30 results.
Transcription Turnaround Time for Common Document Types
Author: AHIMA and MTIA Joint Task Force on Standards Development
Source: Perspectives in Health Information Management | AHIMA report
Publication Date: July 2008
This white paper discusses the current state of the industry relative to turn-around time for selected work types, and how changes may impact operational efficiency, enrich data capture, further empower clinical decision making, and enhance patient care.
Transcription Beyond Transcription: Health IT allows transcriptionists to assist with CDI, other HIM functions
Author: Carnrite, Michael; Sumner, Susan
Source: Journal of AHIMA
Publication Date: October 2012
For decades Medical transcription has been an important fixture of the health information management (HIM) department. Compiling, managing, and retaining transcribed documents as a subset of the entire patient medical record is a foundational role for HIM professionals. And while the electron....
Tomorrow's Transcription Tools: What New Technology Means for Healthcare
Author: Weber, Joe
Source: Journal of AHIMA
Publication Date: March 2003
What does the future hold for the transcription industry? In the third installment of the Journals series on transcription, take a look at the new technology aimed at boosting productivity, improving accuracy, and, in some cases, asking physicians for direct information input.
The y....
Success with Speech Recognition
Author: Clawson, Cathy
Source: AHIMA Convention
Publication Date: September 28, 2010
Introduction: Since Mountain States Health Alliance implemented the Dolbey Speech Recognition platform in October 2007; gains in productivity, decrease in outsourcing, and financial savings have confirmed the successful implementation of this technology.
Background/History: Mountain Sta....
Speech Recognition Systems Help Secure Documents
Author: Dolphin, Peter J.
Source: In Confidence (newsletter)
Publication Date: September 02, 2003
Clinician dictation remains a key component of data gathering for the patient record.While this is no surprise to many, dictation’s usage was widely predicted to decline as healthcare delivery organizations implemented computerized electronic health records (EHRs). The reality is that the quan....
Speech Recognition Propels Transcription Revolution
Author: Schwager, Rob
Source: Journal of AHIMA
Publication Date: October 2000
Speech recognition technology continues to develop. Now, with additional enhancements, the latest models offer solutions for entire enterprises. The author rounds up the latest developments.
Most healthcare organizations and clinicians today have automated some portion of their health in....
Speech Recognition in the Electronic Health Record. Glossary
Author: AHIMA Task Force
Source: AHIMA Task Force
Publication Date: October 20, 2003
This practice brief has been updated. See the latest version here. This version is made available for historical purposes only.
Speech Recognition in the Electronic Health Record. Appendix B: Best Practices for Using Speech Recognition
Author: AHIMA Task Force
Source: AHIMA Task Force
Publication Date: October 20, 2003
This practice brief has been updated. See the latest version here. This version is made available for historical purposes only.
Speech Recognition in the Electronic Health Record. Appendix A: Work Flow Diagram
Author: AHIMA Task Force
Source: AHIMA Task Force
Publication Date: October 20, 2003
This practice brief has been updated. See the latest version here. This version is made available for historical purposes only.
Speech Recognition in the Electronic Health Record (2013 update)
Author: AHIMA
Source: AHIMA practice brief | Journal of AHIMA
Publication Date: September 2013
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....
Speech Recognition in the Electronic Health Record [2003 table of contents]
Author: AHIMA Task Force
Source: AHIMA Task Force
Publication Date: October 2003
This practice brief has been updated. See the latest version here. This version is made available for historical purposes only.
Speech Recognition in the Electronic Health Record (2003)
Author: AHIMA Task Force
Source: AHIMA practice brief
Publication Date: October 2003
This practice brief has been updated. See the latest version here. This version is made available for historical purposes only.
Speaking of That: Using Speech Recognition in Radiology
Author: Demorsky, Susan
Source: AHIMA Convention
Publication Date: October 31, 2006
Background
For decades the HIM profession has been aware of the evolving technology of speech recognition. Viewed as experimental, its use was limited to cutting edge physicians and medical centers. Its use was driven more from curiosity than practicality. Physicians would convince hospital ad....
Putting it All Together: Shands Healthcare Improves Transcription Productivity with a Global Platform and ASR
Author: Starling, Lee; Rollins, Pam
Source: AHIMA Today
Publication Date: October 13, 2008
NLP and Text Mining: Their Role in the EHR
Author: Jagannathan, V.; Heinze, Daniel T.; Naeymi-Rad, Frank; Flanagan, James R.; Bowie, Jack; Kapit, Andrew; van Terheyden, Nick
Source: AHIMA Convention
Publication Date: October 31, 2006
Introduction
The national spotlight is on the cost and questionable quality of healthcare and the numerous ways electronic health records will improve both. There is, therefore, increasing pressure to make this an industry-wide reality within just a few short years. As good corporate cit....
Natural Language Processing Technology and Terminologies: Mining Free Text
Author: Jagannathan, V.; Heinze, Daniel T.; Naeymi-Rad, Frank; Flanagan, James R.; Bowie, Jack; Kivatinetz, Raul
Source: AHIMA Convention
Publication Date: October 21, 2005
Introduction
The dictation and transcription process is one of the most widely used ways of documenting clinical content. This session brings leading vendors with NLP and terminology solutions to discuss their approach and technologies in support of data mining of free text. The applications t....
