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PubMed2002

How to schedule elective surgical cases into specific operating rooms to maximize the efficiency of use of operating room time.

UNLABELLED: We considered elective case scheduling at hospitals and surgical centers at which surgeons and patients choose the day of surgery, cases are not turned away, and anesthesia and nursing staffing are adjusted to maximize the efficiency of use of operating room (OR) time. We investigated scheduling a new case into an OR by using two patient-scheduling rules: Earliest Start Time or Latest Start Time. By using several scenarios, we showed that the use of Earliest Start Time is rational economically at such facilities. Specifically, it maximizes OR efficiency when a service has nearly filled its regularly scheduled hours of OR time. However, Latest Start Time will perform better at balancing workload among services' OR time. We then used historical case duration data from two facilities in computer simulations to investigate the effect of errors in predicting case durations on the performance of these two heuristics. The achievable incremental reduction in overtime by having perfect information on case duration versus using historical case durations was only a few minutes per OR. The differences between Earliest Start Time and Latest Start Time were also only a few minutes per OR. We conclude that for facilities at which the goals are, in order of importance, safety, patient and surgeon access to OR time, and then efficiency, few restrictions need to be placed on patient scheduling to achieve an efficient use of OR time. IMPLICATIONS: We showed how elective cases should be scheduled to maximize the efficiency of use of operating room time. The analysis applies to surgical suites at which surgeons and patients have access to operating room time every workday.

Ambulatory Surgical Procedures↗
PubMed1999

An operating room scheduling strategy to maximize the use of operating room block time: computer simulation of patient scheduling and survey of patients' preferences for surgical waiting time.

UNLABELLED: Determining the appropriate amount of block time to allocate to surgeons and selecting the days on which to schedule elective cases can maximize operating room (OR) use. We used computer simulation to model OR scheduling. Inputs in the computer model included different methods to determine when a patient will have surgery (on-line bin-packing algorithms), case durations, lengths of time patients wait for surgery (2 wk is the median longest length of time that the outpatients [n = 367] surveyed considered acceptable), hours of block time each day, and number of blocks each week. For block time to be allocated to maximize OR utilization, two parameters must be specified: the method used to decide on what day a patient will have surgery and the average length of time patients wait to have surgery. OR utilization depends greatly on, and increases as, the average length of time patients wait for surgery increases. IMPLICATIONS: Operating room utilization can be maximized by allocating block time for the elective cases based on expected total hours of elective cases, scheduling patients into the first available date provided open block time is available within 4 wk, and otherwise scheduling patients in "overflow" time outside of the block time.

Anesthesia↗
PubMed2003

Labor costs incurred by anesthesiology groups because of operating rooms not being allocated and cases not being scheduled to maximize operating room efficiency.

UNLABELLED: Determination of operating room (OR) block allocation and case scheduling is often not based on maximizing OR efficiency, but rather on tradition and surgeon convenience. As a result, anesthesiology groups often incur additional labor costs. When negotiating financial support, heads of anesthesiology departments are often challenged to justify the subsidy necessary to offset these additional labor costs. In this study, we describe a method for calculating a statistically sound estimate of the excess labor costs incurred by an anesthesiology group because of inefficient OR allocation and case scheduling. OR information system and anesthesia staffing data for 1 yr were obtained from two university hospitals. Optimal OR allocation for each surgical service was determined by maximizing the efficiency of use of the OR staff. Hourly costs were converted to dollar amounts by using the nationwide median compensation for academic and private-practice anesthesia providers. Differences between actual costs and the optimal OR allocation were determined. For Hospital A, estimated annual excess labor costs were $1.6 million (95% confidence interval, $1.5-$1.7 million) and $2.0 million ($1.89-$2.05 million) when academic and private-practice compensation, respectively, was calculated. For Hospital B, excess labor costs were $1.0 million ($1.08-$1.17 million) and $1.4 million ($1.32-1.43 million) for academic and private-practice compensation, respectively. This study demonstrates a methodology for an anesthesiology group to estimate its excess labor costs. The group can then use these estimates when negotiating for subsidies with its hospital, medical school, or multispecialty medical group. IMPLICATIONS: We describe a new application for a previously reported statistical method to calculate operating room (OR) allocations to maximize OR efficiency. When optimal OR allocations and case scheduling are not implemented, the resulting increase in labor costs can be used in negotiations as a statistically sound estimate for the increased labor cost to the anesthesiology department.

