Estimating the duration of common elective operations: implications for operating list management

A Comparison of Surgeon Estimated Times and Actual Operative Times in Pediatric Dental Rehabilitation under General Anesthesia. A Retrospective Study

This retrospective study aimed to compare the accuracy of the pediatric dental surgeon's estimated operative times for dental rehabilitation under general anesthesia (DRGA) in pediatric patients. This study population included 674 pediatric patients who underwent DRGA at the study facility between January 2022 and December 2022, using convenience sampling to select patients who met our inclusion criteria. Data were collected from electronic medical and anesthesia records based on several factors, including patient-related factors such as age and gender, surgeon-related factors such as rank and experience, and anesthesia-related factors such as induction and recovery time (in minutes). This study highlights a significant difference between the surgeon's estimated time (SET) and actual operative time (AOT) for pediatric DRGA procedures, with a mean difference of 19.28 min (SD = 43.17, p < 0.0001), indicating a tendency for surgeons to overestimate surgery time. Surgical procedure time was the strongest predictor of this discrepancy, with an R square value of 0.427 and a significant p-value of 0.000. Experience with surgeons, anesthesia induction, and recovery time were also significant predictors. Meanwhile, age, gender, and rank of surgeons did not significantly predict the difference between SET and AOT. Therefore, the study suggests that surgeons should adjust their estimates for pediatric DRGA procedures, specifically emphasizing a more accurate estimation of surgery time, to ensure adequate resource allocation and patient outcomes.

Assessment of Operative Time for Lip and Oral Cancers: A Tool to Improve Operative Room Efficiency

Operation theatre (OT) time utilisation rates can be improved with an assessment of the procedure time that will result in effective scheduling of cases. Our study is the first of its kind to audit the amount of OT time required for a particular surgery in lip and oral cavity cancers, depending on the various components of this complex procedure. This prospective cross-sectional study, based on an operative room database of 323 OT sessions, was conducted in the Department of Surgical Oncology at a tertiary care centre on lip and oral cancer patients from January 1st, 2019 to December 31st, 2020. Various components of the surgery, like the primary site, operating surgeon, type of neck dissection, bone resection, and reconstructive procedure, were noted. The time of entry and exit of the patient from the OT was noted. Operative time and OT time utilisation rates were calculated. SPSS 21.0 statistical tool; Students 'T', ANOVA and Games-Howell tests were applied. In 323 OT sessions, while 303 surgeries were done for primary cases (93.8%), the remaining 20 cases were for recurrent cases (6.2%). Buccal mucosa and the floor of the mouth were the most and least common sites, respectively. The mean OT time was 212.42 ± 73.83 min, the maximum being the primary at alveolus. The mean OT late start time was 70.03 ± 23.41 min and the mean OT runover time was 37.62 ± 43.53 min. The mean time varied significantly with the type of neck dissection, bone resection, and reconstructive surgery done and the operating surgeon. The mean OT time was highest for free flap reconstructive surgery (328.71 ± 62.02 min), but it didn't vary with its type. Considering only the lip and oral cancer surgeries, the OT time utilisation rate was 57.1%. Assessment and quantification of the operative duration of lip and oral cancer surgeries will help in accurate prediction of surgical duration, better OT list planning, and thus improved OT time utilisation rate. Our research not only provides data on the historical mean of procedures, but it may also encourage other centres to adopt our quantitative approach to OT scheduling.

Operating room time as a limited resource: ethical considerations for allocation

Scheduling surgical procedures among operating rooms (ORs) is mistakenly regarded as merely a tedious administrative task. However, the growing demand for surgical care and finite hours in a day qualify OR time as a limited resource. Accordingly, the objective of this manuscript is to reframe the process of OR scheduling as an ethical dilemma of allocating scarce medical resources. Recommendations for ethical allocation of OR time-based on both familiar and novel ethical values-are provided for healthcare institutions and individual surgeons.

Ability of a Complexity Scoring System to Predict Veterinary Student Surgical Procedure and Clinic Duration

The Midwestern University College of Veterinary Medicine hosts student-run free clinics that offer surgical sterilization of male and female dogs and cats, with the goal of 20 surgical cases per clinic. Surgical complexity varies significantly between the surgical procedures for males (castration) and females (ovariohysterectomy) and is also influenced by weight and age for dogs. A surgical complexity scoring system was implemented to ensure the minimum number of patients while providing a diverse mix of cases. The aim of this study was to determine whether the surgical complexity scoring system accurately predicted procedure duration. Surgical records were collected between August 2016 and October 2019. Points (1-5) were assigned to each patient at the time of appointment based on species, sex, additional procedure, age and weight, and the schedule was targeted for 50 points. Each point was predicted to account for 15 minutes of surgical time. The duration for each point category was assessed via rank-sum against the predicted median. Sixteen clinics occurred during the study period, having a mean of 40.4 points and 17 patients, 29.5 (74%) of which were allocated to students. There were 264 surgeries, with 241 (91%) having complete start and end times. Surgical duration for student surgeries was not different from the estimate for each point category, with the exception of 2-points, which had a median 5.0 minutes longer than anticipated (p = .0004). The surgical complexity scoring system is an effective tool to optimize scheduling of educational spay/neuter mobile clinics.

