Vital Signs. Industry Focus. November What s New in Voice Recognition for Radiology Reporting?

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1 Industry Focus Life sciences November 2013 Vital Signs Nadim Michel Daher, Industry Principal, Advanced Medical Technologies What s New in Voice Recognition for Radiology Reporting? Reporting is one of the areas in medical imaging informatics that advanced the most in recent years. With much of the imaging workflow now digitized and carried out through second- and third-generation image and information management systems (such as picture archiving and communication system (PACS) or radiology information system (RIS)), the third pillar of the end-to-end digital imaging workflow has grown less isolated and more influential than ever before signaling the advent of true voice-enabled and speech-driven radiology reporting. Ongoing Market Transition to Technology-Based Solutions Automated speech recognition (ASR) constitutes the technology-based alternative to a more traditional, human-based service model. Rather than employing full-time medical transcriptionists as part of in-house staff or through a contract with medical transcription service organizations (MTSOs), ASR allows providers to perform more of the reporting function themselves, without a huge time penalty. By capturing the voice of an interpreting radiologist through voice dictation and then using natural language processing (NLP) algorithms to transcribe speech into text, ASR can assist radiologists in carrying out the reporting function all the way to report sign-off (front-end ASR). In the case of back-end ASR, the same technology is used to accelerate the work of a transcriptionist, who has more of the groundwork automatically done for them so they can devote more time to doing quality assurance on final reports.

2 As such, in some cases radiology can rely entirely on a technology-based solution for the reporting task, while in other cases there is still some reliance on transcription services. The US market has gone a long way in the adoption of technology-based solutions. Frost & Sullivan estimates between one in four and one in three imaging providers still rely entirely on the human transcriptionist model, while the majority (or between two out of three and three out of four) use some kind of technology-based automated speech recognition solution. 2 Improved Technology for Higher Clinical Efficiency Perhaps the most important new feature in the latest generation of ASR solutions, as far as having direct impact on imaging providers in the past year or two, is the big jump in accuracy of the latest speech engines. That is, the capabilities of these engines to accurately recognize each word a radiologist dictates at once, without the need to repeat it or correct it, and regardless of speech variations such as an English accent or background noise interference. In fact, as the generic versions of speech engines continue to be developed for multiple industries outside of healthcare (think of Apple s Siri and voice-controlled car features) every two or three years, we see a major migration of the healthcare-specific solutions to the latest generation of these engines. Complementing these upgraded speech engines with ever-growing libraries of medical and radiology-specific terms, the new generation of engines essentially allows for more word recognition from the onset, and eventually increases the efficiency of the reporting process and productivity of radiologists. The real novelty in this performance boost of the large vendors latest speech recognition solutions, which are now close to 99% accurate, lies in how they combine higher speech engine accuracy with a larger vocabulary. With techniques and algorithms borrowed from the field of artificial intelligence (AI), the solutions essentially add a layer of machine reading comprehension that takes medical imaging reporting beyond natural language processing (NLP) and into the next level of natural language understanding (NLU). Practically, the new generation of speech solutions is able to grasp the context of a phrase beyond individual words and use this context base to make smart suggestions, provide alerts of critical findings, or highlight potential errors before final report signoff. From Speech Engine to Integration Platform In the absence of large capital available to forklift upgrade imaging informatics solutions, especially in the wake of meaningful use (MU) initiatives, imaging providers are striving to improve the integration and interoperability of their current solutions. Developing bi-directional connectivity between the speech recognition solution and PACS and/or RIS is one of those integration efforts of providers. Whether the reporting workflow is PACS-driven or RIS-driven, bi-directional connectivity with the reporting applications allows populating patient information back-and-forth between these systems and also presents the potential to close the loop with electronic medical records (EMR) and hospital information systems (HIS).

3 vital signs This bi-directional connectivity also allows the reporting solution to be the access point to imaging, such as in the case of an affiliated radiologist working from outside the facility, having only Web access to the reporting solution, and wanting to access patient reports and images. As they feed from and into multiple, sometimes disparate IT systems, speech recognition and reporting solutions are evolving from being a point solution to being a true integration engine for their overall imaging workflow. Many leading healthcare institutions are, in fact, expanding these solutions into an informatics platform to leverage clinical and business analytics and decision support. 3 A Platform for Business and Clinical Data Analytics Two macro trends in healthcare IT are poised to become drastic game-changers for healthcare data analytics and patient engagement. However, much like patient engagement hinges on educated healthcare consumers, the feasibility of data analytics in medical imaging is based on the assumption that clean, structured and consistent data points exist. Radiology is behind other areas like cardiology in its adoption of structured reports and templates throughout its sub-specialties. Estimates place the current penetration level of structured reporting in radiology in the vicinity of 60%, but this number continues to grow gradually, as there is almost never a reversal once there is a shift to structured reporting. When looking at the adoption curve so far, and given it appears to be following a top-down approach from large academic to smaller-scale providers, the adoption level can be projected as near 90% in the US within five to seven years. Radiologists resistance to change is still slowing the adoption curve of structured reporting. The potential drawbacks in productivity and profitability caused in the short term through the learning curve are worth the investment versus continuing self-editing and self-reporting by radiologists. However, this resistance is slowly being offset by the obvious benefits in the long term, including those that stem from developing business and clinical analytics to support decisions in the enterprise. Moving beyond rather basic dashboards that analyze HL7 messages to track relative value units (RVU) or other performance metrics such as report turnaround or emergency turnaround times, the more progressive providers are already making use of the embedded business analytics capabilities of their speech recognition systems, in-house developed applications, and those of third-party systems. Early adopters are using these tools to make data-driven business and clinical decisions, and then analyzing the outcomes of these choices with confidence.

