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Sep 27 2012   12:38PM GMT

Voice recognition: With better communication comes better patient care

Posted by: adelvecchio
dictation, Dragon, EHR, Natural language processing, NLP, patient care, Voice recognition

Guest post by: Dr. Steve Tai, Heritage Medical Associates

Communication and documentation of patient encounters is one of the most important aspects of patient care, aside from actual medical decision making. Documentation is time consuming, labor intensive, and little fun. Doctors went to medical school to take care of patients – not to be scribes or data managers.  Physicians have taken various approaches to recording patient encounters in their electronic health records (EHRs) in response to the push toward EHR adoption. This has commonly led to a point-and click-method/ menu-driven approach to documenting and communicating.  For this reason, physician notes no longer truly reflect our thought process.  Instead, patient notes are a mere reflection of the many radio buttons one can click to document patient history, physical visits, and medical plan of action. I realized that this was no way to accurately and completely document a patient encounter. A patient is a story in my eyes, not a template or check box.  Let me tell you what I did to fix this.

I’m fortunate to have been using EHRs for 15 years.  In 1997, I joined a multi-specialty practice in Florida that had been operating with all clinical encounters documented electronically for several years. I was one of the first physicians who accessed patient information electronically (using an early version of a wireless tablet) in the exam room without relying on a paper chart. Unfortunately, our ability to document at the point-of-care did not exist; rather we would Dictaphone what we remembered or provide notes for a transcriptionist to transcribe later.

In 2002, when I began practicing medicine at my current practice based in Tennessee, my “electronically-savvy” world changed because the practice was still using a paper chart with handwritten notes! Of course, I would’ve used an EHR but the thought of typing my notes after having the benefit of a transcriptionist was not ideal. I had to find an effective method of documenting my notes. Thankfully, this was around the same time that I was introduced to voice recognition, specifically Dragon Medical, and I haven’t looked back since.

Given my experience with both back-end voice recognition (dictating into a Dictaphone for a transcriptionist to then document and edit) and front-end voice recognition (documenting and editing my own notes) I choose the latter of the two. Front-end dictation allows me to truly capture and document my thought process. Using voice recognition saves me about an hour daily. My notes are typically completed at the end of the workday or at the end of the patient visit. Voice recognition improves efficiency by completing my notes in a timely fashion. When I have to transfer care immediately to a specialist the same day, it is especially helpful. The specialist receives full context of the reason for the consultation and a brief summary of the patient’s medical history. Patient care is facilitated with a written document in addition to a personal phone call.

I hope to improve patient care and streamline workflow by recording actionable patient data received through a combination of natural language processing and Dragon Medical technologies. This will help me take my documentation to the next level.

My experience with voice recognition over these past 10 years has been an extremely positive one.  Documentation of the spoken word is a powerful tool. My efficiency has improved along with my quality of care as voice recognition and hardware technology has progressed.  I am pleased that I can have more time in my day to spend focused on my patients. Voice-enabling my EHR workflow has allowed me to work smarter, but not harder.

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