The 'Surgical Time': a myth or reality? Surgeons' prediction of operating time and its effect on theatre scheduling

Objective In Australia, 2.7 million surgical procedures were performed in the year 2016-17. This number is ever increasing and requires effective management of operating theatre (OT) time. Preoperative prediction of theatre time is one of the main constituents of OT scheduling, and anecdotal evidence suggests that surgeons grossly underestimate predicted surgical time. The aim of this study is to assess surgeons' accuracy at predicting OT times across different specialties and effective theatre scheduling. Methods A database was created with de-identified patient information from a 3-month period (late 2016). The collected data included variables such as the predicted time, actual surgery time, and type of procedure (i.e. Emergency or Elective). These data were used to make quantifiable comparisons. Results Data were categorised into a 'Theatre list' and 'Scopes list'. This was further compared as 'Actual-Predicted' time, which ranged from an average underestimation of each procedure by 19min (Ear Nose and Throat surgeons) to an average overprediction of 13.5min (Plastic Surgery). Urgency of procedures (i.e. Emergency and Elective procedures) did not influence prediction time for the 'Theatre list', but did so for the 'Scopes list' (P<0.001). Surgeons were poor at predicting OT times for complex operations and patients with high American Society of Anaesthesiologists grades. Overall, surgeons were fairly accurate with their OT prediction times across 1450 procedures, with an average underestimation of only 2.3 min. Conclusions In terms of global performance at The Queen Elizabeth Hospital institution, surgeons are fairly accurate at predicting OT times. Surgeons' estimates should be used in planning theatre lists to avoid unnecessary over or underutilisation of resources. What is known about the topic? It is known that variables such as theatre changeover times and anaesthesia time are some of the factors that delay the scheduled start time of an OT. Furthermore, operating time depends on the personnel within the operating rooms such as the nursing staff, anaesthesiologists, team setup and day of time. Studies outside of Australia have shown that prediction models for OT times using individual characteristics and the surgeon's estimate are effective. What does this paper add? This paper advocates for surgeons' predicted OT time to be included in the process of theatre scheduling, which currently does not take place. It also provides analysis of a wide range of surgical specialties and assesses each professions' ability to accurately predict the surgical time. This study encompasses a substantial number of procedures. Moreover, it compares endoscopic procedures separately to laparoscopic/open procedures. It contributes how different variables such as the urgency of procedure (Emergency/Elective), estimated length of procedure and patient comorbidities affect the prediction of OT time. What are the implications for practitioners? This will encourage hospital administrators to use surgeons' predicted OT time in calculations for scheduling theatre lists. This will facilitate more accurate predictions of OT time and ensure that theatre lists are not over or underutilised. Moreover, surgeons will be encouraged to make OT time predictions with serious consideration, after understanding its effect on theatre scheduling and associated costs. Hence, the aim is to try to make an estimation of OT time, which is closer to the actual time required.

The Planning Fallacy in the Orthopedic Operating Room

The planning fallacy posits that humans tend to underestimate the amount of time needed to complete a project and that greater complexity results in a larger difference in that estimation. If this phenomenon is present in the orthopedic operating room, it could lead to negative impacts on patients, their families, and physicians themselves. Nine fellowship-trained orthopedic surgeons at one institution were asked to give an estimate of their operative and total room times over the course of three months. Over 759 cases, the surgeons underestimated the total room times by 17.3% (p = 0.034) but did not underestimate their operative times (p = 0.590). The surgeons improved estimation of their operative time for all cases from 13.6 to 10.9 minutes of their actual time (p = 0.031) by comparing the absolute difference for the surgeons' first 25% to the last 25% of cases. Procedures performed at the hospital underestimated operative and total room times by 8.9% and 7.4% compared to the ambulatory center, which overestimated operative times by 6.0% and underestimated total room times by 3.8% (p < 0.001). We found that the planning fallacy does exist in certain situations within the orthopedic operating room.

Rational performance metrics for operating theatres, principles of efficiency, and how to achieve it

BACKGROUND

Several performance metrics are commonly used by National Health Service (NHS) organizations to measure the efficiency and productivity of operating lists. These include: start time, utilization, cancellations, number of operations and gap time between operations. The authors describe reasons why these metrics are flawed, and use clinical evidence and mathematics to define a rational, balanced efficiency metric.

METHODS

A narrative review of literature on the efficiency and productivity of elective NHS operating lists was undertaken. The aim was to rationalize how best to define and measure the efficiency of an operating list, and describe strategies to achieve it.

RESULTS

There is now a wealth of literature on how optimally to measure the performance of elective surgical lists. Efficiency may be defined as the completion of all scheduled operations within the allocated time with no over- or under-runs.

CONCLUSION

Achieving efficiency requires appropriate scheduling using specific procedure mean (or median) times and their associated variance (standard deviation or interquartile range) to calculate the probability they can be completed on time. The case mix may be adjusted to yield better time management. This review outlines common misconceptions applied to managing scheduled operating theatre lists and the challenges of measuring unscheduled operations in emergency settings.

Evaluation of the Reasons for the Cancellation of Elective Procedures at Level 3 University Hospital on the Day of Surgery

PURPOSE

Unexpected cancellations of planned elective procedures are a global problem for hospitals, causing a waste of hospital resources and manpower, and reduces the efficiency of hospitals. In this study, we tried to identify the causes of cancellations of elective procedures, and to examine the relationship between the causes.

DESIGN

A retrospective, descriptive single-center study.

METHODS

Nine thousand five hundred sixty-six elective procedures scheduled between January 2015 and December 2015 were retrospectively examined. Reasons for cancellation, the associated surgical clinic, and the day and season of the canceled procedures were recorded.

FINDINGS

Of the total 9,566 procedures, 496 (5.2%) were canceled. Of the cancellations, 31.3% were due to patient-related reasons, 29.2% because of inadequate anesthesia preparation, and 19% because of nonavailability of operating rooms.

CONCLUSIONS

Cancellation of elective surgeries causes a waste of time and resources. Determining the reasons for cancellations to reduce cancellation rates is important for each hospital.

A Statistical Model-driven Surgical Case Scheduling System Improves Multiple Measures of Operative Suite Efficiency: Findings From a Single-center, Randomized Controlled Trial

OBJECTIVE

We sought to determine whether a data-driven scheduling approach improves Operative Suite (OS) efficiency.

BACKGROUND

Although efficient use of the OS is a critical determinant of access to health care services, OS scheduling methodologies are simplistic and do not account for all the available characteristics of individual surgical cases.

METHODS

We randomly scheduled cases in a single OS by predicting their length using either the historical mean (HM) duration of the most recent 4 years; or a regression modeling (RM) system that accounted for operative and patient characteristics. The primary endpoint was the imprecision in prediction of the end of the operative day. Secondary endpoints included measures of OS efficiency; personnel burnout captured by the Maslach Burnout Inventory; and a composite endpoint of 30-day mortality, myocardial infarction, wound infection, bleeding, amputation, or reoperation.

