedix offers two dictation services: Augmedix Go (AI solution) and Augmedix Live (human Medical Documentation Specialists, or MDS). Augmedix Go comes in various versions, with support levels ranging from none to full review and quality assurance by an MDS before clinician sign-off. Augmedix expects Augmedix Live to appeal to 5-10% of US clinicians, while Augmedix Go could cater to up to 85%. Historically, dictation vendors have served the price-sensitive Augmedix Go market or left it unserved, with clinicians manually producing notes. Augmedix estimates the total addressable market in the US is $8 billion annually. In December 2023, Augmedix announced a pilot of Google Cloud’s Med-PaLM 2 and planned to integrate Google Cloud’s MedLM technology into its stack.
Spun off from 3M in 2024, Solventum offers clinical productivity solutions, including 3M™ M*Modal Fluency Direct, 3M™ M*Modal CDI Engage One, and AI-powered ambient clinical documentation and virtual assistant solutions. These account for roughly 15% of Solventum’s Health Information Systems segment, representing about $200 million. In 2023, Solventum partnered with AWS to use HealthScribe to accelerate the 3M M*Modal ambient intelligence innovation. The collaboration leverages AWS Machine Learning and generative AI services, including Amazon Bedrock, Amazon Comprehend Medical, and Amazon Transcribe Medical, to enhance and scale 3M’s ambient clinical documentation and virtual assistant solutions.
Big Tech is heavily invested in the ambient listening, engaging in “proxy wars” through partnerships: Google with Augmedix, Microsoft with Nuance, and AWS with Solventum. These partnerships vary in their reach and influence. Nuance and Solventum have significant penetration in healthcare systems worldwide, which they can leverage to cross-sell their ambient listening products. Nuance is present in 77% of U.S. hospitals and with 80% of radiologists (as of 2021), while Solventum claims over 75% of U.S. hospitals use at least one of its software solutions. Augmedix’s enterprise customers include over 150,000 clinicians, which it claims represents an addressable market of about $1.6 billion (20% of the total market). However, its current revenue is around $50 million, indicating a penetration of 3.1%.
AI-Native Solutions
In addition to the previously mentioned solutions, there are numerous AI-native ambient listening vendors. Signify Research tracks generative AI product announcements, and there are currently over 40 ambient listening solutions on the market. A select few are highlighted below.
There are also ambient listening solutions developed by EHR providers:
- Oracle’s Clinical Digital Assistant integrates with its EHR system, allowing healthcare providers to retrieve patient information via voice commands. It captures real-time notes using customisable templates and supports next steps like drafting referrals and scheduling follow-ups.
- Sunoh.ai, an EHR-agnostic solution spun out from eClinicalWorks, distinguishes itself with a pay-per-report pricing model. This approach allows clinicians to pay only for the reports they generate, catering to cases requiring minimal documentation.
- Epic initially pursued its clinical assistant, . However, it has since partnered with Nuance and Abridge for ambient listening technology. For example, Stanford Health Care piloted the integration of Epic Rover and DAX CoPilot, which uses a proprietary ChatGPT engine to populate Epic smart fields with suggested summaries from patient consultations.
Solution Assessment
Many vendors face challenges due to a few health systems dominating their enterprise customers. For example, Augmedix has one client representing 27% of its clinicians and two others accounting for 10% and 9%. The rest of their physicians are distributed across over 20 other health systems. The main challenge is integrating into a wide range of healthcare systems. Currently, healthcare providers assess these solutions based on several key metrics:
Accuracy – at the core of any ambient listening system in healthcare is its ability to transcribe and interpret spoken language accurately. Advanced speech recognition engines must handle multi-speaker conversations, differentiate between clinical dialogue and ambient noise, and perform well across various accents and dialects. The accuracy of ambient listening systems in healthcare can be evaluated through a comprehensive set of metrics:
- Speech recognition performance – the system’s ability to correctly transcribe spoken words into text.