Anesthesiology↗
PubMed1999

Statistical method to evaluate management strategies to decrease variability in operating room utilization: application of linear statistical modeling and Monte Carlo simulation to operating room management.

BACKGROUND: Operating room (OR) managers seeking to maximize labor productivity in their OR suite may attempt to reduce day-today variability in hours of OR time for which there are staff but for which there are no cases ("underutilized time"). The authors developed a method to analyze data from surgical services information systems to evaluate which management interventions can most effectively decrease variability in underutilized time. METHODS: The method uses seven summary statistics of daily workload in a surgical suite: daily allocated hours of OR time, estimated hours of elective cases, actual hours of elective cases, estimated hours of add-on cases, actual hours of add-on cases, hours of turnover time, and hours of underutilized time. Simultaneous linear statistical equations (a structural equation model) specify the relationship among these variables. Estimated coefficients are used in Monte Carlo simulations. RESULTS: The authors applied the analysis they developed to two OR suites: a tertiary care hospital's suite and an ambulatory surgery center. At both suites, the most effective strategy to decrease variability in underutilized OR time was to choose optimally the day on which to do each elective case so as to best fill the allocated hours. Eliminating all (1) errors in predicting how long elective or add-on cases would last, (2) variability in turnover or delays between cases, or (3) day-to-day variation in hours of add-on cases would have a small effect. CONCLUSIONS: This method can be used for decision support to determine how to decrease variability in underutilized OR time.

Humans↗
PubMed2002

Uncertainty in knowing the operating rooms in which cases were performed has little effect on operating room allocations or efficiency.

UNLABELLED: At many US surgical facilities, applying the previously published method that maximizes the efficiency of use of operating room (OR) time is an effective way to optimize the allocation of OR time. Results are resistant to small errors in recorded OR times. However, at some facilities, the OR information systems data have as much as a 10% error in the correct OR where each case took place. This decreases the total OR time attributed to each service, which is the basis for the allocation method. Such errors could result in incorrect OR allocations and increased OR staffing costs. Expensive and time-consuming data-cleaning steps may be required to resolve the actual OR allocation for each case. We used 1 yr of data from a large, tertiary academic hospital to investigate, through simulation, how increasing levels of error in the correct OR affect OR efficiency and allocations. To apply noise to the data, the actual ORs were changed randomly to unique, "unknown" rooms. At a 30% error level, OR allocations decreased by 4.8%, and costs increased by 1.4% relative to knowing the actual location of every case. Only 1 of 11 surgical services had an allocation decrease at room error rates of less than 25%. We conclude that, in most circumstances, data-cleaning steps to resolve uncertainty in OR locations are not necessary to make accurate OR allocations. IMPLICATIONS: Up to a 30% uncertainty in knowing the actual operating room (OR) in which cases were performed had a minor effect on OR allocations to maximize OR efficiency and on the resulting staffing costs. Thus, facilities with this common error in their OR information systems data will generally be able to use their existing data for accurate OR allocations.

Efficiency↗
PubMed2002

Foucault could have been an operating room nurse.

