Deep Natural Language Processing Identifies Variation in Care Preference Documentation

Abstract

ContextDocumentation of care preferences within 48 hours of admission to an intensive care unit (ICU) is a National Quality Forum-endorsed quality metric for older adults. Care preferences are poorly captured by administrative data. ObjectivesUsing deep natural language processing, our aim was to determine the rate of care preference documentation in free-text notes and to assess associated patient factors. MethodsRetrospective review of notes by clinicians using a deep natural language processing to identify care preference documentation, including goals-of-care and treatment limitations, within 48 hours of ICU admission within five ICUs (medical, cardiac, surgery, trauma surgery, and cardiac surgery) for adults 75 years and older. Covariates included demographics, ICU type, sequential organ failure assessment score, and need for mechanical ventilation. ResultsDeep natural language processing reviewed 11,575 clinician notes for 1350 ICU admissions. Median patient age was 84.0 years (interquartile range 78.0–88.4). Overall, 64.7% had documentation of care preferences. Patients with documentation were older (85 vs. 83 years; P < 0.001) and more often female (53.8% vs. 43.4%; P < 0.001). In adjusted analysis, rates of care preference documentation were higher for older patients, females, nonelective admissions, and admissions to the medical vs. the cardiac or surgical ICUs (all P ≤ 0.01). ConclusionCare preference documentation within 48 hours was absent in more than one-third of ICU admissions among patients aged 75 years and older and was more likely to occur in medical vs. cardiac or surgical ICUs.