RESULTS

Two hundred and seven operative days were allocated to scheduling with either the RM or the HM methodology. Mean imprecision in predicting the end of the operative day was higher with the HM approach (30.8 vs 7.2 minutes, P = 0.024). RM was associated with higher throughput (379 vs 356 cases scheduled over the course of the study, P = 0.04). The composite rate of adverse 30-day events was similar (2.2% vs 3.2%, P = 0.44). The mean depersonalization score was higher (3.2 vs 2.0, P = 0.044), and mean personal accomplishment score was lower during HM weeks (37.5 vs 40.5, P = 0.028).

CONCLUSIONS

Compared to the HM scheduling approach, the proposed data-driven RM scheduling methodology improves multiple measures of OS efficiency and OS personnel satisfaction without adversely affecting clinical outcomes.

Artificial intelligence and robotics: a combination that is changing the operating room

PURPOSE

The aim of the current narrative review was to summarize the available evidence in the literature on artificial intelligence (AI) methods that have been applied during robotic surgery.

METHODS

A narrative review of the literature was performed on MEDLINE/Pubmed and Scopus database on the topics of artificial intelligence, autonomous surgery, machine learning, robotic surgery, and surgical navigation, focusing on articles published between January 2015 and June 2019. All available evidences were analyzed and summarized herein after an interactive peer-review process of the panel.

LITERATURE REVIEW

The preliminary results of the implementation of AI in clinical setting are encouraging. By providing a readout of the full telemetry and a sophisticated viewing console, robot-assisted surgery can be used to study and refine the application of AI in surgical practice. Machine learning approaches strengthen the feedback regarding surgical skills acquisition, efficiency of the surgical process, surgical guidance and prediction of postoperative outcomes. Tension-sensors on the robotic arms and the integration of augmented reality methods can help enhance the surgical experience and monitor organ movements.

CONCLUSIONS

The use of AI in robotic surgery is expected to have a significant impact on future surgical training as well as enhance the surgical experience during a procedure. Both aim to realize precision surgery and thus to increase the quality of the surgical care. Implementation of AI in master-slave robotic surgery may allow for the careful, step-by-step consideration of autonomous robotic surgery.

Patient Transportation Delays and Effects on Operation Theatres' Efficiency: A Study for Problem Analysis and Remedial Measures

Background and Aims:

Delay in patients’ transportation to the operating theater (OT) is a globally recognized phenomenon, leading to delay in the subsequent processes (anesthesia induction, surgery, and patient turnover). This observational study was conducted to evaluate the common reasons for delay in transporting patients to the neurosurgery OT complex and its consequent effects and how the elimination of these reasons by application of feasible measures can influence the after effects.

Settings and Design:

This was an anesthesiologist-based audit of transportation process of patients to the OT complex of a tertiary care teaching hospital to identify the impediments and effects of delay, suggest and implement remedial measures, and assess the outcomes.

Materials and Methods:

The movement process of successive 551 patients was studied. In the evaluation phase, common reasons for transportation delays were identified. The incidences of consequent effects such as second-case cancellations and overrunning of OTs beyond scheduled hours were noted. In the implementation phase, corrective measures were instituted and the incidences of delays and the consequent effects were again noted.

Statistical Analysis:

Statistical analysis was performed using SPSS 17.0.

Results:

In the evaluation phase (303 patients), common reasons for delays included porter-associated delays (15), unavailable lifts (7), and pediatric patients (6). The incidences of case cancellation (20) and overrunning of OTs (9) were high. In the implementation phase, after remedial measures were enforced, the incidences of delays due to porter, lifts, and pediatric patients dropped to 1, 6, and 0, respectively. Simultaneously, a decrease in second-case cancellation (2) and overrunning of OTs (7) also reduced. As an additional finding, a significant reduction in OT turnover times was also observed (16.31 ± 9.29 min vs. 11.70 ± 5.78 min).

Conclusions:

Analysis of common reasons of patient transportation delays and removal of these impediments can markedly improve the efficiency in OT functioning.

Introducing a reserve waiting list initiative for elective general surgery at a District General Hospital

Cancelled operations represent a significant burden on the National Health Service in terms of theatre efficiency, financial implications and lost training opportunities. Moreover, they carry considerable physical and psychological effects to patients and their relatives. Evidence has shown that up to 93% of cancelled operations are due to patient-related factors. An analysis at our District General Hospital revealed that approximately 18 operations are cancelled on the day of surgery each month. This equates to 27 hours of allocated operating time valued by the trust as £67 500, not being used effectively. This retrospective quality improvement report aims to reduce unused theatre time due to cancelled elective operations in general surgery theatres-thereby improving theatre efficiency and patient care. To ascertain the baseline number of cancelled operations, an initial review of theatre cases was undertaken. Further review was then completed after implementation of two improvements-a short notice surgical waiting list and fast track pre-assessment clinics. The results showed that implementation of the reserve surgical waiting list reduced unused operating time by an average of 2.25 hours per month. By further adding in the fast track preassessment clinic, these figures increased to an average of 11.5 hours over the next 3 months. This precipitated a reutilisation of otherwise wasted theatre time. Economic impact of this time amounts around £28 750 a month, after implementation of both improvements. Simple protocol changes can lead to large improvements in the efficient running of theatres. The resultant change has improved patient satisfaction, led to greater training opportunities and improved theatre efficiency. Extrapolation of our results show better usage of previously underused theatre time, to the equivalent worth of £345 000. Further implementation of these improvements in other surgical specialities and hospitals would be beneficial.

A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery

Robot-assisted surgery (RAS) requires a large capital investment by healthcare organizations. The cost of a robotic unit is fixed, so institutions must maximize use of each unit by utilizing all available operating room block time. One way to increase utilization is to accurately predict case durations. In this study, we sought to use machine learning to develop an accurate predictive model for RAS case duration. We analyzed a random sample of robotic cases at our institution from January 2014 to June 2017. We compared the machine learning models to the baseline model, which is the scheduled case duration (determined by previous case duration averages and surgeon adjustments). Specifically, we used: 1) multivariable linear regression, 2) ridge regression, 3) lasso regression, 4) random forest, 5) boosted regression tree, and 6) neural network. We found that all machine learning models decreased the average root-mean-squared error (RMSE) as compared to the baseline model. The average RMSE was lowest with the boosted regression tree (80.2 min, 95% CI 74.0-86.4), which was significantly lower than the baseline model (100.4 min, 95% CI 90.5-110.3). Using boosted regression tree, we can increase the number of accurately booked cases from 148 to 219 (34.9% to 51.7%, p < 0.001). This study shows that using various machine learning approaches can improve the accuracy of RAS case length predictions, which will increase utilization of this limited resource. Further work is needed to operationalize these findings.

