Comparison of accuracy of prediction of postoperative mortality and morbidity between a new, parsimonious risk calculator (SURPAS) and the ACS Surgical Risk Calculator

Abstract

Background: The novel Surgical Risk Preoperative Assessment System (SURPAS) requires entry of five predictor variables (the other three variables of the eight-variable model are automatically obtained from the electronic health record or a table look-up), provides patient risk estimates compared to national averages, is integrated into the electronic health record, and provides a graphical handout of risks for patients. The accuracy of the SURPAS tool was compared to that of the American College of Surgeons Surgical Risk Calculator (ACS-SRC).

Methods: Predicted risk of postoperative mortality and morbidity was calculated using both SURPAS and ACS-SRC for 1,006 randomly selected 2007-2016 ACS National Surgical Quality Improvement Program (NSQIP) patients with known outcomes. C-indexes, Hosmer-Lemeshow graphs, and Brier scores were compared between SURPAS and ACS-SRC.

Results: ACS-SRC risk estimates for overall morbidity underestimated risk compared to observed postoperative overall morbidity, particularly for the highest risk patients. SURPAS accurately estimates morbidity risk compared to observed morbidity.

Conclusions: SURPAS risk predictions were more accurate than ACS-SRC's for overall morbidity, particularly for high risk patients.

Summary: The accuracy of the SURPAS tool was compared to that of the American College of Surgeons Surgical Risk Calculator (ACS-SRC). SURPAS risk predictions were more accurate than those of the ACS-SRC for overall morbidity, particularly for high risk patients.

Keywords: Accuracy; Comparative effectiveness; Postoperative outcomes; Risk assessment; SURPAS; Surgical risk prediction.