Measuring the quantitative performance of surgical operating lists: theoretical modelling of ‘productive potential’ and ‘efficiency’

The effect of overlapping surgical scheduling on operating theatre productivity: a narrative review

This article reviews the background to overlapping surgery, in which a single senior surgeon operates across two parallel operating theatres; anaesthesia is induced and surgery commenced by junior surgeons in the second operating theatre while the lead surgeon completes the operation in the first. We assess whether there is any theoretical basis to expect increased productivity in terms of number of operations completed. A review of observational studies found that while there is a perception of increased surgical output for one surgeon, there is no evidence of increased productivity compared with two surgeons working in parallel. There is potential for overlapping surgery to have some positive impact in situations where turnover times between cases are long, operations are short (<2 h) and where 'critical portions' of surgery constitute about half of the total operation time. However, any advantages must be balanced against safety, ethical and training concerns.

A graphical assessment of emergency surgical list efficiency to determine operating theatre capacity needs

BACKGROUND

Unlike elective lists, full utilisation of an emergency list is undesirable, as it could prevent patient access. Conversely, a perpetually empty emergency theatre is resource wasteful. Separately, measuring delayed access to emergency surgery from time of booking the urgent case is relevant, and could reflect either deficiencies in patient preparation or be because of an occupied (over-utilised) emergency theatre.

METHODS

We developed a graphical method recognising these two separate but linked elements of performance: (i) delayed access to surgery and (ii) operating theatre utilisation. In a plot of one against the other, data fell into one of four quadrants, with delays associated with high utilisation signifying the need for more emergency capacity. However, delays associated with low utilisation reflect process deficiencies in the emergency patient pathway. We applied this analysis to 73 consecutive lists (>300 cases) from two UK hospitals.

RESULTS

Although both hospitals experienced similar rates of delayed surgery (21.8% vs 21.0%; P=0.872), in one hospital 83% of these were associated with low emergency theatre utilisation (suggesting predominant process deficiencies), whereas in the other 73% were associated with high utilisation (suggesting capacity deficiency; P<0.0001). Increasing emergency capacity in the latter resulted in shorter delays (just 6.7% cases excessively delayed; P<0.0001 for effect of intervention).

CONCLUSIONS

This simple graphical analysis indicates whether more emergency capacity is necessary. We discuss potential applications in managing emergency surgery theatres.

Monitoring Perioperative Services Using 3D Multi-Objective Performance Frontiers

The Acute Care Surgery model has been widely adopted by hospitals across the United States, with Acute Care Surgery services managing Emergency General Surgery patients that were previously being treated by General Surgery. In this analysis, we evaluate the impact of an Acute Care Surgery service model on General Surgery at the University of Vermont Medical Center using three metrics: under-utilized time, spillover time, and a financial ratio of work Relative Value Units over clinical Full Time Equivalents. These metrics are evaluated and used to identify three-dimensional Pareto optimality of General Surgery prior to and after the October 2015 tactical allocation to the Acute Care Surgery model. Our analysis was further substantiated using a Markov Chain Monte Carlo model for Bayesian Inference. We applied multi-objective Pareto and Bayesian breakpoint analysis to three operating room metrics to assess the impact of new operating room management decisions. In the two-dimensional space of Fig. 2, panel a), the post-tactical allocation front lies closer to the origin representing more optimal solutions for productivity and under-utilized time. The post-tactical allocation front is also closer to the origin for productivity and spillover time as shown in the two-dimensional space of Fig. 2, panel b). The results of the three-dimensional multi-objective analysis of Fig. 3 illustrate that the GS post-tactical allocation Pareto-surface is contained within a much smaller volume of space than the GS pre-tactical allocation Pareto-surface. The post-tactical allocation Pareto-surface is slightly lower along the z-axis, representing lower productivity than the pre-tactical allocation surface. This methodology might contribute to the external benchmarking and monitoring of perioperative services by visualizing the operational implications following tactical decisions in operating room management.

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.

Applying Performance Frontiers in Operating Room Management: A Tutorial Using Data From an Academic Medical Center

Although the primary goal of operating room (OR) management is to minimize inefficiencies, it may be difficult for OR managers to track metrics when one extrapolates possible scenarios across every OR on a daily basis. With the ability to visualize the statistical relationships to help simplify the analysis of large datasets, a more elaborate efficiency framework can be established using Pareto optimality (or performance frontiers), a multicriteria framework that includes variables that serve as proxies for a variety of outcomes. Applied to OR management, performance frontiers allow for the evaluation of common and well-understood issues of under- and over-utilized time.

"Knife to skin" time is a poor marker of operating room utilization and efficiency in cardiac surgery

BACKGROUND

Markers of operation room (OR) efficiency in cardiac surgery are focused on "knife to skin" and "start time tardiness." These do not evaluate the middle and later parts of the cardiac surgical pathway. The purpose of this analysis was to evaluate knife to skin time as an efficiency marker in cardiac surgery.

METHODS

We looked at knife to skin time, procedure time, and transfer times in the cardiac operational pathway for their correlation with predefined indices of operational efficiency (Index of Operation Efficiency - InOE, Surgical Index of Operational Efficiency - sInOE). A regression analysis was performed to test the goodness of fit of the regression curves estimated for InOE relative to the times on the operational pathway.

