title: The implementation of speech recognition in an electronic radiology practice.
abstract: For both efficiency and economic reasons, our practice (200,000 examinations) has converted all remote dictation to speech recognition transcription (PowerScribe, L & H, Burlington, MA). The design criteria included complete automation to the existing radiology information system (RIS), with full RIS capabilities immediately available following dictation. All dictations for computed tomography, magnetic resonance imaging, ultrasound, and nuclear medicine were converted from remote transcription to speech recognition over a 2-week period (following a 4-week installation phase and 8 days of training). The average turnaround time for these reports decreased from approximately 2 hours to less than 1 minute. Reports are then sent to the institutional Electronic Medical Record and are available throughout all facilities in a nominal 2 minutes. Speech recognition rates were surprisingly high, although certain phrases caused consistent difficulties and certain staff required retraining. This presents our analysis of both successful and problematic areas during our design and implementation, as well as statistical performance analyses.
authors.affiliation: Department of Radiology, Mayo Clinic Jacksonville, FL 32224, USA.
authors.forename: P J
authors.initials: PJ
authors.lastname: Lemme
authors.forename: R L
authors.initials: RL
authors.lastname: Morin
mesh_terms: D004526:Efficiency; D005431:Florida; D006801:Humans; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D011873:Radiology Information Systems; D013060:Speech; D013996:Time and Motion Studies