Medical Transcription Knowledge Based Workers - Increasing Demand

A working from Home blog "Undress4Success - Work From Home" posted an interesting article on the Medical Transcription industry and the increased demand for Medical Transcriptionists

.... (Overseas) rates are going up too, particularly in India, because they’ve realized that they can demand higher prices thanks to growing need and scarce availability of experienced MTs

The author is right on target - Medical Editors are going to be in high demand. They are and will become key knowledge workers in healthcare. As Tom Harnish says in the blog

...qualified medical transcriptionists (MTs) are in short supply

Good news for those who fear the flatening of the world and the application of technology. Speech recogntion will improve the productivity by automating the rote task of converting the spoken word into text:

The (speech recognition) technology may increase costs by 15% to 20%, but it can increase output 100% to 200% according to one MTSO owner

But to add even more value to this process knowledge based workers will need to do more than just listen to the audio and convert this into text (either by pure typing or editing/proofing a draft output from a speech recognition engine). Adding clinical data that is machine readable and semantically interoperable between all the clinical systems being implemented in our healthcare system will become a must. That process is mostly manual and much information is lost in the avalanche of text based documents that contain the information but only in human readable form. Knowledge based workers will need to provide data elements and structure to these documents turning them into data that can be fed into clinical systems.

CDA4CDT provides an ideal common environment that is designed to flexibly cope with the varied levels of data encoding but still provide the healthcare system with the text based document that can be printed and used as it is currently. But the additional information incorporated into this file allows for semantic interoperability and data exchange at a level that EMRs want and need turning the huge volume of clinical text documents into clinical data inputs to the medical record that can be shared and exchanged between systems

Medical Editors can provide this manually by tagging documents and encoding using the CDA4CDT standard or by using speech understanding technology. Speech understadning outputs a document that is tagged and structured with clinical data. This merges the role of medical editor with a true knoweldge based fuctnion of reviewing and correcting clincal data embedded in the file and clinical document.

Medical Editors are knowledge based workers and are in short supply......