Deep Natural Language Processing Identifies Variation in Care Preference Documentation.

CONTEXT: Documentation 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.

OBJECTIVES: Using 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.

METHODS: Retrospective 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 of age. Covariates included demographics, ICU type, sequential organ failure assessment (SOFA) score, and need for mechanical ventilation.

RESULTS: Deep natural language processing reviewed 11,575 clinician notes for 1,350 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, non-elective admissions, and admissions to the medical versus the cardiac or surgical ICUs (all P≤0.01).

CONCLUSION: Care preference documentation within 48 hours was absent in over one-third of ICU admissions among patients aged ≥75 years and was more likely to occur in medical versus cardiac or surgical ICUs.