Voice Recognition in the Electronic Health Record

Voice Recognition in the Electronic Health RecordDiane LuedtkeNursing Informatics, NSG600INANovember, 2010

Speech Recognition Definition The process of converting an acoustic signal, captured by a microphone or a telephone to a set of words.

History1952 - Recognition of single digits1964 Device exhibited at NY Worlds Fair1980s 1,000 to 20,000 word vocabulariesEarly 90s Accuracy 10% to 50% and discrete voice recognition1997 Recognition of normal speech Early 2000s Accuracy 80%

Types of Speech RecognitionIsolated - pause between wordsContinuous no pause between wordsSpontaneous extemporaneous most difficult to recognize

PropertiesSpeaker enrollmentSpeaker independentFinite state networkGeneral language modelsPerplexityExternal parameters

VariablesPhonemesAcoustic variablesWithin speaker variablesAcross speaker variablesZue, V., Cole, R., Ward, W. Speech recognition. Retrieved from http://cslu.cse.ogi.edu/HLTsurvey/ch1node4.html on 10/6/2010.

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Speech Recognition in Health CareEarliest users radiologistsMost successful early users radiologists, pathologists and emergency physicians

Photo source:www.google.com/imgres?imgurl=http://www.rsna.org/Publications/RSNAnews/November-2010/images_speech_recognition_1.jpg

8Other Healthcare SettingsPrimary care cliniciansPsychiatristsIV nurses - AccuNurse

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Primary CareTrial at US Army Medical Command in 200910,000 copies of voice recognition softwareInstalled 42 healthcare facilitiesSoftware tutorial and face-to-face training offeredChampions trainedAccuracy rated 90% by all participantsNot used with patient in exam room, but used immediately after seeing patient by majority of usersHoyt, R., & Yoshihashi, A. (2010, Winter). Lessons learned from implementation of voice recognition for documentation in the military electronic health record system. Perspectives in Health Information Management, 7(Winter). Retrieved from http://www.ncbe.nlm.nih.gov/pmc/articles/PMC2805557/?tool=pubmed.

10Primary CareClinic from Wellspan Health implemented electronic health records with voice recognition includedVoice recognition treated as component of EHRUsed in exam room with patient

Baker, R.H. (2010, May). Voice recognition assists clinicians. Health Management Technology. Retrieved from http://healthmgttech.com.

11The VAEarly trial in late 1990sCost $2,000 per work stationCompare 3 word recognition systems using 12 physiciansEvaluation from scripted chartingError rate ranged from 6.6% to 14.6%Estimate current use by 7000 nurses and physicians

Devine, E.G., Gaehde, S.A., & Curtis, A.C. (2000, Sept-Oct). Comparative evaluation of three continuous speech recognition software packages in the generation of medical reports. Journal of the American Medical Informatics Association, 7(5), 462-468.

PsychiatryHealth record includes dense narrativeIn mandatory implementation, providers who do not type notes more inclined to accept voice recognitionProviders would not dictate in front of patientProviders found no perceived benefit in speech recognitionHalf of the evaluators favored the use of speech recognition

Derman, Y.D., Arenovich, T, Straus, J. (2010). Speech recognition software and electronic psychiatric progress notes: physicians ratings and preferences. BMC Medical Informatics and Decision Making, 10:44. Retrieved from http://www.biomedcentral.com/1472-6947/10/44.

IV NursesUsed at Butler Memorial Hospital, Butler, PAPilot project with 3 IV nursesLightweight headset and pocket sized wireless deviceComputer entry of IV needs sent to nurses headsetOn completion of patient care, nurse uses voice recognition system to record what was done in patients recordReceive next order over headset for next patientMcGee, Marianne Kolbasuk. (2009, September 17). Voice recognition tools make rounds at hospitals. InformationWeek Healthcare. Retrieved from http://www.informationweek.com/news/healthcare/EMR

Patient Interactive Voice Response SystemAutomated telephone calls made to patients on day following surgeryPatients respond to questions via speechSpeech recognition software updates database based on to patients responseIf response indicates follow-up telephone call by nurse, nurses will be prompted to complete contactSystem reported to be 97% accurateFoster, AJ; LaBranche, R; McKim, R; Faught, JW; Feasby, TE; Janes-Kelley, S; Shojania, KG; van Walraven, C. (2008). Automated patient assessments after outpatient surgery using an interactive voice response system. The American Journal of Managed Care, 14(7), 429-36.

Benefits of Speech RecognitionReduction of transcription expenseImproved patient careReduction in time documenting careIncrease per patient revenueAllows physician to dictate in their own wordsDoes not add recurring labor costs

Barriers to Speech RecognitionCapital cost of EHR with speech recognition Cost in time (users)Security or confidentiality issuesCosts to maintain EHRInterference with doctor-patient relationshipDifficulty with learning new technologyLack of tech supportLack of perceived benefit

Problems with Speech Recognition Accuracy rate approximating 90% requires editingUpgrade of processor speed and/or random access memory may be requiredChange in method of documenting encounter notes Not all users receiving appropriate training

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