Capturing patient information at nursing shift changes: Methodological evaluation of speech recognition and information extraction

Hanna Suominen, Maree Johnson, Liyuan Zhou, Paula Sanchez, Raul Sirel, Jim Basilakis, Leif Hanlen, Dominique Estival, Linda Dawson, Barbara Kelly

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


Objective: We study the use of speech recognition and information extraction to generate drafts of Australian nursinghandover documents. Methods Speech recognition correctness and clinicians' preferences were evaluated using 15 recorder-microphone combinations, six documents, three speakers, Dragon Medical 11, and five survey/interview participants. Information extraction correctness evaluation used 260 documents, six-class classification for each word, two annotators, and the CRF++ conditional random field toolkit. Results A noise-cancelling lapel-microphone with a digital voice recorder gave the best correctness (79%). This microphone was also the most preferred option by all but one participant. Although the participants liked the small size of this recorder, their preference was for tablets that can also be used for document proofing and sign-off, among other tasks. Accented speech was harder to recognize than native language and a male speaker was detected better than a female speaker. Information extraction was excellent in filtering out irrelevant text (85% F1) and identifying text relevant to two classes (87% and 70% F1). Similarly to the annotators' disagreements, there was confusion between the remaining three classes, which explains the modest 62% macro-averaged F1. Discussion We present evidence for the feasibility of speech recognition and information extraction to support clinicians' in entering text and unlock its content for computerized decision-making and surveillance in healthcare. Conclusions The benefits of this automation include storing all information; making the drafts available and accessible almost instantly to everyone with authorized access; and avoiding information loss, delays, and misinterpretations inherent to using a ward clerk or transcription services.

Original languageEnglish
Pages (from-to)e48-e66
JournalJournal of the American Medical Informatics Association
Issue numbere1
Publication statusPublished - 2015


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