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. Technology  An early 20th century transcribing pool at Sears, Roebuck and Co.  The women are using cylinder dictation machines, and listening to the recordings with ear-tubes (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