Elective Case Cancellation on the Day of Surgery at a General Hospital in Sarajevo: Causes and Possible Solutions

Introduction:

Cancelling elective procedures on the day of surgery presents a constant problem in all higher-level medical facilities, and the research of causes, consequences and possible solutions is the duty of every facility in order to enhance the quality of healthcare services.

Aim:

The aim of the research was to determine the percentage and reasons for cancelling elective procedures and provide adequate measure to reduce this number in the future and to identify ways to improve the patients’ satisfaction level.

Material and Methods:

This prospective study included all patients that were scheduled for surgery from March 2016 to November 2018 in the operating rooms at our Department of Surgery, including both performed and cancelled cases. Cases by different surgical departments (general surgery, gynecology, orthopedics, urology, plastic surgery, ophthalmology and otorhinolaryngology) were all included.

Results:

Out of 8201 planned elective procedures from March 2016 to November 2018 at the General Hospital “Abdulah Nakas”, 7825 cases were performed and 376 cases (4.58%) were cancelled on the day of surgery. The most common reasons for cancelling a surgical procedure on the day of surgery were: lack of time to perform surgery (33.51%), surgery cancelled due to medical/anesthetic reasons (31.38%), surgical procedure cancelled by the surgeon on the day of surgery (11.97%).

Conclusion:

This study has shown that the percentage of elective cases cancelled on the day of surgery at our institution stands at an acceptable 4.58%. The most common reasons for case cancellation on the day of surgery were identified. The majority of reasons for cancellation were avoidable, which means that appropriate steps could contribute to lowering the percentage of cancelled elective cases and an improved quality of healthcare services.

Changing operating lists on the day of surgery: a service evaluation

This study aims to explore how often the operating list is changed on the day of surgery and the reasons why this may occur. The purpose was to analyse the wider potential impact that changing the list on the day of surgery may have on patient safety, patient satisfaction and theatre efficiency. Survey data was collected across a multi-specialty elective operating department. The findings demonstrated that a significant change in operating lists occurred in 37.3% of sessions, for a variety of potentially avoidable reasons. We concluded that improved organisation and communication before the planned session could reduce the occurrence of changes, thereby increasing patient safety, theatre efficiency and potentially reducing incidents.

[Role-specific targets and teamwork in the operating room]

BACKGROUND

The primary goal of a surgical team is the successful performance of an operation on a patien; however, this primary goal can show discrepancies from the goals of individual team members. The main causes for differences of interests can be variations in subjective preferences and organizational differences. Subjective preferences are due to the values held by those involved. These values are of an intrinsic nature and therefore difficult to change. Another reason for individual goals is that hospitals and universities are professional bureaucracies. Experts working in professional bureaucracies are known to identify themselves to a greater extent with their respective profession than with their institution; however, teams in the operating room (OR) have to work together in multidisciplinary teams. The main goal of this analysis is to document role-specific targets and motivations within teams.

METHODS

This was a case study at a university hospital with 40 operating rooms. The data collection resulted from the three pillars of the goal documentation instrument, which includes expert interviews, a utility analysis and card placement as a basis for communicative validation. The results were analyzed with a systematic method as a qualitative content analysis. The four-pillar success model, which maps aspects of a successful hospital, was used as a deductive coding scheme. The four pillars represent the level of medical quality (process, structure and outcome quality), economy and efficiency, client satisfaction (patients and referring physicians) and employee satisfaction. At a university hospital an additional focus is on research and teaching. In addition to the four pillar success model as a deductive coding scheme, an inductive coding scheme was introduced. Approximately 10% of the employees from each professional group (surgeons, anesthesiologists, OR nurses, nurse anesthetists) were interviewed resulting in 65 interviews overall. The interviews were conducted within a time span of 4 months.

RESULTS

Considering the main categories quality of medical care, economy and efficiency, patient satisfaction and employee satisfaction as well as research and teaching, surgeons thought the categories of economy and efficiency (37%) and quality of medical care (34%) to be the most important. For anesthesiologists, however, the category of employee satisfaction (38%) was most important, followed by the category of economy and efficiency (31%). For the OR nurses as well as for the nurse anesthetists the category of employee satisfaction was of highest priority (61% and 57%, respectively).

CONCLUSION

The results show that considering the main categories no dimension is equally important for the participating professional groups. This can result in goal conflicts. Additionally, the ad hoc teams make it impossible for team building to occur, making it difficult for the professional groups to adapt to each other and the individual goals. This presents a high potential for conflict. The difference in the perception of the importance of employee satisfaction is a crucial factor for emerging conflicts in the OR, as employee satisfaction correlates with productivity and patient satisfaction. Knowing and communicating the different goals is a first step for optimizing the OR management system.

Reasons for operation cancellations at a teaching hospital: prioritizing areas of improvement

Purpose

To report rates of and reasons for operation cancellation, and to prioritize areas of improvement.

Methods

Retrospective data were extracted from the monthly reports of cancelled listed operations. Data on 14 theatres were collected by the office of quality assurance at Jordan University Hospital from August 2012 to April 2016. Rates and reasons for operation cancellation were investigated. A Pareto chart was constructed to identify the reasons of highest priority.

Results

During the period of study, 6,431 cases (9.31%) were cancelled out of 69,066 listed cases. Patient no-shows accounted for 62.52% of cancellations. A Pareto analysis showed that around 80% of the known reasons for cancellation after admission were due to a lack of surgical theatre time (30%), incomplete preoperative assessment (21%), upper respiratory tract infection (19%), and high blood pressure (13%).

