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Errors in medical records were common long before speech recognition software created themand proof-reading notes has always been essential. Unfortunately, speech recognition does not obviate that responsibility although the technology is constantly improving. Even so, in an era when patients can readily access their records, accuracy is ever more important. (Records are not tweets.)
Zhou L, Blackley SV, Kowalski L, et al. Analysis of Errors in Dictated Clinical Documents Assisted by Speech Recognition Software and Professional Transcriptionists. JAMA Netw Open. 2018;1(3):e180530. doi:https://doi.org/10.1001/jamanetworkopen.2018.0530
How accurate are dictated clinical documents created by speech recognition software, edited by professional medical transcriptionists, and reviewed and signed by physicians?
Among 217 clinical notes randomly selected from 2 health care organizations, the error rate was 7.4% in the version generated by speech recognition software, 0.4% after transcriptionist review, and 0.3% in the final version signed by physicians. Among the errors at each stage, 15.8%, 26.9%, and 25.9% involved clinical information, and 5.7%, 8.9%, and 6.4% were clinically significant, respectively.
An observed error rate of more than 7% in speech recognition–generated clinical documents demonstrates the importance of manual editing and review.
Accurate clinical documentation is critical to health care quality and safety. Dictation services supported by speech recognition (SR) technology and professional medical transcriptionists are widely used by US clinicians. However, the quality of SR-assisted documentation has not been thoroughly studied.
To identify and analyze errors at each stage of the SR-assisted dictation process.
Design, Setting, and Participants
This cross-sectional study collected a stratified random sample of 217 notes (83 office notes, 75 discharge summaries, and 59 operative notes) dictated by 144 physicians between January 1 and December 31, 2016, at 2 health care organizations using Dragon Medical 360 | eScription (Nuance). Errors were annotated in the SR engine–generated document (SR), the medical transcriptionist–edited document (MT), and the physician’s signed note (SN). Each document was compared with a criterion standard created from the original audio recordings and medical record review.
Main Outcomes and Measures
Error rate; mean errors per document; error frequency by general type (eg, deletion), semantic type (eg, medication), and clinical significance; and variations by physician characteristics, note type, and institution.
Among the 217 notes, there were 144 unique dictating physicians: 44 female (30.6%) and 10 unknown sex (6.9%). Mean (SD) physician age was 52 (12.5) years (median [range] age, 54 [28-80] years). Among 121 physicians for whom specialty information was available (84.0%), 35 specialties were represented, including 45 surgeons (37.2%), 30 internists (24.8%), and 46 others (38.0%). The error rate in SR notes was 7.4% (ie, 7.4 errors per 100 words). It decreased to 0.4% after transcriptionist review and 0.3% in SNs. Overall, 96.3% of SR notes, 58.1% of MT notes, and 42.4% of SNs contained errors. Deletions were most common (34.7%), then insertions (27.0%). Among errors at the SR, MT, and SN stages, 15.8%, 26.9%, and 25.9%, respectively, involved clinical information, and 5.7%, 8.9%, and 6.4%, respectively, were clinically significant. Discharge summaries had higher mean SR error rates than other types (8.9% vs 6.6%; difference, 2.3%; 95% CI, 1.0%-3.6%; P < .001). Surgeons’ SR notes had lower mean error rates than other physicians’ (6.0% vs 8.1%; difference, 2.2%; 95% CI, 0.8%-3.5%; P = .002). One institution had a higher mean SR error rate (7.6% vs 6.6%; difference, 1.0%; 95% CI, −0.2% to 2.8%; P = .10) but lower mean MT and SN error rates (0.3% vs 0.7%; difference, −0.3%; 95% CI, −0.63% to −0.04%; P = .03 and 0.2% vs 0.6%; difference, −0.4%; 95% CI, −0.7% to −0.2%; P = .003).
Conclusions and Relevance
Seven in 100 words in SR-generated documents contain errors; many errors involve clinical information. That most errors are corrected before notes are signed demonstrates the importance of manual review, quality assurance, and auditing.
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