Voice Recognition

1. Voice Recognition Efficiency in Internal Medicine Documentation Internal Medicine Noon Conference – 11.24.10 Samuel Ash, MD Resident, Department of Internal Medicine University of Washington Medical Center

2. Problem • Technology • Experience • Conclusions/Discussion • References • Demonstration • Other Strategies Outline

3. Saturday call… • 30 hours • 10 patient • 7 admits • 3 forms per admit • Untold number of pages… Problem

4. An early 20th century transcribing pool at Sears, Roebuck and Co. • Thewomen are using cylinder dictation machines, and listening to the recordings with ear-tubes Technology • (David Morton, the history of Sound Recording History, http://www.recording-history.org/)

7. Technology

8. Technology

9. Outpatient Pediatric Specialty Practice • 2 hours of training + 30 “training” notes • 42 “test” notes • Endpoints: time and accuracy Experience

10. Experience

11. Experience

12. Additional Results • 600 new consultations and 1200 repeat visits per year • Average letter/note length 225 words Experience

13. Advantages • Average turnaround time 1 day vs. 1 week • Disadvantages • 66% less efficient in total time • VRS cost twice as much as traditional transcription (based on attending hourly rate) Experience

14. Surgical Pathology • Decreased turnaround times (by ~81%) • Decreased error rate (by ~48%) Experience

15. Conclusions/Discussion

16. Davis KH, Biddulph R and Balashek S, Automatic recognition of spoken digits. J. Acoust. Soc. Am. 1952; 24:627-642. • Issenman RM and Jaffer IH. Use of voice recognition software in an outpatient pediatric specialty service. Pediatrics 2004; 114:e290-e293. • Juang BH and Rabiner LR. Automatic Speech Recognition – A Brief History of the Technology Development. • Kang HP, Sirintrapun J, Nestler RJ and Parwani AV. Experience with voice recognition in surgical pathology at a large academic multi-institutional center. Anatomic Pathology 2010; 133:156-159. References

17. Demonstration

18. Other Strategies