RESULTS

The mean knife to skin time was 90.6 ± 13 minutes (23% of total OR time). The mean procedure time was 282 ± 123 minutes (71% of total OR time). Utilization efficiencies were highest for aortic valve replacement and coronary artery bypass grafting and least for complex aortic procedures. There were no significant procedure-specific or team-specific differences for standard procedures. Procedure times correlated the strongest with InOE (r = -0.98, p < 0.01). Compared to procedure times, knife to skin is not as strong an indicator of efficiency. A statistically significant linear dependence on InOE was observed with "procedure times" only.

CONCLUSIONS

Procedure times are a better marker of OR efficiency than knife to skin in cardiac cases. Strategies to increase OR utilization and efficiency should address procedure times in addition to knife to skin times.

[Management for the operating room]

Business companies, which in the current times also includes hospitals, must create customer benefits and as a prerequisite for this must sustainably generate profits. Management in the world of business means the formation and directing of a company or parts of a company on a permanent basis, whereby management in this context is not exercising power but function. This concept of management is exemplary developed in this article for the important services sector of the operating room (OR) and individual functions, such as resource control, capacity planning and materials administration are presented in detail. Some OR-specific management challenges are worked out. From this it becomes clear that the economic logic of the most efficient implementation possible is not a contradiction of medical ethics, enabling the most effective treatment possible for patients while safeguarding the highest possible levels of safety and quality. The article aims to build a bridge for medical specialists to the language and world of commerce, emphasizing the profession-based competence and hopefully to arouse interest to go into more detail.

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.

Is percentage theatre utilisation data an accurate predictor of cost-effectiveness and performance in urology?

Objective:

The current economic and political climate demands a focus on efficiency and productivity, whilst delivering quality, across all aspects of the National Health Service (NHS). Operative theatres act as a critical, yet costly resource. The Audit Commission employs the use of percentage theatre utilisation as a principal measure of NHS operating theatre service and efficiency performance. We analysed theatre utilisation data in a five-consultant, high turnover, urology department within a NHS University Teaching Hospital. Our aim was to examine the relationship between theatre utilisation data, cost effectiveness and income generated.

Patients and methods:

Data on the usage of a dedicated urology theatre was collected over 251 hours for a full calendar month. A total of 176 consecutive procedures were performed. Linear regression analysis was performed to assess the correlation between number of operating hours, cases per hour, utilisation percentages and income generated.

Results:

There was no correlation between percentage theatre utilisation and income ( R2=0.0191, p=0.82). No relationship was identified between percentage theatre utilisation and total number of cases performed ( R2=0.0001, p=0.99). Although there appeared to be a positive correlation between the number of cases performed and income generated, this was not statistically significant ( R2=0.725, p=0.067). Furthermore, there was no association between the number of cases performed per hour and income generated ( R2=0.3184, p=0.32).

Conclusion:

Our data identifies no correlation between percentage theatre utilisation, income generated and number of cases performed. Utilisation percentages are not a reliable performance indicator when used in isolation, and therefore should be used as part of a more global picture when assessing cost effectiveness and efficiency performance.

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.

Estimating anesthesia time using the medicare claim: a validation study

INTRODUCTION

Procedure length is a fundamental variable associated with quality of care, though seldom studied on a large scale. The authors sought to estimate procedure length through information obtained in the anesthesia claim submitted to Medicare to validate this method for future studies.

METHODS

The Obesity and Surgical Outcomes Study enlisted 47 hospitals located across New York, Texas, and Illinois to study patients undergoing hip, knee, colon, and thoracotomy procedures. A total of 15,914 charts were abstracted to determine body mass index and initial patient physiology. Included in this abstraction were induction, cut, close, and recovery room times. This chart information was merged to Medicare claims that included anesthesia Part B billing information. Correlations between chart times and claim times were analyzed, models developed, and median absolute differences in minutes calculated.

RESULTS

Of the 15,914 eligible patients, there were 14,369 for whom both chart and claim times were available for analysis. For these 14,369, the Spearman correlation between chart and claim time was 0.94 (95% CI 0.94, 0.95), and the median absolute difference between chart and claim time was only 5 min (95% CI: 5.0, 5.5). The anesthesia claim can also be used to estimate surgical procedure length, with only a modest increase in error.

CONCLUSION

The anesthesia bill found in Medicare claims provides an excellent source of information for studying surgery time on a vast scale throughout the United States. However, errors in both chart abstraction and anesthesia claims can occur. Care must be taken in the handling of outliers in these data.

Estimating the time needed for induction of anaesthesia and its importance in balancing anaesthetists' and surgeons' waiting times around the start of surgery

After the anaesthetist has induced anaesthesia, it is desirable that the surgeon is present and ready to start surgery, otherwise the team needs to wait for the surgeon. From another perspective, however, the surgeon does not necessarily wish to be present from the start of induction, since that process can take a variable time and the surgeon might be otherwise occupied in productive activity rather than waiting for the patient to be ready. Waiting times in the morning can therefore be a source of constant friction between anaesthetists and surgeons. In this prospective study we used the data from 718 first cases of the day, during a 4-week study period at two university hospitals, to develop a simple spreadsheet-based method to analyse the interaction of anaesthesia and surgical start time, anaesthesia technique and the probability of waiting time for anaesthetist or surgeon, respectively. This method can be used to determine the best surgical or anaesthesia start time for each case, so that the waiting time for anaesthetists and surgeons can be minimised.

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.