“Practical Use” of an EHR Using Transcription

Posted on May 12, 2010 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

In a post on EMR and EHR about Transcriptionists Partnering with an EMR Vendor, I got an interesting comment by George Catuogno from StenTel about the various technologies that the Medical Transcription (MT) industry are using alongside EMR software. George called the use of transcription with an EHR “practical use” while still showing “meaningful use.” I think it’s a mistake for any EMR company to ignore the transcription industry.

Here’s George’s description of the medical transcription technologies which I think people will find interesting:

The Medical Transcription (MT) industry actually has done a lot to advance itself amidst HIT, particularly EHR technologies, while supporting narrative dictation, which for many physicians is still the preferred method of information capture because it’s fast and easy (efficient) and it tends to more comprehensively captures the patient “story”. DRT, BESR and NLP are three examples of this. I’ll save the best for last.

1. Discrete Reportable Transcription (DRT) is the process of converting narrative dictation into text documents with discrete data elements than can be easily imported into the appropriate placeholders inside an EMR.

2. Backend Speech Recognition (BESR) has been in play for years which allows physicans to dictate without engaging the computer for realtime correction. The correction is instead done retrospectively by a medical transcriptionist. Some speech rec technologies (like M*Modal) support data structuring. The gap remains, however, in getting applications written that readily move that strucutred infomration into EHRs like DRT can.

3. Natural Language Processing (NLP) trumps both of these solutions because it takes a narrative report, regardless of how it was created, and codifies it (SNOMED) for a number of extraction, analytics and reporting applications: Patient Summary, DRT feed into an EMR, Core Measures and PQRI, coding automation, interoperability, and support for the majority of Meaningful Use requirements. Secondary use opens up to clinical trials and other applications as well.

Overall, if the transcription industry can market itself and get its messaging out through the right channels regaridng these innovations that augment transcription and keep physicians dictating, then transcription is a terrific EHR adoption facilitator, enables “practical use” along with Meaningful Use, and will remain relevant for the foreseeable future.