Types of Speech Recognition Technology

Types of Speech Recognition Technology

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Though EMRs reduced the volume of physician dictation, traditional dictation is still considered as an effective means of documenting patient encounter, especially when it comes to narrative style documentation. This may result in the increasing use of speech recognition technology (SRT) with EMRs as this technology supports both dictation and automation. With this, it is possible to generate comprehensive documentation without spending too much time. The technology has significantly impacted the medical transcription industry also by reducing the significance

of

traditional

transcription

and

increasing

the

demand

for

transcriptionists trained in speech recognition editing.

SRT is categorized into two types, front-end and back-end technology. Each of them has their own advantages and disadvantages.

Front-end SRT When using front-end SRT, users dictate into a microphone connected to the computer running the speech recognition software and the dictation is processed and displayed as text instantaneously on the computer monitor. This technology can be integrated with EMR systems and healthcare providers can dictate the details of a patient encounter instead of typing data manually or using drop down menus to insert ‘canned text’ templates.

Back-end SRT In the case of back-end SRT, the dictation is first recorded in digital form and these audio files are processed by a speech recognition software application and converted to a draft text document. Direct interaction with the dictating user is not required in this case either during the initial creation of the text or the process of training/correcting recognition errors. An initial draft of the recognized text is created, reviewed and edited by healthcare documentation specialists (group of medical

transcriptionists,

QA

specialists

and

professionals

focus

on

documentation) rather than the dictating provider. Then, the SRT software compares the corrected version of the transcript to the initial draft. The application will learn not to make the same mistakes in due course of time and produce drafts containing few errors.

Overall, either technology requires editing to generate accurate documentation. If the responsibility of editing lies on physicians in the case of front-end technology, speech recognition editors take up that job in the back-end scenario. In most cases, physicians won’t get enough time to make corrections and if they spend time, they can’t balance their time for patient care as most of the errors are not easily recognizable in the front-end scenario. For this reason, many practices prefer backend technology. Back-end SRT in conjunction with qualified speech recognition editors can identify most of the errors either related to SRT or erroneous dictation, correct them and flag for further review. The role of SR editors is very crucial in this scenario. This job is more challenging than transcription as it requires more intense focus and concentration.

However, the front-end software is very sophisticated, can distinguish among accents and specialties and reduce physician workflow. For all these reasons, it is useful for practices where patient data is required urgently. But, what can we do with the errors? A suggestion is to make physicians work in multiple environments, some of which employ front-end while others use back-end. Short reports can be reviewed in front-end mode while detailed and complex work at back-end mode.

Speech recognition technology is being increasingly used within healthcare settings, on account of its potential for productivity enhancement. It is expected that SRT will continue to be used as the technology advances further. As for the medical transcription industry, though there may be a decrease in the volume of traditional transcription the demand for speech recognition technology editors is bound to increase.