• Natasha E Holmes, Sobia Amjad, Marcus Young, David J Berlowitz, and Rinaldo Bellomo.
• Data Analytics Research and Evaluation Centre, University of Melbourne and Austin Hospital, Melbourne, VIC, Australia. natasha.holmes@austin.org.au.
• Crit Care Resusc. 2019 Dec 1; 21 (4): 299-302.

ObjectiveTo develop a library of delirium-suggestive words.DesignCross-sectional survey.SettingSingle tertiary referral hospital.ParticipantsMedical, nursing and allied health staff and medical coders.Main Outcome MeasuresFrequency of graded response on a 5-point Likert scale to individual delirium-suggestive words.ResultsTwo-hundred and three complete responses were received from 227 survey respondents; the majority were medical and nursing staff (42.4% and 43.8% respectively), followed by allied health practitioners and medical coders (10.3% and 3.4%). Words that were "very likely" to suggest delirium were "confused/ confusion", "delirious", "disoriented/disorientation" and "fluctuating conscious state". Differences in word selection were noted based on occupational background, prior knowledge of delirium, and experience in caring for intensive care unit patients. Distractor words included in the survey were rated as "unlikely" or "very unlikely" by respondents as expected. Textual responses identified several other descriptors of delirium-suggestive words.ConclusionA comprehensive repertoire of delirium-suggestive words was validated using a multidisciplinary survey and new words suggested by respondents were added. The use of natural language processing algorithms may allow for earlier detection of delirium using our delirium library and be deployed for real-time decision making and clinical care.

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