Influence of a surgeon's exposure to operating room turnover delays on patient outcomes

Abstract

Background: A surgeon's daily performance may be affected by operating room organizational factors, potentially impacting patient outcomes. The aim of this study was to investigate the link between a surgeon's exposure to delays in starting scheduled operations and patient outcomes.

Methods: A prospective observational study was conducted from 1 November 2020 to 31 December 2021, across 14 surgical departments in four university hospitals, covering various surgical disciplines. All elective surgeries by 45 attending surgeons were analysed, assessing delays in starting operations and inter-procedural wait times exceeding 1 or 2 h. The primary outcome was major adverse events within 30 days post-surgery. Mixed-effect logistic regression accounted for operation clustering within surgeons, estimating adjusted relative risks and outcome rate differences using marginal standardization.

Results: Among 8844 elective operations, 4.0% started more than 1 h late, associated with an increased rate of adverse events (21.6% versus 14.4%, P = 0.039). Waiting time surpassing 1 h between procedures occurred in 71.4% of operations and was also associated with a higher frequency of adverse events (13.9% versus 5.3%, P < 0.001). After adjustment, delayed operations were associated with an elevated risk of major adverse events (adjusted relative risk 1.37 (95% c.i. 1.06 to 1.85)). The standardized rate of major adverse events was 12.1%, compared with 8.9% (absolute difference of 3.3% (95% c.i. 0.6% to 5.6%)), when a surgeon experienced a delay in operating room scheduling or waiting time between two procedures exceeding 1 h, as opposed to not experiencing such delays.

Conclusion: A surgeon's exposure to delay before starting elective procedures was associated with an increased occurrence of major adverse events. Optimizing operating room turnover to prevent delayed operations and waiting time is critical for patient safety.

Fig. 1

Flow chart

Fig. 2

Adjusted risk of major adverse events associated with a surgeon’s exposure to delayed operation and waiting time Adjusted relative risks were derived from mixed logistic regression models to capture surgeon variations and obtained from marginal probabilities of events for exposed (p_{T = 1}) and non-exposed (p_{T = 0}) subjects. They were calculated as RR = p_{T = 1}/p_{T = 0}. Confidence intervals were estimated using non-parametric bootstraps based on 1000 replications, picking as endpoints the 2.5th and the 97.5th percentiles. Models were adjusted with surgeon’s age (older than 45 years versus 45 years or younger), surgeon’s professional status (associate/full-time professor versus non-professor), and preoperative risk scores calculated for each outcome and derived from risk models developed on data from these same surgeons, but during another phase of the project. These risk scores took into account the surgical specialty, the surgical procedure complexity, the ICD-10 chapter of the surgical indication, the scheduling (urgent, semi-urgent, or elective), the type of anaesthesia, the surgical approach, and patient factors (age, sex, socio-economic status (median income of the municipality of residence in quartiles and precarious situation), American Society of Anesthesiologists (ASA) grade, and the following co-morbidities: current pregnancy, obesity (body mass index (BMI) greater than or equal to 30 kg/m²), malnourishment, tobacco addiction, alcohol addiction, other addiction, open wound, surgical-site infection, sepsis, endocarditis, cancer, neoadjuvant treatment, immune deficiency, coagulopathy, anticoagulant treatment, antiaggregation treatment, blood transfusion, coma, limb paralysis, other neurological disorder, confusion, dementia, depression, cardiovascular disease, neurovascular disease, peripheral arterial disease, cardiac arrhythmia, chronic heart failure, hypertension, diabetes, dyslipidaemia, pulmonary artery systolic pressure (greater than 60 mmHg), chronic renal failure, acute renal failure, chronic respiratory failure, chronic obstructive pulmonary disease, liver disease, rheumatic pathology, and hypoparathyroidism). A detailed explanation of the construction of the risk scores is provided in Appendix S1. *Delay of a scheduled operation was measured by comparing the actual start time of the current operation (marked by the patient’s entry into the operating room) with the planned start time for that operation. †Waiting time between operations was determined by measuring the duration between the incision for the current operation and the closure time of the previous operation. Waiting time was not calculated for the first surgical procedure of the day. ICU, intensive care unit; IMCU, intermediate care unit.

Fig. 3

Difference in standardized outcome rates between exposed and non-exposed operations to delays The bar charts represent the standardized outcome rates between non-exposed and exposed operations. These standardized rates were calculated using estimated coefficients obtained from the mixed logistic regression models and a marginal standardization method to control case-mix differences between non-exposed and exposed operations. Differences above brackets indicate absolute differences in standardized rates between the groups. The population of waiting time (n = 4139) was very different from that of delayed operation (n = 8758), notably with the exclusion of highly complex operations that lasted the entire day. Therefore, event rates associated with or without long waiting times cannot be compared with those for delayed operations. *Delay of a scheduled operation was measured by comparing the actual start time of the current operation (marked by the patient’s entry into the operating room) with the planned start time for that operation. †Waiting time between operations was determined by measuring the duration between the incision for the current operation and the closure time of the previous operation. Waiting time was not calculated for the first surgical procedure of the day. ‡P < 0.050. §Since mixed logistic regression models did not converge, it was not possible to calculate standardized outcome rates and standardized differences. NA, non applicable; ICU, intensive care unit; IMCU, intermediate care unit.