Conclusion

This study identified the most common reasons for operation cancellation at a teaching hospital. Potential avoidable root causes and recommended interventions were suggested accordingly. Future research, available resources, hospital policies, and strategic measures directed to tackle these reasons should take priority.

Determinants of operative time in thyroid surgery: A prospective multicenter study of 3454 thyroidectomies

Objective

To identify the determinants of operative time for thyroidectomy and quantify the relative influence of preoperative and intra-operative factors.

Background

Anticipation of operative time is key to avoid both waste of hospital resources and dissatisfaction of the surgical staff. Having an accurate and anticipated planning would allow a rationalized operating room use and may improve patient flow and staffing level.

Methods

We conducted a prospective, cross-sectional study between April 2008 and December 2009. The operative time of 3454 patients who underwent thyroidectomy performed by 28 surgeons in five academic hospitals was monitored. We used multilevel linear regression to model determinants of operative time while accounting for the interplay of characteristics specific to surgeons, patients, and surgical procedures. The relative impact of each variable on operative time was estimated.

Results

Overall, 86% (99% CI 83 to 89) of operative time variation was related to preoperative variables. Surgeon characteristics accounted for 32% (99% CI 29 to 35) of variation, center location for 29% (99% CI 25 to 33), and surgical procedure or patient variables for 24% (99% CI 20 to 27). Operative time was significantly lower among experienced surgeons having practiced from 5–19 years (-21.8 min, P<0.05), performing at least 300 thyroidectomies per year (-28.8 min, P<0.05), and with increasing number of thyroidectomies performed the same day (-11.7min, P<0.001). Conversely, operative time increased in cases of procedure supervision by a more experienced surgeon (+20.0 min, P<0.001). The remaining 13.0% of variability was attributable to unanticipated technical difficulties at the time of surgery.

Conclusions

Variation in thyroidectomy duration is largely explained by preoperative factors, suggesting that it can be accurately anticipated. Prediction tools allowing better regulation of patient flow in operating rooms appears feasible for both working conditions and cost management.

Causes of cancellations on the day of surgery at a Tertiary Teaching Hospital

Background

Cancellation of elective scheduled operations on the day of surgery leads to an inefficient use of operating room (OR) time and a waste of resources. It also causes inconvenience for patients and families. Moreover, day of surgery (DOS) cancellation creates logistic and financial burden associated with extended hospital stay and repetitions of pre-operative preparations as well as opportunity costs of lost time and missed income. The objective of this study is to establish the rate of elective surgical cases cancellations on the day of surgery and the reasons for these cancellations stratified by avoidable versus unavoidable within a tertiary care teaching hospital in Beirut, Lebanon as well as recommend appropriate solutions.

Method

This is a prospective audit of the operation theatre list over a period of eight months (January 1, 2013-August 30, 2013). All patients scheduled to undergo elective surgeries at the hospital from January-August 2013 were included. An assigned OR staff recorded the cancelled cases in real time. The assigned staff confirmed the cancellation reason and added additional explanation if necessary by calling patients or through direct inquiry of clerical and/or clinical staff the following day. A Pareto chart was constructed to prioritize the reasons that accounted for 80 % of the avoidable surgical cancellations.

Results

For the given study period, 5929 elective surgeries were performed, of which 261 cases (4.4 %) were cancelled on the day of surgery. 187 cases (or 71.6 %) were judged as potentially avoidable cancellations versus 74 (28.4 %) that were judged as unavoidable. Of the 187 potentially avoidable cancellations, lack of financial clearance, incomplete medical evaluation, patient not showing up for surgery, and OR behind schedule accounted for almost 80 % of the causes.

Conclusion

This study showed that the majority of cancellations were deemed avoidable and hospital related. A day of surgery cancellation rate less than 2 % is attainable. Determining the major avoidable contributors to DOS cancellations is an essential first step to developing appropriate interventions to improve operating theater efficiency. Recommended interventions were presented accordingly.

Design of an improved surgical instrument for the removal of bladder tumours

The aim of this work was to design an add-on instrument that could potentially decrease the recurrence of non-muscle invasive bladder cancer. The current surgical approach permits spilled tumour cells to disseminate within the bladder, re-implant and cause tumour recurrence. An add-on instrument has been designed in the form of an opening cone intended to provide space for surgery and yet reduce tumour cell spillage and dissemination. A prototype was manufactured using the shape memory metal Nitinol which was activated using an electrical current to facilitate opening and supplemented with latex to provide a sealed environment. The prototype was tested in comparable surgical conditions utilising porcine bladder wall and blue dye to simulate tumour cells. It was demonstrated that the vast majority of dye was retained within the device, supporting the proposed aim.

Overutilization and underutilization of operating rooms - insights from behavioral health care operations management

The planning of surgery durations is crucial for efficient usage of operating theaters. Both planning too long and too short durations for surgeries lead to undesirable consequences, e.g. idle time, overtime, or rescheduling of surgeries. We define these consequences as operating room inefficiency. The overall objective of planning surgery durations is to minimize expected operating room inefficiency, since surgery durations are stochastic. While most health care studies assume economically rational behavior of decision makers, experimental studies have shown that decision makers often do not act according to economic incentives. Based on insights from health care operations management, medical decision making, behavioral operations management, as well as empirical observations, we derive hypotheses that surgeons' behavior deviates from economically rational behavior. To investigate this, we undertake an experimental study where experienced surgeons are asked to plan surgeries with uncertain durations. We discover systematic deviations from optimal decision making and offer behavioral explanations for the observed biases. Our research provides new insights to tackle a major problem in hospitals, i.e. low operating room utilization going along with staff overtime.

The effect of obesity on theatre utilisation time during primary hip and knee replacements

Introduction :

The aim of this study is to assess the effect of body mass index (BMI) and body weight on theatre utilisation time during primary total hip (THR) and knee replacements (TKR).

Methods :

A total of 1859 cases were included (820 THR and 1039 TKR). Patients were divided into groups based on BMI and body weight. The time interval from ‘starting anaesthesia’ to ‘transfer back to recovery’ was used as total theatre time. Hierarchal regression analysis was then used to study the effect of BMI and body weight while controlling the effect of any confounding variables.

