Patient-specific Predictors of Surgical Delay in a Large Tertiary-care Hospital Operating Room

Purpose: The purpose of this study was to describe patient-specific factors predictive of surgical delay in elective surgical cases. Design: Retrospective cohort study. Methods: Data were extracted retrospectively from the electronic health record of 32,818 patients who underwent surgery at a large academic hospital in Los Angeles between May 2012 and April 2017. Following bivariate analysis of patient-specific factors and surgical delay, statistically significant predictors were entered into a logistic regression model to determine the most significant predictors of surgical delay. Findings: Predictors of delay included having monitored anesthesia care (odds ratio [OR], 1.28; 95% confidence intervals [CI], 1.20-1.36), American Society of Anesthesiologist class 3 or above (OR, 1.21; 95% CI, 1.15-1.28), African American race (OR, 1.25; 95% CI, 1.12-1.39), renal failure (OR, 1.20; 95% CI, 1.09-1.32), steroid medication (OR, 1.13; 95% CI, 1.04-1.23) and Medicaid (OR,1.18; 95%CI, 1.09-1.30) or medicare insurance (OR, 1.14; 95% CI, 1.07-1.21). Six surgical specialties also increased the odds of delay. Obesity and cardiovascular anesthesia decreased the odds of delay. Conclusions: Certain patient-specific factors including type of insurance, health status, and race were associated with surgical delay. Whereas monitored anesthesia care anesthesia was predictive of a delay, cardiovascular anesthesia reduced the odds of delay. Additionally, obese patients were less likely to experience a delay. While the electronic health record provided a large amount of detailed information, barriers existed to accessing meaningful data. (c) 2023 American Society of PeriAnesthesia Nurses. Published by Elsevier Inc. All rights reserved.