Date of Award


Degree Name

PhD Nursing

Dissertation Committee

Joseph F. Burkard, DNSc, CRNA, Chairperson; Ruth A. Bush, PhD, MPH, FAMIA; Sarah E. Giron, PhD, CRNA


surgical delay, operating room, patient-specific, acuity, disparity


The high cost of healthcare is driving the search for more efficient practice, especially in high-stakes locations like the operating room. In addition to financial losses, patients suffer physical and emotional distress, including an increased risk of morbidity or mortality when surgical cases are delayed due to inefficiency. While patient-related causes of delay have been implicated, it is unclear which specific factors are most significant. This study aimed to identify specific patient factors correlated with surgical delay and develop a predictive risk algorithm that describes the relationship between patient-specific factors and surgical delay.

A retrospective review of 36,543 patients’ charts who underwent surgery at a large academic hospital over a 5-year period was conducted. Patient-specific factors, including demographics, insurance type, proximity to the hospital, anesthesia type, American Society of Anesthesiologists (ASA) classification, system-specific comorbidities, and medication usage, were identified. Bivariate analysis using chi-square analysis was conducted to determine if any of these factors were significantly correlated with surgical delay. The significant patient-specific factors were entered into a logistic regression model.

Black race, ASA =>3, renal failure, insulin, steroid, and several surgical specialties (colorectal, gynecologic oncology, hepatobiliary, neurosurgery, ophthalmology, and plastic surgery) were associated with an increased odds of surgical delay in this sample. Obesity, general anesthesia, and cardiovascular anesthesia were associated with a decreased odds of surgical delay. The model explains approximately 3.8-5.3% of surgical delays in this sample. The overall predictive rate of the model was 57.1%. Despite previous studies attributing a significant amount of surgical delay to patient factors, reasons other than patient factors were responsible for 94-95% of surgical delay in this sample. Further research in other populations or studies using different methods such as a prospective approach are necessary to fully understand the role of patient-specific factors in surgical delay. On the other hand, the power of this study permitted the discovery of seemingly small disparities that are nonetheless clinically significant. This study demonstrates that there are certain types of patients more at risk for surgical delay and therefore a diminished access to care.

Document Type

Dissertation: Open Access