RESUMEN
OBJECTIVE: To develop an electronic health record-based risk model for perioperative medicine (POM) triage and compare this model with legacy triage practices that were based on clinician assessment. SUMMARY OF BACKGROUND DATA: POM clinicians seek to address the increasingly complex medical needs of patients prior to scheduled surgery. Identifying which patients might derive the most benefit from evaluation is challenging. METHODS: Elective surgical cases performed within a health system 2014- 2019 (N = 470,727) were used to develop a predictive score, called the Comorbidity Assessment for Surgical Triage (CAST) score, using split validation. CAST incorporates patient and surgical case characteristics to predict the risk of 30-day post-operative morbidity, defined as a composite of mortality and major NSQIP complications. Thresholds of CAST were then selected to define risk groups, which correspond with triage to POM appointments of different durations and modalities. The predictive discrimination CAST score was compared with the surgeon's assessments of patient complexity and the American Society of Anesthesiologists class. RESULTS: The CAST score demonstrated a significantly higher discrimination for predicting post-operative morbidity (area under the receiver operating characteristic curve 0.75) than the surgeon's complexity designation (0.63; P < 0.001) or the American Society of Anesthesiologists (0.65; P < 0.001) ( Fig. 1 ). Incorporating the complexity designation in the CAST model did not significantly alter the discrimination (0.75; P = 0.098). Compared with the complexity designation, classification based on CAST score groups resulted a net reclassification improvement index of 10.4% ( P < 0.001) ( Table 1 ). CONCLUSION: A parsimonious electronic health record-based predictive model demonstrates improved performance for identifying pre-surgical patients who are at risk than previously-used assessments for POM triage.