Contribution of a speech recognition system to a computerized pneumonia guideline in the emergency department

TitleContribution of a speech recognition system to a computerized pneumonia guideline in the emergency department
Publication TypeConference Proceedings
Year of Conference2000
AuthorsChapman, WW, Aronsky, D, Fiszman, M, Haug, PJ
Conference NameProceedings of the American Medical Informatics Association Symposium
Pagination131–135
KeywordsComparative Study, Computer-Assisted, Computerized, Documentation/*methods, Emergency Service, Hospital, Human, Medical Records Systems, my\_papers, Natural Language Processing, Pneumonia/*radiography/therapy, Practice Guidelines, Support, Thoracic, Time Factors, {*Decision} Making, {*Medical} Records/statistics & numerical data, {*Radiography}, {*Speech}, {NLP}, {P.H.S.}, {U.S.} Gov't
Abstract

{OBJECTIVE:} Evaluate the effect of a radiology speech recognition system on a real-time computerized guideline in the emergency department. {METHODS:} We collected all chest x-ray reports (n = 727) generated for patients in the emergency department during a six-week period. We divided the concurrently generated reports into those generated with speech recognition and those generated by traditional dictation. We compared the two sets of reports for availability during the patient's emergency department encounter and for readability. {RESULTS:} Reports generated by speech recognition were available seven times more often during the patients' encounters than reports generated by traditional dictation. Using speech recognition reduced the turnover time of reports from 12 hours 33 minutes to 2 hours 13 minutes. Readability scores were identical for both kinds of reports. {CONCLUSION:} Using speech recognition to generate chest x-ray reports reduces turnover time so reports are available while patients are in the emergency department.

URLhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11079859