Results :

In THR cases, the median theatre time was significantly different between BMI and body weight subgroups (p=0.001). In TKR cases, the median theatre time was more significantly different between weight subgroups (p<0.001) than BMI subgroups (p=0.021). Regression analysis showed that only weight remained a significant predictor (p=0.018) of theatre time in THR cases after controlling for other variables. In TKR cases, body weight and BMI were not predictors of theatre time after controlling for other variables.

Conclusion :

Body weight is a significant predictor of theatre time during THR. Neither weight nor BMI predicted theatre time during TKR.

The accuracy of surgeons' provided estimates for the duration of hysterectomies: a pilot study

STUDY OBJECTIVE

To determine the accuracy of gynecologic surgeons' estimate of operative times for hysterectomies and to compare these with the existing computer-generated estimate at our institution.

DESIGN

Pilot prospective cohort study (Canadian Task Force classification II-2).

SETTING

Academic tertiary women's hospital in the Northeast United States.

PARTICIPANTS

Thirty gynecologic surgeons including 23 general gynecologists, 4 gynecologic oncologists, and 3 urogynecologists.

INTERVENTION

Via a 6-question survey, surgeons were asked to predict the operative time for a hysterectomy they were about to perform. The surgeons' predictions were then compared with the time predicted by the scheduling system at our institution and with the actual operative time, to determine accuracy and differences between actual and predicted times. Patient and surgery data were collected to perform a secondary analysis to determine factors that may have significantly affected the prediction.

MEASUREMENTS AND MAIN RESULTS

Of 75 hysterectomies analyzed, 36 were performed abdominally, 18 vaginally, and 21 laparoscopically. Accuracy was established if the actual procedure time was within the 15-minute increment predicted by either the surgeons or the scheduling system. The surgeons accurately predicted the duration of 20 hysterectomies (26.7%), whereas the accuracy of the scheduling system was only 9.3%. The scheduling system accuracy was significantly less precise than the surgeons, primarily due to overestimation (p = .01); operative time was overestimated on average 34 minutes. The scheduling system overestimated the time required to a greater extent than the surgeons for nearly all data examined, including patient body mass index, surgical approach, indication for surgery, surgeon experience, uterine size, and previous abdominal surgery.

CONCLUSION

Although surgeons' accuracy in predicting operative time was poor, it was significantly better than that of the computerized scheduling system, which was more likely to overestimate operative time.

How often does the operating list follow the planned order? An analysis of elective maxillofacial operating lists

OBJECTIVES

The authors explored consistency of the observed running order in operating sequence compared with prior scheduled listing. We analysed potential variables felt to be predictive in the chances of a patient having their procedure as previously scheduled.

METHODS

Data were retrospectively collected for a consecutive group of patients who underwent elective maxillofacial procedures over a four week period. The consistency of scheduled and observed running order was documented. We considered four independent variables (original list position, day of week, morning or afternoon list, seniority of surgeon) and analysed their relationship to the probability of a patient undergoing their operation as per listing. Logistic regression analysis was used to determine significant associations between predictor variables with an altered list order.

RESULTS

Data were available for 35 lists (n = 133). 49% of lists were found to run according to prior given order, the remainder subject to some alteration. Logistic regression analysis showed a statistically significant association between original scheduled position and day of week, with list position consistency. Patients listed first were twelve times more likely to have their operation as listed compared to those placed fourth (OR 12.7, 95% CI 3.7-43, p < 0.05). Operating lists at the start of a week were subject to less alteration (p < 0.05). There was no demonstrated relationship between the grade of surgeon operating and alteration in operating sequence.

CONCLUSION

Approximately half of lists showed some alteration to the previously printed order. It appears that being first on an elective list offers the greatest guarantee that a patient will have their operation as per prior schedule. It may be reasonable for clinicians to be mindful of potential operating list alterations when preparing their patients for elective surgery.

An audit of operating room time utilization in a teaching hospital: is there a place for improvement?

Aim. To perform a thorough and step-by-step assessment of operating room (OR) time utilization, with a view to assess the efficacy of our practice and to identify areas of further improvement. Materials and Methods. We retrospectively analyzed the most ordinary general surgery procedures, in terms of five intervals of OR time utilization: anaesthesia induction, surgery preparation, duration of operation, recovery from anaesthesia, and transfer to postanaesthesia care unit (PACU) or intensive care unit (ICU). According to their surgical impact, the procedures were defined as minor, moderate, and major. Results. A total of 548 operations were analyzed. The mean (SD) time in minutes for anaesthesia induction was 19 (9), for surgery preparation 13 (8), for surgery 115 (64), for recovery from anaesthesia 12 (8), and for transfer to PACU/ICU 12 (9). The time spent in each step presented an ascending escalation pattern proportional to the surgical impact (P = 0.000), which was less pronounced in the transfer to PACU/ICU (P = 0.006). Conclusions. Albeit, our study was conducted in a teaching hospital, the recorded time estimates ranged within acceptable limits. Efficient OR time usage and outliers elimination could be accomplished by a better organized transfer personnel service, greater availability of anaesthesia providers, and interdisciplinary collaboration.

The influence of anesthesia-controlled time on operating room scheduling in Dutch university medical centres

BACKGROUND

Predicting total procedure time (TPT) entails several elements subject to variability, including the two main components: surgeon-controlled time (SCT) and anesthesia-controlled time (ACT). This study explores the effect of ACT on TPT as a proportion of TPT as opposed to a fixed number of minutes. The goal is to enhance the prediction of TPT and improve operating room scheduling.

METHODS

Data from six university medical centres (UMCs) over seven consecutive years (2005-2011) were included, comprising 330,258 inpatient elective surgical cases. Based on the actual ACT and SCT, the revised prediction of TPT was determined as SCT × 1.33. Differences between actual and predicted total procedure times were calculated for the two methods of prediction.

RESULTS

The predictability of TPT improved when the scheduling of procedures was based on predicting ACT as a proportion of SCT.