BACKGROUND: Operating room nursing is an under-researched area of nursing practice. The stereotypical image of operating room nursing is one of task- and technically-orientated aspects of practice, where nurses work in a medical model and are dominated by constraints from outside their sphere of influence. This paper explores the possibility of understanding operating room nursing in a different way. AIM: Using the work of Michel Foucault to analyse the work of operating room nursing, this paper argues the relevance of the framework for a more in-depth analysis of this specialty area of practice. CONTENT: The concepts of power, discipline and subjectivity are used to demonstrate how operating room nursing is constructed as a discipline and how operating room nurses act to govern and construct the specialty. Exemplars are drawn from extensive professional experience, from guidelines of professional operating room nursing associations, as well as published texts. The focus is predominantly on the regulation of space and time to maintain the integrity of the sterile surgical field and issues of management, as well as the use of the ethical concept of the 'surgical conscience'. CONCLUSIONS: This form of analysis provides a level and depth of inquiry that has rarely been undertaken in operating room nursing. As such, it has the potential to provide a much needed, different view of operation room nursing that can only help to strengthen its professional foundations and development.

Ethics↗
PubMed1999

Which algorithm for scheduling add-on elective cases maximizes operating room utilization? Use of bin packing algorithms and fuzzy constraints in operating room management.

BACKGROUND: The algorithm to schedule add-on elective cases that maximizes operating room (OR) suite utilization is unknown. The goal of this study was to use computer simulation to evaluate 10 scheduling algorithms described in the management sciences literature to determine their relative performance at scheduling as many hours of add-on elective cases as possible into open OR time. METHODS: From a surgical services information system for two separate surgical suites, the authors collected these data: (1) hours of open OR time available for add-on cases in each OR each day and (2) duration of each add-on case. These empirical data were used in computer simulations of case scheduling to compare algorithms appropriate for "variable-sized bin packing with bounded space." "Variable size" refers to differing amounts of open time in each "bin," or OR. The end point of the simulations was OR utilization (time an OR was used divided by the time the OR was available). RESULTS: Each day there were 0.24 +/- 0.11 and 0.28 +/- 0.23 simulated cases (mean +/- SD) scheduled to each OR in each of the two surgical suites. The algorithm that maximized OR utilization, Best Fit Descending with fuzzy constraints, achieved OR utilizations 4% larger than the algorithm with poorest performance. CONCLUSIONS: We identified the algorithm for scheduling add-on elective cases that maximizes OR utilization for surgical suites that usually have zero or one add-on elective case in each OR. The ease of implementation of the algorithm, either manually or in an OR information system, needs to be studied.

Algorithms↗
PubMed1994

Fire safety in the operating room.

The operating room environment is considered a potentially significant fire hazard. The role of the anesthetist in preventing and handling fires is pivotal to patient survival. Means of preventing fires as well as extinguishing them are discussed.

Fires↗
PubMed2001

The reliability of an instrument for identifying and quantifying surgeons' teaching in the operating room.

BACKGROUND: The operating room is an important teaching venue where surgical residents develop their operative skills and clinical judgement. The purpose of this study was to establish reliability for an observation instrument designed to quantify surgeons' teaching behaviors in the operating room. METHODS: An instrument was developed to identify operating room teaching behaviors in four categories: informing, questioning, responding, and setting tone. Two trained observers coded videotaped operations. Cronbach's alpha was used to estimate the instrument's internal consistency, and criterion-related reliability was established through an interobserver agreement level (IOA). RESULTS: Results for each of the teaching behavior categories were as follows: informing (IOA = 86%, alpha = +0.978); questioning (IOA = 97%, alpha = +0.966); responding (IOA = 93%, alpha = +0.97); setting tone (IOA = 97%, alpha = +0.882). CONCLUSIONS: This instrument is reliable in identifying and quantifying surgeons' teaching behaviors in the operating room. Identifying teaching behaviors will be valuable to describing and enhancing teaching in the operating room.

Behavior↗
PubMedDate not supplied

Automated data collection and presentation in the operating room.

An 'Operating Room Data Integration System', is described which is used to collect, present and archive all important physiological parameters during open heart surgery. The system requires very little attention, and provides an easy to understand and coherent interface to the user. The system is adaptable to a large extend and thus data can be presented to the user in a manner, with which he or she is already familiar. Simple drivers can be written to enable connection of the system to almost any other piece of medical equipment, if the latter provides an analog or digital, output signal. Automatic logging of the acquired signals is then possible.

Computer Systems↗