eTech Insight – Suki, A New Entrant in the Learning Virtual-Scribe Market - Cover

eTech Insight – Suki, A New Entrant in the Learning Virtual-Scribe Market

Why a KLAS First Look on Suki?

Suki was one of the most mentioned companies in KLAS’ Emerging HCIT Companies 2019 Report, published in February of this year. This indicates that Suki is a top-of-mind emerging company among provider organizations—leaving us with a desire to learn and understand more about Suki, a digital-assistant product (no human intervention required to create the documentation) and the virtual-scribe market (where human intervention is still required to complete the documentation) and to share with you what we’ve gathered thus far. This First Look is made up of our own thoughts and opinions as an independent market research and analyst firm—after reviewing the market and the years of data around physician EHR experiences and having an in-depth discussion with Suki’s CEO. We (KLAS) look forward to publishing a KLAS Spotlight on Suki in 2019, which will include perspectives and thoughts from live customers about the performance of and their overall experience with Suki.

The Problem 

Physicians are forced to use inefficient keyboards and mouses with an EHR to document patient notes. That causes the physicians to spend more time interacting with the EHR than the patients. This environment can be a component of physician burnout.

The Solution 

Suki is creating a voice-recognition/natural language processing (NLP) solution that can run on any laptop, android, or native iOS device, enabling the physician to use conversational language to generate patient notes. Suki is creating this solution on the foundation of Google speech recognition and AutoML Natural Language, and other asynchronous speech-recognition environments. This foundation provides the ability to create effective ontologies used in NLP as the application learns the vocabularies used by the physicians in their specialty. This approach will eliminate the need for providers to acquire proprietary devices (e.g., Alexa) to support the virtual-scribe application.

Suki claims to be integrated with several EHR vendors, including athenahealth, Cerner, eClinicalWorks, and Epic. Suki is committed to using an API based on FHIR standards to accommodate the integration of their tool with EHRs. New capabilities with AthenaHealth such as the ability to query the EHR using Suki voice recognition in order to access medication records, problem lists, and diagnostic results are available.

Suki claims that it takes physicians an average of 24 minutes to be fully onboarded with the tool and that, once in use, the average physician rating of the application’s capabilities is 9 out of 10.

Suki’s tool has been implemented in approximately 50 locations in the US, with recent implementations at Sutter Health and five Ascension ministries.

The Justification 

Eliminating death by a thousand clicks for physicians using EHRs will improve care delivery efficiency while also reducing physician burnout. Patient engagement during the patient interaction will likely drive higher levels of patient satisfaction. The ability to load the Suki application onto any Android device, laptop, or smartphone will also increase workflow flexibility and mobility. Ease of integration and onboarding of physicians are key considerations for providers evaluating IT solutions. The ability to onboard a physician in 30 minutes or less should be a selection criterion for any virtual-scribe solution.

The Players 

Representative vendors in the voice-solution market for medical documentation are legacy voice-recognition vendors (e.g., Nuance and MModal), large cross-industry technology vendors (e.g., Google, Amazon, Apple, and Microsoft), and emerging companies (e.g., Suki, Sopris Health, Robin Healthcare, Augmedix, EmpowerMD, Notable, and Saykara).

Success Factors

The ability to create prototypes of virtual-scribe solutions in controlled specialty environments will enable providers to more effectively evaluate these applications for functionality, workflow integration, and cost.

The elimination of any human intervention in the virtual-scribe process should be the end result for these applications. But the accuracy of the virtual-scribe solution for creating patient notes must be closely monitored to ensure the completeness and quality of the documentation. Adjustments to physician workflows must be evaluated for potential reengineering.

Evaluate the NLP platform to determine how it is related to ontologies that support the vocabularies of various specialists. The use of NLP to generate continually evolving ontologies is a good approach if it meets the needs of the specialists using the virtual-scribe application. NLP that uses ontology-data schemas can be very effective but usually require a different schema for each specialty, and the NLP must be manually updated when adjustments are necessary.


Suki represents an emerging innovator in the voice-solution market for medical documentation. The technology based on Google speech and AutoML Natural Language, and other asynchronous speech recognition environments will provide flexibility for organizations that are not locked into other mobile technologies. The ability to run virtual-scribe applications on several mobile devices (e.g., phones, tablets, and laptops) will enable a more effective integration with existing or reengineered workflows. The ability to quickly train physicians on effective uses of the applications is also a bonus. API integration with EHRs provides a layer of physician interactions that should reduce physician burnout.

Innovative companies entering healthcare present a higher risk proposition for long-term viability. In most cases, successful new market entrants are likely to be acquired by larger companies who have a buy-rather-than-build strategy for expanding their healthcare IT portfolios. Acquired companies may also generate higher risks if their parent company does not have a successful track record of integrating and growing their acquisitions.

     Photo cred: Adobe Stock, peshkova



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