CONCLUSIONS

Efficient operating room (OR) management demands the accurate prediction of the times needed for all components of care, including SCT and ACT, for each surgical procedure. Supported by an extensive dataset from six UMCs, we advise grossing up the SCT by 33% to account for ACT (revised prediction of TPT = SCT × 1.33), rather than employing a methodology for predicting ACT based on a fixed number of minutes. This recommendation will improve OR scheduling, which could result in reducing overutilized OR time and the number of case cancellations and could lead to more efficient use of limited OR resources.

Priority setting in neurosurgery as exemplified by an everyday challenge

BACKGROUND

The allocation of limited healthcare resources poses a constant challenge for clinicians. One everyday example is the prioritization of elective neurosurgical operating room (OR) time in circumstances where cancellations may be encountered. The bioethical framework, Accountability for Reasonableness (A4R) may inform such decisions by establishing conditions that should be met for ethically-justifiable priority setting.

OBJECTIVE

Here, we describe our experience in implementing A4R to guide decisions regarding elective OR prioritization.

METHODS

The four primary expectations of the A4R process are: (1) relevance, namely achieved by support for the process and criteria for decisions amongst all stakeholders; (2) publicity, satisfied by the effective communication of the results of the deliberation; (3) challengeability through a fair appeals process; and (4) Oversight of the process to ensure that opportunities for its improvement are available.

RESULTS

A4R may be applied to inform OR time prioritization, with benefits to patients, surgeons and the institution itself. We discuss various case-, patient-, and surgeon-related factors that may be incorporated into the decision-making process. Furthermore, we explore challenges encountered in the implementation of this process, including the need for timely neurosurgical decision-making and the presence of hospital-based power imbalances.

CONCLUSION

The authors recommend the implementation of a fair, deliberative process to inform priority setting in neurosurgery, as demonstrated by the application of the A4R framework to allocate limited OR time.

Accuracy of predicting the duration of a surgical operation

PURPOSE

The ability to predict how long a particular operation will take is important for maintaining operating room efficiency. The purpose of this study was to determine how accurate oral and maxillofacial surgeons (OMSs) can be in making this determination.

MATERIALS AND METHODS

Three experienced OMSs predicted their operating times for various operations; these predictions were compared with the actual times. The cases were then grouped into those with accurate predictions and those with overestimated and underestimated times, and the operative reports were reviewed for possible operation trends or other contributing factors.

RESULTS

In the 100 cases analyzed, the surgeons correctly estimated operating times 26% of the time, overestimated 42% of the time, and underestimated 32% of the time. In the 42 overestimated times, 10 cases involved multiple tooth extractions or removal of impacted third molars, and 8 cases involved orthognathic surgery. In the 32 underestimated cases, 7 involved orthognathic surgery and 8 involved the open reduction of fractures. The 26 accurately estimated cases involved 7 cases of multiple tooth extractions or impacted third molar removal and 5 cases of arthroscopic temporomandibular joint lysis and lavage.

CONCLUSIONS

Although operating times need to be used for scheduling purposes, they can be highly unpredictable. Surgeons need to constantly analyze their predictions for confounding factors in order to improve their accuracy.

Reasons for cancellation of operation on the day of intended surgery in a multidisciplinary 500 bedded hospital

BACKGROUND

Cancellation of operations in hospitals is a significant problem with far reaching consequences. This study was planned to evaluate reasons for cancellation of elective surgical operation on the day of surgery in a 500 bedded Government hospital.

MATERIALS AND METHODS

The medical records of all the patients, from December 2009 to November 2010, who had their operations cancelled on the day of surgery in all surgical units of the hospital, were audited prospectively. The number of operation cancelled and reasons for cancellation were documented.

RESULTS

7272 patients were scheduled for elective surgical procedures during study period; 1286 (17.6 %) of these were cancelled on the day of surgery. The highest number of cancellation occurred in the discipline of general surgery (7.1%) and the least (0.35%) occurred in Ear-Nose-Throat surgery. The most common cause of cancellation was the lack of availability of theater time 809 (63%) and patients not turning up 244 (19%) patients. 149 cancellations (11.6%) were because of medical reasons; 16 (1.2%) were cancelled by the surgeon due to a change in the surgical plan; 28 (2.1%) were cancelled as patients were not ready for surgery; and 40 (3.1%) were cancelled due to equipment failure.].

CONCLUSION

Most causes of cancellations of operations are preventable.

Sustainability of healthcare improvement: what can we learn from learning theory?

Background

Changes that improve the quality of health care should be sustained. Falling back to old, unsatisfactory ways of working is a waste of resources and can in the worst case increase resistance to later initiatives to improve care. Quality improvement relies on changing the clinical system yet factors that influence the sustainability of quality improvements are poorly understood. Theoretical frameworks can guide further research on the sustainability of quality improvements. Theories of organizational learning have contributed to a better understanding of organizational change in other contexts. To identify factors contributing to sustainability of improvements, we use learning theory to explore a case that had displayed sustained improvement.

Methods

Førde Hospital redesigned the pathway for elective surgery and achieved sustained reduction of cancellation rates. We used a qualitative case study design informed by theory to explore factors that contributed to sustain the improvements at Førde Hospital. The model Evidence in the Learning Organization describes how organizational learning contributes to change in healthcare institutions. This model constituted the framework for data collection and analysis. We interviewed a strategic sample of 20 employees. The in-depth interviews covered themes identified through our theoretical framework. Through a process of coding and condensing, we identified common themes that were interpreted in relation to our theoretical framework.

Results

Clinicians and leaders shared information about their everyday work and related this knowledge to how the entire clinical pathway could be improved. In this way they developed a revised and deeper understanding of their clinical system and its interdependencies. They became increasingly aware of how different elements needed to interact to enhance the performance and how their own efforts could contribute.

Conclusions

The improved understanding of the clinical system represented a change in mental models of employees that influenced how the organization changed its performance. By applying the framework of organizational learning, we learned that changes originating from a new mental model represent double-loop learning. In double-loop learning, deeper system properties are changed, and consequently changes are more likely to be sustained.

