The use of patient factors to improve the prediction of operative duration using laparoscopic cholecystectomy

Assessing the Precision of Surgery Duration Estimation: A Retrospective Study

Background and Objectives

The operating room (OR) is considered the highest source of cost and earnings. Therefore, measuring OR efficiency, which means how time and resources are allocated precisely for their intended purposes in the operating room is crucial. Both overestimation and underestimation negatively impact OR efficiency Therefore, hospitals defined metrics to Measuring OR Effeciency. Many studies have discussed OR efficiency and how surgery scheduling accuracy plays a vital role in increasing OR efficiency. This study aims to evaluate OR efficiency using surgery duration accuracy.

Methods

This retrospective, quantitative study was conducted at King Abdulaziz Medical City. We extracted data on 97,397 surgeries from 2017 to 2021 from the OR database. The accuracy of surgery duration was identified by calculating the duration of each surgery in minutes by subtracting the time of leaving the OR from the time of entering the OR. Based on the scheduled duration, the calculated durations were categorized as either underestimation or overestimation. Descriptive and bivariate analyses (Chi-square test) were performed using the Statistical Package for the Social Sciences (SPSS) software.

Results

Sixty percent out of the 97,397 surgeries performed were overestimated compared to the time scheduled by the surgeons. Patient characteristics, surgical division, and anesthesia type showed statistically significant differences (p <0.05) in their OR estimation.

Conclusion

Significant proportion of procedures have overestimated. This finding provides insight into the need for improvement.

Recommendations

It is recommended to enhance the surgical scheduling method using machine learning (ML) models to include patient characteristics, department, anesthesia type, and even the performing surgeon increases the accuracy of duration estimation. Then, evaluate the performance of an ML model in future studies.

External Validation of Two Scoring Tools to Predict the Operative Duration and Open Conversion of Elective Laparoscopic Cholecystectomy in a Mexican Population

INTRODUCTION

This study aimed to evaluate the use of laparoscopic cholecystectomy (LC) operative time (CholeS score) and conversion to an open procedure (CLOC score) outside their validation dataset in Mexican population.

METHODS

Patients >18 years who underwent elective LC were analyzed in a single-center retrospective chart review study. Association between scores (CholeS and CLOC) with operative time and conversion to open procedures was assessed with Spearman correlation. The predictive accuracy of the CholeS score and CLOC score was evaluated by receiver operator characteristic.

RESULTS

200 patients were included in the study (33 excluded for emergency case or missing data). Spearman coefficient correlations between CholeS or CLOC score and operative time were 0.456 (p < 0.0001) and 0.356 (p < 0.0001), respectively. Area under the curve (AUC) for operative prediction time (>90 min) by CholeS score was 0.786 with a 3.5-point cutoff (80% sensitivity and 63.2% specificity). AUC for open conversion (CLOC score) was 0.78 with a 5-point cutoff (60% sensitivity and 91% specificity). The CLOC score had a 0.740 AUC (64% sensitivity and 72.8% specificity) for operative time >90 min.

CONCLUSIONS

The CholeS and the CLOC scores predicted LC long operative time and risk for conversion to an open procedure, respectively, outside their original validation set.

Artificial intelligence prediction of cholecystectomy operative course from automated identification of gallbladder inflammation

BACKGROUND

Operative courses of laparoscopic cholecystectomies vary widely due to differing pathologies. Efforts to assess intra-operative difficulty include the Parkland grading scale (PGS), which scores inflammation from the initial view of the gallbladder on a 1-5 scale. We investigated the impact of PGS on intra-operative outcomes, including laparoscopic duration, attainment of the critical view of safety (CVS), and gallbladder injury. We additionally trained an artificial intelligence (AI) model to identify PGS.

METHODS

One surgeon labeled surgical phases, PGS, CVS attainment, and gallbladder injury in 200 cholecystectomy videos. We used multilevel Bayesian regression models to analyze the PGS's effect on intra-operative outcomes. We trained AI models to identify PGS from an initial view of the gallbladder and compared model performance to annotations by a second surgeon.

