The Influence of Decreasing Variable Collection Burden on Hospital-Level Risk-Adjustment

Analysis of 141 hospitals demonstrates that removing congenital malformation as a predictor variable from NSQIP-Ped risk-adjustment models maintains model performance while reducing data collection burden. Hospital outlier status and performance rankings remained stable, suggesting opportunities to streamline registry data collection without compromising quality benchmarking.