Speech recognition: impact on workflow and report availability

With ongoing technical refinements speech recognition systems (SRS) are becoming an increasingly attractive alternative to traditional methods of preparing and transcribing medical reports. The two main components of any SRS are the acoustic model and the language model. Features of modern SRS with continuous speech recognition are macros with individually definable texts and report templates as well as the option to navigate in a text or to control SRS or RIS functions by speech recognition. The best benefit from SRS can be obtained if it is integrated into a RIS/RIS-PACS installation. Report availability and time efficiency of the reporting process (related to recognition rate, time expenditure for editing and correcting a report) are the principal determinants of the clinical performance of any SRS. For practical purposes the recognition rate is estimated by the error rate (unit ''word''). Error rates range from 4 to 28%. Roughly 20% of them are errors in the vocabulary which may result in clinically relevant misinterpretation. It is thus mandatory to thoroughly correct any transcribed text as well as to continuously train and adapt the SRS vocabulary. The implementation of SRS dramatically improves report availability. This is most pronounced for CT and CR. However, the individual time expenditure for (SRS-based) reporting increased by 20-25% (CR) and according to literature data there is an increase by 30% for CT and MRI. The extent to which the transcription staff profits from SRS depends largely on its qualification. Online dictation implies a workload shift from the transcription staff to the reporting radiologist. (orig.)