Proponents of the technology say clinical documentation or the EHR’S via speech recognition builds a more complete patient record and help drive EHR adoption but there’s a flipside to this coin as well.
Problem of EHR’S
In general, most physicians love EHR systems (Electronic Health Records) for their ability to present information in an easy-to-access format. However, the idea of accumulation of patient information, being turned into data entry doesn’t fit too well for some. Another reason frequently given for poor EHR adoption rates are the templates and drop-down menus drive the patient interaction rather than serve as tools. Physicians report that the pre-structured responses and choices actually change or limit how they question patients. Their behavior portrays the technology rather than having it flow naturally to capture valuable action for diagnosis and treatment purposes.
To, effectively deal with these problems, some consider speech recognition technology because it enables physicians to interview patients in their customary manner and then dictate reports in free-form narrative. Two basic types of speech recognition technology are available: real-time (front-end) and background (back-end) systems.
Front-End Speech Recognition
Front-end speech recognition occurs in real time during the documentation process. The physician logs into the EHR system or opens a Microsoft Word document and dictates into a microphone or a headset. As he or she is speaking, the words the speech recognizer hears appear on the screen instantaneously. When the dictation is finished, the physician reviews the words on the screen, makes any corrections, signs it, and files it in the EHR.
Errors can occur when physicians don’t talk directly into the microphone, don’t pay attention to what they’re saying, or just don’t talk clearly. Transcriptionists identify the errors and return the document to the physician to correct and sign off. Corrections are then made by the physician in the electronic health record.
Speech recognition is so accurate that some physicians can dictate 30 to 40 charts with only one or two errors. The technology is ready for prime time, say proponents
Efficiency of speech recognition
The efficiency of speech recognition can be further enhanced through the use of macros, or subroutines within the software that extract information from the EHR. Using macros, one can reinstate dictation with the patient’s medical history, social history, family history, and the like.
The Next Evolution
Speech recognition delivers significant productivity improvements and eliminates the problem of forcing physicians to think and question patients according to EHR templates and drop-down menus. However, the technology faces one major hurdle. It cannot convert the free-form narrative produced by clinicians into structured information that can be data mined and queried by clinical systems. This also means coding and billing cannot be done automatically. Coders and billers have to review and code charts in the traditional way.
That’s where speech understanding comes in. It not only listens and transcribes, but it actually understands what the physician or clinician is saying and converts it into a structured document. It attaches semantically interoperable tags and values to the information so that computers can read it without human intervention.
Do’s and don’ts’ on Sound Input Devices
Speech recognition technologies have the potential to provide huge savings in transcription costs, but cutting corners on microphones will decrease reliability and negate some of those benefits. To take full advantage of today’s accurate speech recognizers, experts say it is wise to invest in high-quality sound input devices.
We believe that speech recognition is not as evolved or advanced as many doctors would like it to be. The output of the speech recognition software has to be proofread by an MT or a doctor himself. Now that 32 million more Americans are going to come under the umbrella of health insurance, we can take it for granted that the workload of the doctors is going to increase. Doctors do not want to waste their time proofreading documents generated by speech recognition programs. The doctors want to spend as much time with the patients as possible, as this is their job. Thus human MTs are not going anywhere, and by extension, outsourcing medical transcription work to cheaper offshore locations is also not going away anytime soon.