RESULTS

Slightly inflamed gallbladders (PGS-2) minimally increased duration, adding 2.7 [95% compatibility interval (CI) 0.3-7.0] minutes to an operation. This contrasted with maximally inflamed gallbladders (PGS-5), where on average 16.9 (95% CI 4.4-33.9) minutes were added, with 31.3 (95% CI 8.0-67.5) minutes added for the most affected surgeon. Inadvertent gallbladder injury occurred in 25% of cases, with a minimal increase in gallbladder injury observed with added inflammation. However, up to a 28% (95% CI - 2, 63) increase in probability of a gallbladder hole during PGS-5 cases was observed for some surgeons. Inflammation had no substantial effect on whether or not a surgeon attained the CVS. An AI model could reliably (Krippendorff's α = 0.71, 95% CI 0.65-0.77) quantify inflammation when compared to a second surgeon (α = 0.82, 95% CI 0.75-0.87).

CONCLUSIONS

An AI model can identify the degree of gallbladder inflammation, which is predictive of cholecystectomy intra-operative course. This automated assessment could be useful for operating room workflow optimization and for targeted per-surgeon and per-resident feedback to accelerate acquisition of operative skills.

Estimation of Surgery Durations Using Machine Learning Methods-A Cross-Country Multi-Site Collaborative Study

The scheduling of operating room (OR) slots requires the accurate prediction of surgery duration. We evaluated the performance of existing Moving Average (MA) based estimates with novel machine learning (ML)-based models of surgery durations across two sites in the US and Singapore. We used the Duke Protected Analytics Computing Environment (PACE) to facilitate data-sharing and big data analytics across the US and Singapore. Data from all colorectal surgery patients between 1 January 2012 and 31 December 2017 in Singapore and, 1 January 2015 to 31 December 2019 in the US were used, and 7585 cases and 3597 single and multiple procedure cases from Singapore and US were included. The ML models were based on categorical gradient boosting (CatBoost) models trained on common data fields shared by both institutions. The procedure codes were based on the Table of Surgical Procedure (TOSP) (Singapore) and the Current Procedural Terminology (CPT) codes (US). The two types of codes were mapped by surgical experts. The CPT codes were then transformed into the relative value unit (RVU). The ML models outperformed the baseline MA models. The MA, scheduled durations and procedure codes were found to have higher loadings as compared to surgeon factors. We further demonstrated the use of the Duke PACE in facilitating data-sharing and big data analytics.

Attending Surgeon Influences Operative Time More Than Resident Level in Laparoscopic Cholecystectomy

BACKGROUND

Prior studies on laparoscopic cholecystectomy (LC) have concluded that resident involvement lengthens operative time without impacting outcomes. However, the lack of effect of resident level on operative duration has not been explained. We hypothesized that attending-specific influence on average operative time for LC is more pronounced than resident post-graduate year level.

MATERIALS AND METHODS

We retrospectively analyzed all LC cases performed on patients 18 y and older between November 2018 and March 2020 at 2 academic medical center-affiliated hospitals. Regression models were used to compare operative times, conversion to open rates, and complication rates by attending surgeon and resident level.

RESULTS

Nine hundred twenty-five LCs were performed over the study period, 862 (93.1%) with resident participation. Of the 44.5% variation in operative time was explained by differences in attending surgeon, as compared to 11.0% attributable to differences in resident level (P < 0.0001). This effect persisted after adjusting for patient and disease factors (33.0% versus 7.1%, P < 0.0001). Neither attending surgeon (P = 0.80), nor the level of the involved resident (P = 0.94) demonstrated a significant effect on the conversion-to-open rate (4.9%). Similarly, neither the attending surgeon (P = 0.33), nor resident level (P = 0.81) significantly affected the complication rate (8.58%).

CONCLUSIONS

Operative time for LC is primarily determined by patient- and disease-specific factors; resident level has no effect on conversion to open or complication rates. Attending influence on operative time was more pronounced than resident level influence. These findings suggest attending surgeon-related factors are more important than resident experience in determining operative duration for LC.

Statistical models to preoperatively predict operative difficulty in laparoscopic cholecystectomy: A systematic review

BACKGROUND

Laparoscopic cholecystectomy operative difficulty is highly variable and influences outcomes. This systematic review analyzes the performance and clinical value of statistical models to preoperatively predict laparoscopic cholecystectomy operative difficulty.

METHODS

PRISMA guidelines were followed. PubMed, Embase, and the Cochrane Library were searched until June 2020. Primary studies developing or validating preoperative models predicting laparoscopic cholecystectomy operative difficulty in cohorts of >100 patients were included. Studies not reporting performance metrics or enough information for clinical implementation were excluded. Data were extracted according to CHARMS, and study quality was assessed using the PROBAST tool.

