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WVU Medicine West Virginia University Health System to Advance Clinical Documentation Strategy and Drive EHR Adoption with M*Modal Solutions

Published on May 8, 2017

The M*Modal cloud-based documentation platform chosen for its top-ranking speech and real-time cognitive technologies to improve outcomes at nine affiliate hospitals

Franklin, TN – May 8, 2017 – M*Modal, a leading provider of clinical documentation and Speech Understanding™ solutions, today announced it will provide WVU Medicine with its artificial intelligence enabled documentation platform to reduce the administrative burden on 1,500 physicians while improving clinical and financial outcomes. WVU Medicine, a premier healthcare organization comprising nine hospitals including a 645-bed academic medical center and multiple physician practices, is in the midst of deploying the Epic EHR system. M*Modal market-leading solutions will help clinicians at WVU Medicine document quickly, accurately and completely in their Epic system, both in inpatient and outpatient care settings.

Upgrading from a legacy voice recognition product, WVU Medicine selected M*Modal to revitalize and standardize clinical documentation processes across the growing enterprise. Additionally, M*Modal’s long-standing collaboration with Epic to power applications such as Epic NoteReader as well as the real-time clinical intelligence delivered with M*Modal Computer-Assisted Physician Documentation (CAPD) were key deciding factors. To meet WVU Medicine’s goal of higher physician adoption and utilization of speech recognition technology to reduce cost and improve quality, M*Modal in-house Adoption Services will deliver differentiating expertise, training and responsiveness.

The Best Speech-Driven Solutions

With this strategic partnership, WVU Medicine will utilize top-ranking M*Modal solutions to empower both its front-end physician users and back-end medical editors transcribing over 25 million lines annually. The M*Modal speech-enabled documentation platform includes both #1 Best in KLAS, Speech Recognition: Front-End EMR, M*Modal Fluency Direct®, and #1 KLAS Category Leader, Speech Recognition: Back-End, M*Modal Fluency for Transcription®.

“We expect M*Modal CAPD to significantly reduce time-consuming, retrospective physician queries that are very disruptive to clinicians and labor intensive for nurses and CDI specialists,” said James Venturella, Vice President and CIO of WVU Medicine West Virginia University Health System. “We are excited to leverage the M*Modal real-time natural language understanding technology to bring Clinical Documentation Improvement (CDI) to the front-end documentation workflow in Epic, which will free up back-end resources, improve chart documentation, support more appropriate reimbursement and deliver a significant return on investment.”

“We are proud to serve as a collaborative partner to West Virginia University Medicine to deliver next-generation documentation solutions with an extensible technology framework for a growth-enabling documentation strategy,” said Michael Finke, President of M*Modal. “Given our fully-aligned goals of improving the physician documentation experience, freeing up physician time for patient care and meeting organizational objectives on better clinical, financial and operational outcomes, we look forward to early and sustained success.”

Driving Physician Satisfaction and Engagement

With this multi-facility deployment, M*Modal will help unify workflows and empower multiple stakeholders at WVU Medicine. M*Modal Fluency Direct  provides front-end speech recognition with embedded CAPD functionality for delivering real-time and in-workflow clinical insights to physicians as they dictate or type in over 120 EHRs. Used in conjunction with M*Modal CDI EngageTM, this closed-loop documentation solution continually analyzes the clinical note, suggests improvements in quality and compliance, and reports on physician engagement with the system for a uniquely effective and targeted approach. M*Modal Fluency for Transcription delivers advanced back-end workflow management capabilities to significantly boost the productivity of in-house medical editors at WVU Medicine with efficiency-enhancing and quality-assurance functionality. All these solutions are powered by the same artificial intelligence enabled technology platform and a single user voice profile so that physicians can effectively capture the complete patient story, irrespective of how or where they document care.

About M*Modal

M*Modal is a leading healthcare technology provider of advanced clinical documentation solutions, enabling hospitals and physicians to enrich the content of patient electronic health records (EHR) for improved healthcare and comprehensive billing integrity. As one of the largest clinical transcription service providers in the U.S., with a global network of medical editors, M*Modal also provides advanced cloud-based Speech Understanding™ technology and data analytics that enable physicians and clinicians to include the context of their patient narratives into electronic health records in a single step, further enhancing their productivity and the cost-saving efficiency and quality of patient care at the point of care. For more information, please visit, Twitter, Facebook and YouTube.

About West Virginia University Medicine (WVU)

WVU Medicine unites the physicians of West Virginia University with the hospitals, clinics, and health professionals of the West Virginia University Health System. Together, they are a national leader in patient safety and quality, and are unified and driven by a passion to provide the most advanced healthcare possible to the people of West Virginia and beyond. WVU Medicine includes the physicians, specialists, and sub-specialists of the West Virginia University School of Medicine; the affiliated schools of the WVU Health Sciences Center; four community hospitals; three critical access hospitals; and a children’s hospital, all anchored by a 645-bed academic medical center that offers tertiary and quaternary care.


Media Contact:
Aparna Prabhakar