Name
Abstract | ||
|---|---|---|
Speech recognition (SR) speeds patient care processes by reducing report turnaround times. However, concerns have emerged about prolonged training and an added secretarial burden for radiologists. We assessed how much proofing radiologists who have years of experience with SR and radiologists new to SR must perform, and estimated how quickly the new users become as skilled as the experienced users. We studied SR log entries for 0.25 million reports from 154 radiologists and after careful exclusions, defined a group of 11 experienced radiologists and 71 radiologists new to SR (24,833 and 122,093 reports, respectively). Data were analyzed for sound file and report lengths, character-based error rates, and words unknown to the SR's dictionary. Experienced radiologists corrected 6 characters for each report and for new users, 11. Some users presented a very unfavorable learning curve, with error rates not declining as expected. New users' reports were longer, and data for the experienced users indicates that their reports, initially equally lengthy, shortened over a period of several years. For most radiologists, only minor corrections of dictated reports were necessary. While new users adopted SR quickly, with a subset outperforming experienced users from the start, identification of users struggling with SR will help facilitate troubleshooting and support. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s10278-013-9614-7 | J. Digital Imaging |
Keywords | Field | DocType |
Speech recognition,Radiology reporting,Workflow,Statistic analysis | Troubleshooting,Computer science,Radiology information systems,Speech recognition,Medical record,Patient care,Speech Recognition Software | Journal |
Volume | Issue | ISSN |
26 | 6 | 1618-727X |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| tomi kauppinen a | 1 | 221 | 22.58 |
| Johanna Kaipio | 2 | 65 | 10.02 |
| Mika P. Koivikko | 3 | 35 | 3.70 |