RESULTS

In total, 2,654 articles were identified, and 22 met eligibility criteria. Eighteen were model development, whereas 4 were validation studies. Eighteen studies were at high risk of bias. However, 11 studies showed low concern for applicability. Identified models predict 9 definitions of laparoscopic cholecystectomy operative difficulty, the most common being conversion to open surgery and operating time. The most validated models predict an intraoperative difficulty scale and procedures >90 minutes with an area under the curve of >0.70 and >0.76, respectively. Commonly used predictors include demographic variables such as age and gender (9/18 models) and ultrasound findings such as gallbladder wall thickness (11/18). Clinical implementation was never studied.

CONCLUSION

There is a longstanding interest in estimating laparoscopic cholecystectomy operative difficulty. Models to preoperatively predict laparoscopic cholecystectomy operative difficulty have generally good performance and seem applicable. However, an unambiguous definition of operative difficulty, validations, and clinical studies are needed to implement patients' stratification in laparoscopic cholecystectomy.

Using operative features to identify surgical complexity: a case in breast surgery practice

Increasing workload is one of the main problems that surgical practices face. This increase is not only due to the increasing demand volume but also due to increasing case complexity. This raises the question on how to measure and predict the complexity to address this issue. Predicting surgical duration is critical to parametrize surgical complexity, improve surgeon satisfaction by avoiding unexpected overtime, and improve operation room utilization. Our objective is to utilize the historical data on surgical operations to obtain complexity groups and use this groups to improve practice.Our study first leverages expert opinion on the surgical complexity to identify surgical groups. Then, we use a tree-based method on a large retrospective dataset to identify similar complexity groups by utilizing the surgical features and using surgical duration as a response variable. After obtaining the surgical groups by using two methods, we statistically compare expert-based grouping with the data-based grouping. This comparison shows that a tree-based method can provide complexity groups similar to the ones generated by an expert by using features that are available at the time of surgical listing. These results suggest that one can take advantage of available data to provide surgical duration predictions that are data-driven, evidence-based, and practically relevant.

NASA-TLX Assessment of Surgeon Workload Variation Across Specialties

OBJECTIVE

With advancements in surgical equipment and procedures, human-system interactions in operating rooms affect surgeon workload and performance. Workload was measured across surgical specialties using surveys to identify potential predictors of high workload for future performance improvement.

SUMMARY BACKGROUND DATA

Surgical instrumentation and technique advancements have implications for surgeon workload and human-systems interactions. To understand and improve the interaction of components in the work system, NASA-Task Load Index can measure workload across various fields. Baseline workload measurements provide a broad overview of the field and identify areas most in need of improvement.

METHODS

Surgeons were administered a modified NASA-Task Load Index survey (0 = low, 20 = high) following each procedure. Patient and procedural factors were retrieved retrospectively.

RESULTS

Thirty-four surgeons (41% female) completed 662 surgery surveys (M = 14.85, SD = 7.94), of which 506 (76%) have associated patient and procedural data. Mental demand (M = 7.7, SD = 5.56), physical demand (M = 7.0, SD = 5.66), and effort (M = 7.8, SD = 5.77) were the highest rated workload subscales. Surgeons reported difficulty levels higher than expected for 22% of procedures, during which workload was significantly higher (P < 0.05) and procedural durations were significantly longer (P > 0.001). Surgeons reported poorer perceived performance during cases with unexpectedly high difficulty (P < 0.001).

CONCLUSIONS

When procedural difficulty is greater than expected, there are negative implications for mental and physical demand that result in poorer perceived performance. Investigations are underway to identify patient and surgical variables associated with unexpected difficulty and high workload. Future efforts will focus on re-engineering the surgical planning process and procedural environment to optimize workload and performance for improved surgical care.

DOES MALE GENDER INCREASE THE RISK OF LAPAROSCOPIC CHOLECYSTECTOMY?

Background:

Laparoscopic cholecystectomy is the preferable treatment for chronic or acute cholecystitis. Some factors may increase the rate of laparoscopic conversion to open cholecystectomy and perioperative complications. The role of gender as a risk factor for laparoscopic cholecystectomy is controversial.

Aim:

To evaluate the role of the gender on the operative findings and outcome of laparoscopic cholecystectomy.

