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Speech Recognition in the Electronic Health
Record (2013 update)
Introduction
Many technologies exist to assist with better clinical documentation and speech recognition technology (SRT) is one
solution. Since SRT uses mathematic probabilities, the technology can be complicated. The goals of its use in
healthcare today, however, are clear: Increase productivity, decrease costs, and improve documentation while
placing it closest to the point of care.
This practice brief focuses on increasing the understanding of how speech recognition works by highlighting the
driving forces that are shaping current and future applications of this technology and its associated benefits and risks.
This practice brief also provides tools including illustrated work flow, tasks and skills, and best practices to assist in
efficient and effective application of SRT for day-to-day operations.
Driving Forces
Payment reform. Quality measures. Meaningful use. EHR adoption. Transition to ICD-10-CM/PCS. Health
information exchange. Consumer engagement. Personal health records and patient portals. What do these areas have
in common? They all point to the increasing need for accurate, complete, and accessible data in an environment that
requires real-time documentation.
Documentation should improve the quality of the patient encounter and create efficiencies.
In the past, handwriting provided an immediate record of care. Legibility came to the forefront as an issue and
documentation was often not as comprehensive when compared to a well-constructed dictated note. Today, speech
recognition or speech-to-text is used in conjunction with the EHR and is considered a viable option in the face of the
growing demand for near-real-time data.
Front-end speech recognition (FESR) and back-end speech recognition (BESR) technologies can help in the
production of legible and comprehensive document(s). It also serves as a productivity tool to help lower costs and
increase productivity, especially when compared to the manual labor required by traditional dictation and
transcription.
Emerging Roles
In 2012, The Association for Healthcare Documentation Integrity (AHDI) coined the term "healthcare
documentation specialist (HDS)," which they define as "an umbrella term that includes medical transcriptionists,
speech recognition editors and QA specialists."1
For the purposes of this practice brief, the term "HDS" will be used when referring to this role. Visit AHDI's website
for more information on the role of the HDS (www.ahdi.org).
Copyright © 2013 by The American Health Information Management Association. All Rights Reserved.
http://www.ahima.org/copyright
The use of medical scribes is increasing in various healthcare settings due to growing EHR implementations and the
need for timely, detailed point-of-care documentation.
There are distinct differences between HDS and scribes. HDS professionals work in a "one-way process" while
scri.
Speech Recognition in the Electronic Health
Record (2013 update)
Introduction
Many technologies exist to assist with better clinical documentation and speech recognition technology (SRT) is one
solution. Since SRT uses mathematic probabilities, the technology can be complicated. The goals of its use in
healthcare today, however, are clear: Increase productivity, decrease costs, and improve documentation while
placing it closest to the point of care.
This practice brief focuses on increasing the understanding of how speech recognition works by highlighting the
driving forces that are shaping current and future applications of this technology and its associated benefits and risks.
This practice brief also provides tools including illustrated work flow, tasks and skills, and best practices to assist in
efficient and effective application of SRT for day-to-day operations.
Driving Forces
Payment reform. Quality measures. Meaningful use. EHR adoption. Transition to ICD-10-CM/PCS. Health
information exchange. Consumer engagement. Personal health records and patient portals. What do these areas have
in common? They all point to the increasing need for accurate, complete, and accessible data in an environment that
requires real-time documentation.
Documentation should improve the quality of the patient encounter and create efficiencies.
In the past, handwriting provided an immediate record of care. Legibility came to the forefront as an issue and
documentation was often not as comprehensive when compared to a well-constructed dictated note. Today, speech
recognition or speech-to-text is used in conjunction with the EHR and is considered a viable option in the face of the
growing demand for near-real-time data.
Front-end speech recognition (FESR) and back-end speech recognition (BESR) technologies can help in the
production of legible and comprehensive document(s). It also serves as a productivity tool to help lower costs and
increase productivity, especially when compared to the manual labor required by traditional dictation and
transcription.
Emerging Roles
In 2012, The Association for Healthcare Documentation Integrity (AHDI) coined the term "healthcare
documentation specialist (HDS)," which they define as "an umbrella term that includes medical transcriptionists,
speech recognition editors and QA specialists."1
For the purposes of this practice brief, the term "HDS" will be used when referring to this role. Visit AHDI's website
for more information on the role of the HDS (www.ahdi.org).
Copyright © 2013 by The American Health Information Management Association. All Rights Reserved.
http://www.ahima.org/copyright
The use of medical scribes is increasing in various healthcare settings due to growing EHR implementations and the
need for timely, detailed point-of-care documentation.
There are distinct differences between HDS and scribes. HDS professionals work in a "one-way process" while
scri.
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