Development and Validation of the Intensive Documentation Index for ICU Mortality Prediction: A Temporal Validation Study

BackgroundNursing documentation patterns may reflect patient acuity and clinical deterioration, yet their prognostic value remains underexplored. We developed the Intensive Documentation Index (IDI), a novel framework quantifying temporal documentation rhythms, and evaluated its ability to enhance ICU mortality prediction.58 MethodsWe analyzed 26,153 ICU admissions of heart failure patients from the MIMIC-IV database (2008-2019). Nine IDI features capturing documentation rhythm, volume, and surveillance gaps were extracted from electronic health record timestamps during the first 24 hours of ICU stay. We compared logistic regression models with and without IDI features using temporal validation and race-stratified analysis.2124 ResultsThe cohort had a mean age of 68.5 {+/-} 13.2 years and an in-hospital mortality rate of 15.99% (n=4,181). The baseline model (age, sex, ICU length of stay) achieved an AUC of 0.658 (95% CI 0.609-0.710). Addition of nine IDI features significantly improved discrimination to 0.683 (95% CI 0.631-0.732), an absolute increase of 0.025 (p<0.05, DeLong test). Leave-one-year-out cross-validation across 12 years yielded a mean AUC of 0.684 (SD 0.008). The coefficient of variation of inter-event intervals (idi_cv_interevent) was the strongest predictor (OR 1.53 per SD, 95% CI 1.38-1.70, p<0.001). Model performance was consistent across racial and ethnic groups (AUC range 0.673-0.691), with no evidence of systematic bias. ConclusionsDocumentation rhythm patterns, captured through the IDI framework, significantly enhance ICU mortality prediction beyond traditional clinical variables. The association between documentation irregularity and mortality may reflect nursing workload, patient acuity, or care processes warranting further investigation. IDI represents a novel, readily available prognostic signal that could inform future clinical decision support systems.25