Natural language processing diagnosed behavioral disturbance vs confusion assessment method for the intensive care unit: prevalence, patient characteristics, overlap, and association with treatment and outcome

Purpose To compare the prevalence, characteristics, drug treatment for delirium, and outcomes of patients with Natural Language Processing (NLP) diagnosed behavioral disturbance (NLP-Dx-BD) vs Confusion Assessment Method for intensive care unit (CAM-ICU) positivity. Methods In three combined medical-surgical ICUs, we obtained data on demographics, treatment with antipsychotic medications, and outcomes. We applied NLP to caregiver progress notes to diagnose behavioral disturbance and analyzed simultaneous CAM-ICU. Results We assessed 2313 patients with a median lowest Richmond Agitation-Sedation Scale (RASS) score of − 2 (− 4.0 to − 1.0) and median highest RASS score of 1 (0 to 1). Overall, 1246 (53.9%) patients were NLP-Dx-BD positive (NLP-Dx-BD pos ) and 578 (25%) were CAM-ICU positive (CAM-ICU pos ). Among NLP-Dx-BD pos patients, 539 (43.3%) were also CAM-ICU pos . In contrast, among CAM-ICU pos patients, 539 (93.3%) were also NLP-Dx-BD pos . The use of antipsychotic medications was highest in patients in the CAM-ICU pos and NLP-Dx-BD pos group (24.3%) followed by the CAM-ICU neg and NLP-Dx-BD pos group (10.5%). In NLP-Dx-BD neg patients, antipsychotic medication use was lower at 5.1% for CAM-ICU pos and NLP-Dx-BD neg patients and 2.3% for CAM-ICU neg and NLP-Dx-BD neg patients (overall P