Medical Dictation: A New Generation
Author: Groner, Gabriel F.
Source: Journal of AHIMA
Publication Date: June 1999
As the term implies, automatic speech recognition is a computer's recognition of speech, automatically converting it into readable text and interpretable commands. To fully understand automatic speech recognition, one must first be aware of the distinction between speech recognition an....
Lessons Learned from Implementation of Voice Recognition for Documentation in the Military Electronic Health Record System
Author: Hoyt, Robert; Yoshihashi, Ann
Source: Perspectives in Health Information Management
Publication Date: January 2010
Abstract
This study evaluated the implementation of voice recognition (VR) for documenting outpatient encounters in the electronic health record (EHR) system at a military hospital and its 12 outlying clinics. Seventy-five clinicians volunteered to use VR, and 64 (85 percent) resp....
Journey Continues: Server-based Speech Recognition
Author: Derynck, Arleen; Olevson, Pat; Owen, Betsy
Source: AHIMA Convention
Publication Date: September 23, 2002
If You Say It, It Will Be So: Advances in Speech Recognition Technology
Author: van Terheyden, Nick; Doyle, Karen
Source: AHIMA Convention
Publication Date: October 15, 2004
Presentation Overview
The aim of this article is to provide an overall understanding of Speech Recognition technology with examples of how it relates to healthcare. First, we will look at the history of speech recognition and provide a description of speech recognition technology and its....
How Can I Use Speech Recognition to Benefit My Organization?
Author: Spring, Christopher
Source: AHIMA Convention
Publication Date: October 10, 2007
Background
Speech recognition is definitely a hot topic in the information management market. The problem is that no one really understands it. The purpose of this presentation is to educate health information management professionals on the benefits that the use of speech recognition ca....
Generating Discharge Summaries in the MIS and Using Speech Recognition Software
Author: Loos, Markus
Source: IFHRO Congress | AHIMA Convention
Publication Date: October 15, 2004
Introduction
The Charité--University of Medicine Berlin, is the largest hospital in Europe. Its four campuses have about 2,300 beds. The 9,384 employees care for about 100,000 inpatients and about 250,000 ambulatory patients per year. Approximately 4,900 students are instructed in....
Determine if Speech Recognition Technology Is Right for You
Author: Charest, Todd; Kosegi, Lynn
Source: AHIMA Convention
Publication Date: October 31, 2006
Determine if Speech Recognition Technology Is Right for You
Todd Charest, MBA, and Lynn Kosegi, PMP The Question
Is speech recognition technology right for your organization?
Speech recognition (SR) has the potential to increase the productivity of both physicians and medical transc....
Current State of Speech Recognition: Despite High Accuracy and Growing Interest, Behavioral Barriers Remain
Author: Fallati, Donald T.
Source: Journal of AHIMA
Publication Date: April 2006
Speech recognition has moved beyond the experimental early-adopter stage, and while it has a way to go before it becomes truly widespread, the technology is actively deployed in hundreds of healthcare institutions. Adopters span the spectrum of inpatient and outpatient facilities, academic and....
Continuous Speech Recognition: What You Should Know
Author: Clark, Holly
Source: Journal of AHIMA
Publication Date: October 1998
Is speech recognition a futuristic dream, an emerging technology, or a current reality? How vital is speech input to a computerized patient record strategy? How can you influence your organization to investigate speech recognition options that best meet its needs? There are no simple answers t....
Better and Faster: New Systems Make Report Processing Easier
Author: Krautwald, Peter
Source: Journal of AHIMA
Publication Date: October 2001
Voice recognition, electronic signature, combined system interfaces-the future is now in many HIM departments. In this article, the author focuses on the use of advanced report processing technologies in HIM departments and how they are changing the way we work.
Technology and....
Attacking the Rising Cost of Transcription: the Return on Investment of Speech Recognition
Author: Embke, James; Fallati, Donald T.
Source: AHIMA Convention
Publication Date: September 23, 2002
Analysis of the Implementation and Impact of Speech-Recognition Technology in the Healthcare Sector
Author: Parente, Ronaldo; Kock, Ned; Sonsini, John
Source: Perspectives in Health Information Management
Publication Date: June 2004
This research was sponsored by a grant from the American Health Information Management Association (AHIMA) Foundation of Research and Education (FORE).
Abstract
This paper develops a conceptual framework and offers research propositions for understanding the adoption of....
Ambulatory Payment Classification System Challenges Drive Coding Technology Changes
Author: Servais, Cheryl
Source: IFHRO Congress | AHIMA Convention
Publication Date: October 15, 2004
The outpatient prospective payment system, implemented in August 2000, introduced two significant challenges to those responsible for gathering the codes necessary to determine the expected payment for services. The challenges are:
(1) How to bring all the CPT-4 codes together in one fil....
Advancing Technology Connects Transcription and Coding: The Developing Role of NLP, NLU, and CAC in HIM
Author: Dooling, Julie A
Source: Journal of AHIMA
Publication Date: July 2012
For many years transcription and coding departments have been two separate and independent structures within health information management (HIM).
While these areas have always been interdependent regarding their need to share documentation, their technology platforms have op....