Method:

All patients who underwent laparoscopic cholecystectomy for chronic or acute cholecystitis were included. Demographic, clinical, laboratory, imaging exams, intraoperative and postoperative data were obtained and analyzed. The data was obtained retrospectively from electronic medical records and study protocols.

Results:

Of a total 1,645 patients who were subjected to laparoscopic cholecystectomy, 540 (32.8%) were men and 1,105 (67.2%) were women. Mean age was similar in both genders (p=0.817). Operative time has longer in the male (72.48±28.50) than in the female group (65.46±24.83, p<0.001). The rate of acute cholecystitis was higher in the male (14.3%) than in the female group (5.1%, p<0.001). There was no difference between the genders in regard to the rate of conversion (p=1.0), intraoperative complication (p=1.0), postoperative complication (p=0.571), and operative mortality (p=1.0).

Conclusion:

Male gender is not an independent risk factor for laparoscopic conversion and perioperative complications.

Correlation between port-to-target distance and procedural difficulty in single-incision laparoscopic cholecystectomy: An observational study

INTRODUCTION

Single-incision laparoscopic cholecystectomy (SILC) is more challenging than conventional (multiport) laparoscopic cholecystectomy (CLC) because of the increased likelihood of instrument collision and the limited surgical workspace. In SILC, procedural difficulties may increase when the port-to-target distance is long. We aimed to assess the correlation between port-to-target distance and procedural difficulty.

METHODS

Thirty-six consecutive patients who underwent SILC at our hospital were included in this study. The umbilicus-to-Calot's triangle distance (UCD) was measured intraoperatively. The correlations between the UCD and operative time were analyzed, and for comparison, CLC cases during the same period (n = 28) were similarly analyzed. Moreover, UCD was estimated from preoperative CT (UCD-CT), and the usefulness of UCD-CT was assessed during SILC and CLC.

RESULTS

Thirty-four patients successfully underwent SILC. There were positive correlations between the UCD and pneumoperitoneum time. Multivariate linear regression analysis, including BMI and height, which were previously reported to have a correlation with longer operative time in SILC, showed that UCD is an independent predictive factor for prolonged operative duration. However, BMI and height were not independent predictive factors. UCD and UCD-CT had a very strong positive correlation; therefore, UCD was estimated from CT. UCD-CT had a strong positive correlation with operative time in SILC, but not in CLC.

CONCLUSIONS

A longer UCD is an important predictive factor for difficult cases of SILC, but this finding is not applicable in CLC. The usefulness of UCD is specific to SILC.

Surgical team workload comparison for 4-port and single-port laparoscopic cholecystectomy procedures

Advanced minimally invasive procedures may cause postural constraints and increased workload and stress for providers. This study compared workload and stress across surgical team roles for 48 laparoscopic cholecystectomies (4-port vs single-port) using a task load index (NASA-TLX), a procedural difficulty question, and salivary stress hormones. Statistical analyses were performed based on the presence intra-cluster correlation within team roles, at α=0.05. The single-port technique resulted in an 89% increase in physical workload for the surgeon and 63% increase for the assistant (both p<0.05). The surgeon had significantly higher salivary stress hormones during single-port surgeries. The degree of procedural difficulty was positively correlated between the surgeon and most roles: resident (r=0.67), assistant (r=0.81), and technician (r=0.81). There was a statistically significant positive correlation between the surgeon and assistant for all selfreported workload measures (p<0.05). The single-port technique requires further improvement to balance surgical team workload for optimal patient safety and satisfaction.

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

BACKGROUND

The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations.

METHODS

Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves.

RESULTS

After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45-85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p < 0.001), with the proportions of operations lasting > 90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score.

CONCLUSION

The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care.

Impact of an Onsite Clinic on Utilization of Preventive Services

OBJECTIVE

To assess impact of an onsite clinic on healthcare utilization of preventive services for employees of a public university and their dependents.

METHOD

Descriptive statistics, logistic regression and classification tree techniques were used to assess health claim data to identify changes in patterns of healthcare utilization and factors impacting usage of onsite clinic.

RESULT

Utilization of preventive services significantly increased for women and men employees by 9% and 14% one year after implementation of the onsite clinic. Hourly-paid employees, employees without diabetes, employees with spouse opt out or no coverage were more likely to go to the onsite clinic.

CONCLUSION

Adapted framework for assessing performance of onsite clinics based on usage of health informatics would help to identify health utilization patterns and interaction between onsite clinic and offsite health providers.