Posts Tagged 'radiology speech recognition'

“You can have the best scanner in the world, but if there is no report, it is worthless”

 Well said, Mr. Radiologist. In a recent interview with AuntMinnie Radiology magazine, Dr. Giles Boland, medical director of teleradiology and vice chairman of radiology at Massachusetts General Hospital (MGH) in Boston, talks about the pressure Radiologists are facing when it comes to documentation. 

The article starts off with a rather capitalistic – although realisitic- view of the 21st century reading room: “radiologists today are measured constantly, whether it is in the number of images they read, their relative value unit (RVU) activity, or their report turnaround times.” Not only that. “You can get three different radiologists to look at the same scan and they can give very different lengths and styles of interpretations,” Boland continues. “How is a referring physician to navigate through those variable styles?”

The advantage of voice recognition is that it may be counterintuitive because if radiologists have to edit that report, they naturally will shorten the number of words they put in it. They don’t want to edit a report that is five pages long.

According to Boland and colleagues as per another interview with European Radiology (March 8, 2008), the adoption of an “integrated RIS/PACS and voice recognition system” is the only path to “reducing report turnaround consistently meeting stakeholder expectations.” Voice recognition systems “also offer the opportunity to create standardized, higher-quality reports,” they wrote.

Aunt Minnie editor goes on to comment how “MGH has utilized voice recognition technology for the past 11 years. During that time, the facility has reduced the average time it takes staff to go from a preliminary report to final sign-off to approximately three hours. Total report turnaround — the time from when a study is completed to when the final report is available on the system — is 12 hours.” Boland confirms:

“The majority of the reports that are signed in this institution are within a matter of a few hours of the exam having been completed. The heightened expectations have not increased reading errors by radiologists. Instead of leaving work unfinished, radiologists also are more inclined to complete their assignments.

“There is the (amount of time between the) completion of the exam to preliminary report, which really hasn’t changed much. That is a matter of an hour or two from when it is read to the time the exam is completed. The big change is the time from the preliminary report to final signing. For those groups with no residents or fellows, preliminary reports go away, so turnaround is even quicker.”

“Radiologists have to understand what their work product is — and that is ultimately the radiology report. The clear enhancement of value in that report is when you add voice recognition, because you can get it out quicker and remove that whole redundant route with transcriptionists. You also can structure it with macros and templates, shorten the report, make it more succinct, and the whole report turnaround time is faster,” concludes Boland.


Radiology: white noise can increase speech recognition accuracy

white noise can increase speech recognition accuracy I came across the following article from Health Imaging & IT magazine this morning. According to a recent study conducted at the University of Maryland Medical Center, the introduction of white noise as part of the acoustic background has a positive impact on speech recognition accuracy…

Although radiology practices pay significant attention to the environment for diagnostic image interpretation, few give as much consideration to the acoustic workspace in which the physicians dictate their clinical report.

According to Joseph Zwemmer, MD, who presented the results of the research at the 93rd annual meeting of the Radiological Society of North America (RSNA), speech recognition technology is now used by almost half of the academic and approximately 25 percent of private practices in diagnostic radiology.

Zwemmer reported that dictated reports were compared to the original report to determine the number of errors present. The researchers found that the mean baseline transcription error rate (TER) was 11.6 percent (range 6.5 percent26.1 percent). However, the TER at the four white noise levels was 10.3 percent, 12.3 percent, 13 percent and 13.5 percent, respectively.

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