- Writing quality (clarity, grammar, professionalism, and overall coherence of the generated notes).
- Clinical accuracy is determined by how well the notes reflect the original medical encounter, including correct documentation of terms, findings, diagnoses, and treatment plans, ensuring the captured information’s fidelity.
- Completeness involves all necessary and relevant medical information being recorded without gaps in the patient’s story or care plan
- Proper organisation of medical information (whether following the traditional SOAP format, problem-based charting, etc.)
- Accuracy of EHR integration that can be measured by clinicians’ acceptance or rejection rates
- Real-time transcription capability
Seamless integration with EHR systems allows the AI to access and incorporate relevant patient data, such as medical history and prior notes, into newly generated documentation. The system should be capable of producing a wide range of note types while intelligently populating structured data fields within the EHR.
Data Security and Compliance. Robust data security measures are paramount. Ambient listening technologies must adhere to stringent security standards, including HIPAA and GDPR and relevant certifications. Data encryption during storage and transmission and clear data ownership and control policies are critical considerations.
Customisation and User-Centric Design. Customisation and workflow adaptation are crucial for widespread adoption. Systems should offer options for human oversight and review before finalising notes, ensuring accuracy and allowing for necessary adjustments. Solutions should feature intuitive interfaces that require minimal training and can be tailored to individual preferences with minimal disruption to existing workflows.
Enhanced language support and communication features are increasingly important to cater to diverse patient populations. Vendors should prioritise support for languages beyond English and provide tools to enhance patient-provider communication.
To justify the adoption and demonstrate value, ambient listening systems should provide comprehensive performance analytics that can track utilisation rates, time savings, and other key metrics. The ability to integrate performance metrics into existing analytics platforms can provide HCPs with valuable insights into the impact of the technology on operations.
Advanced Features and Integration. Advanced ambient listening systems may include real-time transcription and the ability to function in environments with limited internet connectivity, integration of medical coding, navigation, chart search, appointment scheduling, CPOE, automated generation of referral letters, AI-powered search engines for medical guidelines, integrated clinical decision support, real-time prompts, sign-posting, closing gaps in care etc.
There is evidence to suggest that “Abridge is ahead” as per Dr. Lee Schwamm, chief digital health officer at Yale New Haven Medical System and an Abridge customer. Apart from having amassed the highest funding from AI-native solutions, Abridge and Nuance also recently won the AI Tech Sprint created by the Department of Veterans Affairs. However, the fierce competition could lead to those vendors that are currently leading losing these dominant positions.
Plausible Future
The distinction between technology as a feature versus a product lies in its standalone value. If it holds sufficient value on its own that people would purchase it separately, it’s considered a product. Conversely, if it derives most of its value when integrated with other technologies, it’s seen as a feature. Companies often lower the cost of complementary technologies to boost demand for their core products. Ambient listening solutions are likely to be commoditised soon, as evidenced by Commure and Innovaccer offering the feature for free to existing customers.
However, given the significant venture capital investment in this space, financial institutions are expected to seek to recoup their investments. Vendors are exploring various commercialisation strategies. Some, like Sunoh.ai, charge per report, while others use a per-physician-per-month model. Alternative pricing could be based on hours of recorded or summarised conversations.
Looking ahead, ambient listening may initially be a distinct product during the next 1-3 years. However, in the longer term (3+ years), it will likely become a standard feature integrated into all EHR systems, like how Oracle and InterSystems implement the technology.
Medium-Term
In the medium term, vendors will likely compete on price and capabilities. The likely medium-term pricing strategy will be based on the capabilities offered. Below is an illustrative view of what vendors could do in the short to medium term to commercialise the product while creating a competitive advantage by providing certain features that competitors do not.
EHR integration and solution accuracy are crucial factors. A solution would need to achieve mid- to high-90s accuracy to be highly effective. However, once a certain accuracy threshold is met, healthcare providers may not value incremental improvements significantly. For instance, the difference between 93% and 95% accuracy is unlikely to have a substantial impact.
