Franklin Dexter

The impact of service-specific staffing, case scheduling, turnovers, and first-case starts on anesthesia group and operating room productivity: a tutorial using data from an Australian hospital.

BACKGROUND:In this tutorial, we consider the impact of operating room (OR) management on anesthesia group and OR labor productivity and costs. Most of the tutorial focuses on the steps required for each facility to refine its OR allocations using its own data collected during patient care. METHODS:Data from a hospital in Australia are used throughout to illustrate the methods. OR allocation is a two-stage process. During the initial tactical stage of allocating OR time, OR capacity (“block time”) is adjusted. For operational decision-making on a shorter-term basis, the existing workload can be considered fixed. Staffing is matched to that workload based on maximizing the efficiency of use of OR time. RESULTS:Scheduling cases and making decisions on the day of surgery to increase OR efficiency are worthwhile interventions to increase anesthesia group productivity. However, by far, the most important step is the appropriate refinement of OR allocations (i.e., planning service-specific staffing) 2–3 mo before the day of surgery. CONCLUSIONS:Reducing surgical and/or turnover times and delays in first-case-of-the-day starts generally provides small reductions in OR labor costs. Results vary widely because they are highly sensitive both to the OR allocations (i.e., staffing) and to the appropriateness of those OR allocations.

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

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.

Analysis of strategies to decrease postanesthesia care unit costs

Background: The goal of this study was to identify interventions that anesthesiologists can make to decrease total costs of a postanesthesia care unit (PACU). Methods: Data were collected retrospectively from patients who underwent ambulatory surgery at our tertiary care center. Results: Supplies and medications accounted for only 2% of PACU charges. Personnel costs, which depend on the peak number of patients in the PACU, accounted for almost all PACU costs. If nausea and vomiting could have been eliminated in each patient who suffered this complication, without causing sedation, the total time to discharge for all patients would have been decreased by less than 4.8% (95% confidence interval <7.3%). Arrival rates to and times to discharge from the PACU followed triangular and log-normal distributions, respectively. Computer simulations, using published times to discharge for drugs with «faster recovery,» such as propofol, showed that the use of these drugs would only decrease PACU costs if operating rooms were consistently scheduled to run later each day. Such earlier discharge also might be beneficial if used at night, but only if the PACU could close after a single patient leaves. However, reasonably achievable decreases in the times to discharge for all patients undergoing general anesthesia are unlikely to substantively decrease PACU costs. In contrast, arranging an operating room schedule to optimize admission rates would greatly affect the number of PACU nurses needed. Conclusions: Anestheslologists have little control over PACU economics via choice of anesthetic drugs. The major determinant of PACU costs is the distribution of admissions

Analysis of Statistical Tests to Compare Visual Analog Scale Measurements among Groups

Background A common type of study performed by anesthesiologists determines the effect of an intervention on pain reported by groups of patients. The goal of this study was to evaluate the effectiveness of t, analysis of variance (ANOVA), Mann-Whitney, and Kruskal-Wallis tests to compare visual analog scale (VAS) measurements between two or among three groups of patients. These results may be particularly helpful during the design of studies that measure pain with a VAS. Methods One VAS measurement was obtained from each of 480 nulliparous women in labor who were receiving oxytocin (149), nalbuphine (159), or epidural bupivacaine (172). Multiple simulated samples were then drawn from these data. These simulated samples were used in computer simulations of clinical trials comparing VAS measurements among groups. t and ANOVA tests were performed before and after an arcsin transformation was used, to make the data closer to a normal distribution. VAS measurements were also compared after they were divided into five ranked categories. Results The statistical distributions of VAS measurements were not normal (P < 10 sup -7). Arcsin transformation made the distributions closer to normal distributions. Nevertheless, no statistical test incorrectly suggested that a difference existed among groups, when there was no difference, more often than the expected rate, t or ANOVA tests had a slightly greater statistical power than the other tests to detect differences among groups. Because arcsin transformation both decreased differences among means and reduced the variance to a lesser extent, it decreased power to detect differences among groups. Statistical power to detect differences among groups was not less for a five-category VAS than for a continuous VAS. Conclusions We conclude that t and ANOVA, without an accompanying arcsin transformation, are good tests to find differences in VAS measurements among groups.

Making management decisions on the day of surgery based on operating room efficiency and patient waiting times

The authors review the scientific literature on operating room management operational decision making on the day of surgery. (1) Some decisions should rely on the expected (mean) duration of the scheduled case. Other decisions should use upper prediction bounds, lower prediction bounds, and other measures reflecting the uncertainty of case duration estimates. One single number cannot be used for good decision making, because durations are uncertain. (2) Operational decisions can be made on the day of surgery based on four ordered priorities. (3) Decisions to reduce overutilized operating room time rely on mean durations. Limited additional data are needed to make these decisions well, specifically, whether a patient is in each operating room and which cases are about to finish. (4) Decisions involving reducing patient (and surgeon) waiting times rely on quantifying uncertainties in case durations, which are affected highly by small sample sizes. Future studies should focus on using real-time display of data to reduce patient waiting.