4 Speech Recognition and Reporting Segment: Four Competing Models for Radiology Reporting U.S., 2012 FOUR MODELS FOR RADIOLOGY REPORTING 4 Dictation through front-end ASR Dictation followed by human transcription services Dictation followed by ASR-assisted transcription services PACS-or EMR-based structured reporting template Source: Frost & Sullivan analysis A Quick Look at the Competition In the past few years, the speech recognition industry has consolidated, sometimes through predatory merger and acquisition activity, especially among MTSOs. Examples include MedQuist s acquisition of Spheris (April 2010) and Nuance s acquisitions of Webmedx (July 2011) and Transcend Services (March 2012). Any way one looks at it by number of customers, imaging procedures or revenue Nuance Communications is the clear market leader for technology-based ASR in the US medical imaging and the broader healthcare market. Nuance leads the market both for back-end and front-end ASR, while its closest competitor, M*Modal (formerly MedQuist), the established MTSO market leader, has moved up from a distant second position in the ASR market since acquiring M*Modal in 2011, albeit while losing share to Nuance in the MTSO market due to Nuance s recent MTSO acquisitions. With Nuance and M*Modal established by far as the two largest industry forces, and with a fragmented industry in the smaller scale, the market is facing somewhat of a vendor duopoly, but benefiting from the high level of competition subsisting between all vendors. In Analytics The emergence of analytics in medical imaging is shaping up a new competitive niche in the industry poised to get more visibility and attention from vendors and providers. Two companies can be deemed the current movers and shakers in this area Medicalis and Montage Healthcare with other notable mentions for companies such as Softek and Primordial Design. Some of these companies are already partnering with the large speech recognition vendors (such as Nuance and Montage), while the large vendors are aggressively developing their own capabilities on the analytics front.

5 vital signs Company Spotlight: Montage Healthcare Solutions As radiology shifts from volume-based to value-based imaging, radiology productivity, quality, and safety improvement tools will be crucial for success. Today all radiology practices, whether freestanding, hospital-based, or part of an outpatient center, must operate like disciplined businesses to survive and prosper. And like any enterprise, business intelligence and quality analytics are essential to improving performance. As such, practice leaders must learn how to refine and improve their business practices. It is no longer just about administering day-to-day business, but also about ensuring the health of the business and, increasingly, growing the business in a planned manner. 5 In the new era of Imaging 3.0 1, radiology decision-makers must be able to rapidly access actionable information, and provide a way for meaningful quality, outcomes, patient safety and productivity understanding to be extracted from the unstructured radiology narrative in the radiology information system (RIS) and electronic medical record (EMR). By leveraging the power and simplicity of search and natural language processing (NLP), complex clinical quality questions can be easily answered, while the customizable analytics tools speed up the assessment of business performance and clinical quality. Flagship Product: Montage Search & Analytics Montage Healthcare Solutions developed Montage Search and Analytics, a unique tool for helping radiology leaders succeed in the Imaging 3.0 era. Montage Search & Analytics is an intuitive radiology data mining and analytics solution that enables department leaders, radiologists, administrators, researchers and educators to more efficiently deliver a higher-quality clinical service. Its novel search-driven approach leverages proprietary NLP to extract and visualize business and clinical understanding, using information contained in an organization s RIS and EMR. Search is the underlying mechanism for uncovering clinical findings, whether from radiology only, or across radiology and pathology and other clinical specialties. Business performance and clinical quality analytics enable levels of understanding not previously available, because of the detailed and actionable information that is provided, and the interactive manner in which it can be viewed. Using these more capable analytic tools, radiology managers will quickly find answers to such questions as, How many MRI studies demonstrating a tumor had pathology correlation? How well does the pathology correlate to radiologic findings, and how does this vary by reporting radiologist?

6 Noteworthy Milestones Montage Healthcare Solutions is founded by William Boonn, M.D., Woojin Kim, M.D., Curtis Langlotz, M.D., Ph.D., and Rajan Agarwal, M.D., MBA as a privately held company Montage Healthcare and Yottalook combine forces through Montage s acquisition of ivirtuoso Montage starts technology collaboration and signs a reseller agreement in 2011 with Nuance Communications, Inc. Montage Healthcare partners with Radimetrics to enable correlation of radiation dose with radiology clinical quality measures Montage launches Montage Signal, a real-time report analysis software tool Partnership with Mammography Reporting Systems is formalized to enrich mammography quality efforts. More than 50 healthcare organizations have purchased and deployed Montage Search and Analytics in their practices. Montage Healthcare nominated as finalist for Best New Radiology Vendor in the 2013 edition of the The Minnies. Contact Information William Boonn, M.D., President, Montage Healthcare Solutions Inc. Bill@MontageHealthcare.com 1 Imaging 3.0 is a trademark of the American College of Radiology

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