Long-Term
As previously discussed, commoditisation appears inevitable in the long term. The following sections offer speculative insights into potential industry developments, supported by my rationale. However, it’s important to note that these predictions are speculative and may not accurately reflect future outcomes, as I lack a crystal ball or any means of predicting the future with certainty.
We view the Augmedix/Commure merger positively because it allows both vendors to maintain neutrality and EHR agnosticism and enables them to cross-sell to each other’s customer bases. Augmedix’s solutions will likely become commoditised and integrated into Commure’s broader portfolio, aligning with Commure’s existing strategy.
Augmedix currently employs ~1,000 MDS. While some healthcare providers may still prefer “real” medical scribes (estimated at 5-10% by Augmedix), similar to how traditional taxis coexist with Uber, the significant cost difference between AI and human scribes could drive the shift toward AI solutions. As a result, Commure might either repurpose these personnel for its expanded portfolio or consider making them redundant.
Solventum is a significant revenue cycle management (RCM) player with a substantial portion of the market share alongside Optum. By leveraging AWS’s generative AI capabilities, Solventum can enhance its medical coding services and cross-sell to its existing customer base. Acquiring an ambient listening provider could be a strategic move to expand its capabilities further. DeepScribe is a promising candidate within the AWS ecosystem due to its scalability and customizability, making it a potential ideal fit for Solventum’s portfolio.
Epic could acquire Abridge, which it has been co-developing through its partnership program. However, Epic is known for its preference for in-house development over acquisitions. Although Epic has attempted to create its solutions in the past, given the rapid commoditisation of the market and its existing integrations with Nuance and Abridge, it seems unlikely they would pursue this route again. That being said, Epic is known for its unpredictability; only Epic can reveal its true intentions.
Meditech could, for example, strengthen its partnership with Suki to appeal to less cash-loaded healthcare systems.
However, it is worth noting that some ambient listening vendors would prefer to stay vendor-agnostic. This allows them to partner with a broader range of healthcare providers, avoiding dependency on a single EHR system and maximising market reach and flexibility. Suki appears to be one of those vendors, as it has spent significant time, money, and energy integrating with leading EHR vendors; however, a sale is always possible for the right price.
Oracle will likely continue developing its solution unless it fails to meet market standards, in which case it might acquire another vendor.
Market Development
Most vendors primarily target the US market, serving a range of clients from large health systems to individual practitioners. While international expansion presents challenges due to regulatory, financial, and cultural factors, some vendors successfully dominate their local markets, such as Corti in the Nordics and Nabla (headquartered in France), which can make a splash in Western Europe. As technology evolves, US-based innovative companies are also beginning to explore international opportunities cautiously.
Similar to the US EHR market (Signify Research, 2022), leading companies will become enterprise-grade players with a tail end of alternatives. Market consolidation among smaller players is also on the cards.
Conclusion
The ambient listening market is at a critical juncture, with significant potential for growth and consolidation. As vendors compete on price and capabilities, the future will see a mix of commoditisation and innovative advancements. To leverage these emerging technologies effectively, stakeholders in the healthcare IT market should stay informed and adaptable.
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About The Author
Vlad joined Signify Research in 2023 as a Senior Market Analyst in the Digital Health team. He brings several years of experience in the consulting industry, having undertaken strategy, planning, and due diligence assignments for governments, operators, and service providers. Vlad holds an MSc degree with distinction in Business with Consulting from the University of Warwick.
About the AI in Healthcare Team
Signify Research’s AI in Healthcare team delivers in-depth market intelligence and insights across a breadth of healthcare technology sectors. Our areas of coverage include medical imaging analysis, clinical IT systems, pharmaceutical and life sciences applications, as well as electronic medical records and broader digital health solutions. Our reports provide a data-centric and global outlook of each market with granular country-level insights. Our research process blends primary data collected from in-depth interviews with healthcare professionals and technology vendors, to provide a balanced and objective view of the market.
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