Yesterday afternoon, as the snow continued to fall here in Brooklyn, the DHL delivery man brought me the latest medical speech recognition software from Nuance Communications, Dragon NaturallySpeaking 9 Medical. I'm not only interested in streamlining my workflow when writing on oncology and medical technology topics, but also speech-driven clinical documentation. This allows the physician to customize patient data in an EMR that pick lists won't allow.
This story by Eric Fishman, MD of EMRConsultant.com, tells of his experience using templates for capturing data in an EMR versus using speech recognition. [Disclosure: He's a reseller for this software.] His point is that although much of the patient interview process is about clearly defined reponses to standard questions, eventually these patient records begin to look alike if you're limited to using pick lists.
While data dictated by speech recognition and transcribed as free text is not easily parsed and distributed to third parties, it does have some advantages:
- It helps the physician create a record that paints a mental picture of each patient, so that they can be remembered individually
- A plan of care can be described so that when the physician selects "chest pain" as a symptom, he or she can elaborate why a cardiac cause has been ruled out
It does take some effort on the part of the person dictating in developing a good dictation technique. When I was a pathology resident, I gained an expertise in dictating observations as I did my dissections of specimens. These tapes were later given to a transcriptionist who typed out the reports.
As far as producing a convincing story that explains a topic in an interesting way, some forethought is needed, but you still can expect to do some editing afterwards. If you don't, you wind up with a written piece that's a tad bit too chatty--you're caught up in a web of circumlocution, and the reader doesn't have a clear idea of the points you're making.
Now for the unboxing. You can see in the photo that the package contains 3 CDs, a manual and a headset with a boom mike.
Installation occurred without a hitch, and it was just a matter of plugging in the headset into the sound card of my PC with the headphone and mike jacks.
It had me read a few paragraphs for the initial training. Then it scanned my Word docs and Outlook e-mail to get an insight into how I write. I wonder if they should give you the option of choosing which files to look at because some of my Word docs are culled from the Web, and my e-mail tends to be telegraphic with a few exceptions including the occasional angry rant at Apple for something iTunes screwed up again.
Next, I was given the choice and reading a medical passage, ranging from easy to hard. I chose the hard just to get the most mileage from my spent doing this. It was a typical surgical procedure dictation. This is was about placing a cardiac catheter via a groin stick. I started the video training feature, but it sparked my memory of when I was using the regular version of Pro 9, so I skipped it and proceeded with testing its accuracy.
You have to keep in mind that this is the hardest test for this software, since as you use the software more, it becomes better acclimated to your speech. These both were the first attempts at reading these oncology passages. The first paragraph is what I was reading, and the second in red is what the software transcribed:
In Burkitt's lymphoma, the c-myc oncogene is
activated by translocation of genetic material from chromosome 8 to chromosome
14. Chronic myelogenous leukemia (CML) is defined by a reciprocal translocation
of the long arms of chromosomes 9 and 22, resulting in the generation of a
fusion protein (BCR-ABL) with tyrosine kinase activity.
In Burkitt's lymphoma, the C.
MIC on go gene is activated by translocation of genetic material from
chromosome 8 to chromosome 14. Chronic
myelogenous leukemia (CML) is defined by reciprocal translocation of the long
arms of chromosomes and 9 and 22, resulting in the generation of the fusion
protein (BCR-ABL) with tyrosine kinase activity.
I picked this passage specifically for "c-myc oncogene" term. What I said was "see mick oncogene," which is the way I would pronounce it if I were giving a talk. From what I understand so far, I can produce a voice macro that will allow me say something like, "Charlie hyphen m-y-c oncogene" and it will produce this term with the proper italicization.
Treatment of HER-2/neu-positive early-stage breast
cancer with the combination of chemotherapy and the targeted agent trastuzumab
has resulted in striking improvements in outcome so much so that finding this
gene not only predicts response to treatment but also a lower risk of
recurrence.
Treatment
of HER-2/neu positive early-stage breast cancer with the combination of
chemotherapy and a targeted agent trastuzumab has resulted in striking
improvements in outcome so much so that finding this gene not only predicts
response to treatment but also a lower risk of recurrence.
The next passage really impressed me considering the only error was a missed hyphen after "neu" which may really not be needed, and the lack of italicization. Getting "trastuzumab" correct shows the benefit of having a comprehensive medical vocabulary.
In future posts, I'll try to give some more helpful hints for using this software. In the meantime, you can discuss this topic on these speech recognition forums:
ScanSoft
SpeechComputing
VoiceRecognition
KnowBrainer
