Advertisement

Journal of Digital Imaging

, Volume 21, Issue 4, pp 378–382 | Cite as

Improvement of Report Workflow and Productivity Using Speech Recognition—A Follow-up Study

  • Mika P. Koivikko
  • Tomi Kauppinen
  • Juhani Ahovuo
Article

Abstract

Speech recognition (SR), available since the 1980s, has only recently become sufficiently reliable to allow utilization in medical environment. This study measured the effect of SR for the radiological dictation process and estimated differences in report turnaround times (RTTs). During the transition from cassette-based reporting to SR, the workflow of 14 radiologists was periodically followed up for 2 years in a university hospital. The sample size was more than 20,000 examinations, and the radiologists were the same throughout the study. A RTT was defined as the time from imaging at the modality to the time when the report was available for the clinician. SR cut down RTTs by 81% and the standard deviation by 83%. The proportion of reports available within 1 h escalated from 26% to 58%. The proportion of reports created by SR increased during a follow-up time of this study from 0% up to 88%. SR decreases turnaround times and may thus speed up the whole patient care process by facilitating online reporting. SR was easily adopted and well accepted by radiologists. Our findings encourage the utilization of SR, which improves the productivity and accelerates the workflow with excellent end-user satisfaction.

Key words

Speech recognition productivity report workflow report turnaround time 

References

  1. 1.
    White KS: Speech recognition implementation in radiology. Pediatr Radiol 35:841–846, 2005PubMedCrossRefGoogle Scholar
  2. 2.
    Vorbeck F, Ba-Ssalamah A, Kettenbach J, Huebsch P: Report generation using speech recognition in radiology. Eur Radiol 10:1976–1982, 2000PubMedCrossRefGoogle Scholar
  3. 3.
    Trumm C, Francke M, Küttner B, Nissen-Meyer S, Reiser M, Glaser C: Speech recognition: impact on report availability and clinical workflow. Hosp Imaging Radiol Eur 1:14–16, 2006Google Scholar
  4. 4.
    Voll K, Atkins S, Forster B: Improving the utility of speech recognition through error detection. J Digit Imaging, DOI  10.1007/s10278-007-9034-7, 2008 (in press)
  5. 5.
    Eng J, Eisner JM: Radiology report entry with automatic phrase completion driven by language modeling. Radiographics 24:1493–1501, 2004PubMedCrossRefGoogle Scholar
  6. 6.
    Deng L, Erler K: Structural design of hidden Markov model speech recognizer using multivalued phonetic features: comparison with segmental speech units. J Acoust Soc Am 92:3058–3067, 1992PubMedCrossRefGoogle Scholar
  7. 7.
    Liu D, Zucherman M, Tulloss WB Jr: Six characteristics of effective structured reporting and the inevitable integration with speech recognition. J Digit Imaging 19:98–104, 2006PubMedCrossRefGoogle Scholar
  8. 8.
    Reiner B, Siegel E: Radiology reporting: returning to our image-centric roots. Am J Roentgenol 187:1151–1155, 2006CrossRefGoogle Scholar
  9. 9.
    Talton D: Perspectives of speech recognition technology. Radiol Manage 27(38–40):42–43, 2005Google Scholar
  10. 10.
    Sistrom CL: Conceptual approach for the design of radiology reporting interfaces: the talking template. J Digit Imaging 18:176–187, 2005PubMedCrossRefGoogle Scholar
  11. 11.
    Pezzullo JA, Tung GA, Rogg JM, Davis LM, Brody JM, Mayo-Smith WW: Voice recognition dictation: radiologist as transcriptionist. J Digit Imaging, DOI  10.1007/s10278-007-9039-2, 2008 (in press)
  12. 12.
    Langer SG: Impact of speech recognition on radiologist productivity. J Digit Imaging 15:203–209, 2002PubMedCrossRefGoogle Scholar
  13. 13.
    Langer SG: Impact of tightly coupled PACS/speech recognition on report turnaround time in the radiology department. J Digit Imaging 15:234–236, 2002PubMedCrossRefGoogle Scholar
  14. 14.
    Rana DS, Hurst G, Shepstone L, Pilling J, Cockburn J, Crawford M: Voice recognition for radiology reporting: is it good enough? Clin Radiol 60:1205–1212, 2005PubMedCrossRefGoogle Scholar
  15. 15.
    Mehta A, McLoud TC: Voice recognition. J Thorac Imaging 18:178–182, 2003PubMedCrossRefGoogle Scholar

Copyright information

© Society for Imaging Informatics in Medicine 2008

Authors and Affiliations

  • Mika P. Koivikko
    • 1
  • Tomi Kauppinen
    • 2
  • Juhani Ahovuo
    • 2
  1. 1.HUS Helsinki Medical Imaging CenterHelsinki University Central HospitalHelsinkiFinland
  2. 2.HUS Helsinki Medical Imaging CenterHelsinki University Central HospitalHelsinkiFinland

Personalised recommendations