A retrospective observational study of patient cancellations on the day of surgery in the general surgical directorate

'On the day' cancellations carry significant consequences. This article reviews all cases that were cancelled on the day of surgery within the general surgical directorate of the Royal Hallamshire Hospital, Sheffield from 2005 - 2010. 978 cancellations were made on the day of surgery. Most significant reasons were due to patients' fitness (40%) and lack of theatre time (21%). The conclusion is drawn that 80% of cancellations are avoidable or potentially avoidable, and we suggest implementation of further strategies to reduce cancellations.

Reasons for cancellation of elective cardiac surgery at Prince Sultan Cardiac Centre, Saudi Arabia

The cancellation of surgery is a significant drain on health resources. However, a persistent problem in most hospitals is short notice cancellation of scheduled operations, even upto the day of surgery. In some cases, patients have been prepared for surgery, and the staff is assembled and expecting to operate. In UK 8% of scheduled elective operations are cancelled within 24 hours of surgery. The reasons include cancellation by the patient, cancellation for poorly optimized medical conditions, or cancellations due to poor organization. Many of these are difficult to quantify. However, one relatively easily measured factor is the possibility that some operating lists were predictably over-booked. An operating list may over-run because of delayed starts, slow turnover, unanticipated surgical/anaesthetic problems or staff shortages. Many of these are difficult to quantify.

BACKGROUND AND OBJECTIVE

Prince Sultan Cardiac center is one of the largest referral center in the Middle East and there is no published data on the reasons for cancellation of specifically cardiac procedures. However, an audit was performed to assess the reasons for the cancellation of the cases on the day of surgery in cardiac theatres. According to one of the studies published in an Australian journal the percentage of cancelled cardiothoracic cases was determined to be 15.8%.

RESULTS

Total number of cardiac surgical patients including pediatric and adult during a period from June 2008 to May 2009 were 2191. Out of those, 1681 cases were done during the study period, 510 (23.27%) cases were cancelled during the study period. The operation theatre was functional for 331 days during the study period. Cancellations done by the surgeons were 34% while the patient's related cancellations were 32%. The administrative issues contributed to 34% in overall cancellation and anaesthetist-related cancellation were 0%.

CONCLUSION

We estimated 22% of the elective operations which were cancelled on the day of surgery were potentially avoidable. There is still a need to do further research to look for the identifiable reasons and strategic measures to eliminate the reasons for cancellation on the day of surgery.

Using mean duration and variation of procedure times to plan a list of surgical operations to fit into the scheduled list time

BACKGROUND AND OBJECTIVE

It is important that a surgical list is planned to utilise as much of the scheduled time as possible while not over-running, because this can lead to cancellation of operations. We wished to assess whether, theoretically, the known duration of individual operations could be used quantitatively to predict the likely duration of the operating list.

METHODS

In a university hospital setting, we first assessed the extent to which the current ad-hoc method of operating list planning was able to match the scheduled operating list times for 153 consecutive historical lists. Using receiver operating curve analysis, we assessed the ability of an alternative method to predict operating list duration for the same operating lists. This method uses a simple formula: the sum of individual operation times and a pooled standard deviation of these times. We used the operating list duration estimated from this formula to generate a probability that the operating list would finish within its scheduled time. Finally, we applied the simple formula prospectively to 150 operating lists, 'shadowing' the current ad-hoc method, to confirm the predictive ability of the formula.

RESULTS

The ad-hoc method was very poor at planning: 50% of historical operating lists were under-booked and 37% over-booked. In contrast, the simple formula predicted the correct outcome (under-run or over-run) for 76% of these operating lists. The calculated probability that a planned series of operations will over-run or under-run was found useful in developing an algorithm to adjust the planned cases optimally. In the prospective series, 65% of operating lists were over-booked and 10% were under-booked. The formula predicted the correct outcome for 84% of operating lists.

CONCLUSION

A simple quantitative method of estimating operating list duration for a series of operations leads to an algorithm (readily created on an Excel spreadsheet, http://links.lww.com/EJA/A19) that can potentially improve operating list planning.

Cancellations of elective surgery may cause an inferior postoperative course: the ‘invisible hand’ of health-care prioritization?

Elective surgery can be cancelled when resources are overwhelmed by emergency cases. We hypothesized that such cancellations, on psychological grounds, are followed also by inferior clinical results and we conducted a retrospective survey of patients following joint replacement surgery. Sixty patients having suffered from administrative cancellation prior to their operation during an 18-month period and with six months follow-up were identified and compared with another 60 matched patients after having the same type of surgery but without prior cancellation. All patients received questionnaires on complications and on visual analogue scale (VAS) assessment on subjective wellbeing and quality of life (QoL) at follow-up. The study group reported 50 complications versus 33 for controls ( P < 0.03). A borderline significant difference was found for myocardial infarction, 4 versus 0 ( P < 0.05). There was no difference in VAS registration and QoL measurements did not quite reach statistical significance ( P = 0.06). Cancellations (postponements) of elective surgery for administrative reasons may be followed by inferior clinical results, and this merits further prospective study.

Understanding waiting lists as the matching of surgical capacity to demand: are we wasting enough surgical time?

If surgical 'capacity' always matched or exceeded 'demand' then there should be no waiting lists for surgery. However, understanding what is meant by 'demand', 'capacity' and 'matched' requires some mathematical concepts that we outline in this paper. 'Time' is the relevant measure: 'demand' for a surgical team is best understood as the total min required for the surgery booked from outpatient clinics every week; and 'capacity' is the weekly operating time available. We explain how the variation in demand (not just the mean demand) influences the analysis of optimum capacity. However, any capacity chosen in this way is associated with only a likelihood (that is, a probability rather than certainty) of absorbing the prevailing demand. A capacity that suitably absorbs the demand most of the time (for example, > 80% of weeks) will inevitably also involve considerable waste (that is, many weeks in which there is spare, unused capacity). Conversely, a level of capacity chosen to minimise wasted time will inevitably cause an increase in size of the waiting list. Thus the question of how to balance demand and capacity is intimately related to the question of how to balance utilisation and waste. These mathematical considerations enable us to consider objectively how to manage the waiting list. They also enable us critically to analyse the extent to which philosophies adopted by the National Health Service (such as 'Lean' or 'Six Sigma') will be successful in matching surgical capacity to demand.