Abstract
The integration of illness severity and organ dysfunction scores into clinical practice, including the APACHE II and SOFA scores, has been challenging due to constraints associated to manual score calculation. With electronic medical records (EMR), score calculation automation using data extraction scripts has emerged as a solution. We aimed to demonstrate that APACHE II and SOFA scores calculated with an automated EMR-based data extraction script predict important clinical endpoints. In this retrospective cohort study, every adult patient admitted to one of our three ICUs, between July 1, 2019, and December 31, 2020, were enrolled. For every patient, an automated ICU admission APACHE II score was calculated using EMR data and minimal clinician input. Fully automated daily SOFA scores were calculated for every patient. 4 794 ICU admissions met our selection criteria. Of these ICU admissions, 522 deaths were recorded (10.9% in-hospital mortality rate). The automated APACHE II was discriminant for in-hospital mortality (AU-ROC = 0.83 (95% CI 0.81-0.85)). We observed an association between the APACHE II score and ICU LOS, with a statistically significant mean increase of 1.1 days of ICU LOS (1.1 [1-1.2]; p = < .0001) for each 10 units increase in APACHE score. SOFA score curves did not discrimate significantly between survivors and non-survivors. A partially automated APACHE II score, calculated with real-world EMR data using an extraction script, is associated with in-hospital mortality risk. The automated APACHE II score could potentially constitute an acceptable surrogate of ICU acuity to be used in resource allocation and triaging, especially in time of high demand for ICU beds.