Document Type

Article

Publication Date

2023

Journal Title

Journal of Perianesthesia Training

Volume Number

39

Issue Number

1

First Page

116

Last Page

121

DOI

https://doi.org/10.1016/j.jopan.2023.07.011

Version

Publisher PDF: the final published version of the article, with professional formatting and typesetting

Disciplines

Nursing

Abstract

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.

Included in

Nursing Commons

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