Acute risk change (ARC) identifies outlier institutions in perioperative cardiac surgical care when the standardized mortality ratio cannot

Abstract

© 2016 The Author 2016. Background With improvements in short-term mortality after cardiac surgery, the sensitivity of the standardized mortality ratio (SMR) as a performance-monitoring tool has declined. We assessed acute risk change (ARC) as a new and potentially more sensitive metric to differentiate overall cardiac surgical unit performance. Methods Retrospective analysis of the Australian and New Zealand Society of Cardiac and Thoracic Surgeons database and Australian and New Zealand Intensive Care Society Adult Patient Database was performed. The 16 656 patients who underwent coronary artery bypass grafting or cardiac valve procedures during a 4 yr period were included. The ARC was generated using the change between preoperative and postoperative probability of death. Outlier institutions were those with higher (outside 99.8% confidence intervals) ARC or SMR on annual and 4 yr funnel plots. Outliers were grouped and compared with non-outliers for baseline characteristics, intraoperative events, and postoperative morbidity. Results No outliers were identified using SMR. Two outliers were identified using ARC. Outliers had higher rates of new renal failure (5.7 vs 4.5%, P=0.017), stroke (1.6 vs 0.9%, P=0.001), reoperation (9 vs 6.0%, P<0.001), and prolonged ventilation (15.3 vs 9.5%, P<0.001). Outliers transfused more blood products (P<0.001) and had longer cardiopulmonary bypass times (P<0.001) and less senior surgeons operating (P<0.001). Conclusions Acute risk change was able to discriminate between units where SMR could not. Outliers had more adverse events. Acute risk change can be calculated before mortality outcome and identifies outliers with lower patient numbers. This may allow early recognition and investigation of outlier units.