{Voice Recognition

Efficiency in Internal Medicine DocumentationInternal Medicine Noon Conference – 11.24.10

Samuel Ash, MDResident, Department of Internal MedicineUniversity of Washington Medical Center

Problem Technology Experience Conclusions/Discussion References Demonstration Other Strategies

Outline

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

Problem

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/)

Technology

Technology

Outpatient Pediatric Specialty Practice 2 hours of training + 30

“training” notes 42 “test” notes Endpoints: time and

accuracy

Experience

Experience

Experience

Additional Results 600 new consultations and

1200 repeat visits per year Average letter/note length

225 words

Experience

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

Surgical Pathology Decreased turnaround times

(by ~81%) Decreased error rate (by

~48%)

Experience

Conclusions/Discussion

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

Demonstration

Other Strategies