Decreases in anesthesia-controlled time cannot permit one additional surgical operation to be reliably scheduled during the workday.

We tested whether anesthesiologists can decrease operating room (OR) costs by working more quickly.Anesthesia-controlled time (ACT) was defined as the sum of 1) the time starting when the patient enters an OR until preparation or surgical positioning can begin plus 2) the time starting when the dressing is finished and ending when the patient leaves the OR. Case time was defined as the time starting when one patient undergoing an operation leaves an OR and ending when the next patient undergoing the same operation leaves the OR. An actual case series was constructed of 709 consecutive patients who underwent one of 11 elective operations at a tertiary care center. Statistical analysis of measured OR times showed that ACT would have to be decreased by more than 100% to permit one additional scheduled, short (30-min) operation to be performed in an OR during an 8-h workday after a prior series of cases, each lasting more than 45 min. Anesthesiologists alone cannot reasonably decrease case times sufficiently to permit one extra case to be reliably scheduled during a workday. Methods to decrease ACT (e.g., using preoperative intravenous catheter teams, procedure rooms, and/or shorter acting drugs) may simply increase costs. (Anesth Analg 1995;81:1263-8)

Development of a Measure of Patient Satisfaction with Monitored Anesthesia Care The Iowa Satisfaction with Anesthesia Scale

Background:The authors describe development of the Iowa Satisfaction with Anesthesia Scale (ISAS) for monitored anesthesia care (MAC). Patients complete the self-administered written questionnaire before discharge from the hospital. The authors designed the ISAS to measure satisfaction with MAC itse

Differential Effects of Anesthetic Agents on Outcome from Near-complete but Not Incomplete Global Ischemia in the Rat

BackgroundIt has been postulated that anesthetic agents that reduce cerebral metabolic rate will protect the brain against ischemia when electroencephalographic (EEG) activity is persistent, but will provide no protection when ischemia is severe enough to cause EEG isoelectricity. No outcome studies

Operating room managers' use of integer programming for assigning block time to surgical groups: a case study.

A common problem at hospitals with fixed amounts of available operating room (OR) time (i.e., “block time”) is determining an equitable method of distributing time to surgical groups. Typically, facilities determine a surgical group’s share of available block time using formulas based on OR utilization, contribution margin, or some other performance metric. Once each group’s share of time has been calculated, a method must be found for fitting each group’s allocated OR time into the surgical master schedule. This involves assigning specific ORs on specific days of the week to specific surgical groups, usually with the objective of ensuring that the time assigned to each group is close to its target share. Unfortunately, the target allocated to a group is rarely expressible as a multiple of whole blocks. In this paper, we describe a hospital’s experience using the mathematical technique of integer programming to solve the problem of developing a consistent schedule that minimizes the shortfall between each group’s target and actual assignment of OR time. Schedule accuracy, the sum over all surgical groups of shortfalls divided by the total time available on the schedule, was 99.7% (sd 0.1%, n = 11). Simulations show the algorithm’s accuracy can exceed 97% with ≥4 ORs. The method is a systematic and successful way to assign OR blocks to surgeons.

Hospital profitability per hour of operating room time can vary among surgeons

The operating margins (i.e., profits) of hospitals are decreasing. An important aspect of a hospital’s finances is the profitability of individual surgical cases, which is measured by contribution margin. We sought to determine the extent to which contribution margin per hour of operating room (OR) time can vary among surgeons. We retrospectively analyzed 2848 elective cases performed by 94 surgeons at the Stanford University School of Medicine. For each case, we subtracted variable costs from the total payment to the hospital to compute contribution margin. We found moderate variability in contribution margin per hour of OR time among surgeons, relative to the variability in contribution margins per OR hour among each surgeon’s cases (Cohen’s f equaled 0.29, 95% lower confidence interval bound 0.27). Contribution margin per OR hour was negative for 26% of the cases. These results have implications for hospitals for which OR utilization is extensive, and for which elective cases are only scheduled if they can be completed during regularly scheduled hours. To increase or achieve profitability, managers need to increase the hours of lucrative cases, rather than encourage surgeons to do more and more cases. Whether the variability in contribution margin among surgeons should be used to more optimally (profitably) allocate OR time depends on the scheduling objectives of the surgical suite.