Sex-Specific Differences in Endothelial Function Are Driven by Divergent Mitochondrial Ca2+ Handling.

Background Sex-specific differences in vasodilation are mediated in part by differences in cytosolic Ca2+ handling, but how variations in mitochondrial Ca2+ contributes to this effect remains unknown. Here, we investigated the extent to which mitochondrial Ca2+ entry via the MCU (mitochondrial Ca2+ uniporter) drives sex differences in vasoreactivity in resistance arteries. Methods and Results Enhanced vasodilation of mesenteric resistance arteries to acetylcholine (ACh) was reduced to larger extent in female compared with male mice in 2 genetic models of endothelial MCU ablation. Ex vivo Ca2+ imaging of mesenteric arteries with Fura-2AM confirmed higher cytosolic Ca2+ transients triggered by ACh in arteries from female mice versus male mice. MCU inhibition both strongly reduced cytosolic Ca2+ transients and blocked mitochondrial Ca2+ entry. In cultured human aortic endothelial cells, treatment with physiological concentrations of estradiol enhanced cytosolic Ca2+ transients, Ca2+ buffering capacity, and mitochondrial Ca2+ entry in response to ATP or repeat Ca2+ boluses. Further experiments to establish the mechanisms underlying these effects did not reveal significant differences in the expression of MCU subunits, at either the mRNA or protein level. However, estradiol treatment was associated with an increase in mitochondrial mass, mitochondrial fusion, and the mitochondrial membrane potential and reduced mitochondrial superoxide production. Conclusions Our data confirm that mitochondrial function in endothelial cells differs by sex, with female mice having enhanced Ca2+ uptake capacity, and that these differences are attributable to the presence of more mitochondria and a higher mitochondrial membrane potential in female mice rather than differences in composition of the MCU complex.

Benchmarking Surgeons' Gender and Year of Medical School Graduation Associated With Monthly Operative Workdays for Multispecialty Groups.

Background Female surgeons reportedly receive less surgical block time and fewer procedural referrals than male surgeons. In this study, we compared operative days between female and male surgeons throughout Florida. Our objective was to facilitate benchmarking by multispecialty groups, both the endpoint to use for statistically reliable results and expected differences. Methodology The historical cohort study included all 4,060,070 ambulatory procedural encounters and inpatient elective surgical states performed between January 2017 and December 2019 by 8,472 surgeons at 609 facilities. Surgeons' gender, year of medical school graduation, and surgical specialty were obtained from their National Provider Identifiers. Results Female surgeons operated an average of 1.0 fewer days per month than matched male surgeons (99% confidence interval 0.8 to 1.2 fewer days, P < 0.0001). The mean differences were 0.8 to 1.4 fewer days per month among each of the five quintiles of years of graduation from medical school (all P ≤ 0.0050). Results were comparable when repeated using the number of monthly cases the surgeons performed. Conclusions An average difference of ≤1.4 days per month is a conservative estimate for the current status quo of the workload difference in Florida. Suppose that a group's female surgeons average more than two fewer operative days per month than the group's male surgeons of the same specialty. Such a large average difference would call for investigation of what might reflect systematic bias. While such a difference may reflect good flexibility of the organization, it may show a lack of responsiveness (e.g., fewer referrals of procedural patients to female surgeons or bias when apportioning allocated operating room time).

Temporal Relationship Between Visual Field, Retinal and Microvascular Pathology Following 125I-Plaque Brachytherapy for Uveal Melanoma.

Purpose: To define the temporal relationship of vascular versus neuronal abnormalities in radiation retinopathy. Methods: Twenty-five patients with uveal melanoma treated with brachytherapy and sixteen controls were tested. Functional outcome measures included visual acuity and threshold perimetry (HVF 10-2), while structural outcomes included retinal thickness by OCT and vascular measures by OCT angiography and digital fundus photography. The degree of structural abnormality was determined by intereye asymmetry compared with normal subject asymmetry. Diagnostic sensitivity and specificity of each measure were determined using receiver operating characteristic curves. The relationships between the outcome measures were quantified by Spearman correlation. The effect of time from brachytherapy on visual function, retinal layer thickness, and capillary density was also determined. Results: Within the first 2 years of brachytherapy, outcome measures revealed visual field loss and microvascular abnormalities in 38% and 31% of subjects, respectively. After 2 years, they became more prevalent, increasing to 67% and 67%, respectively, as did retinal thinning (50%). Visual field loss, loss of capillary density, and inner retinal thickness were highly correlated with one another. Diagnostic sensitivity and specificity were highest for abnormalities in digital fundus photography, visual field loss within the central 10°, and decrease in vessel density. Conclusions: Using quantitative approaches, radiation microvasculopathy and visual field defects were detected earlier than loss of inner retinal structure after brachytherapy. Strong correlations eventually developed between vascular pathology, change in retinal thickness, neuronal dysfunction, and radiation dose. Radiation-induced ischemia seems to be a primary early manifestation of radiation retinopathy preceding visual loss.

Sample times for surveillance of S. aureus transmission to monitor effectiveness and provide feedback on intraoperative infection control.

BACKGROUND: Reductions in perioperative surgical site infections are obtained by a multifaceted approach including patient decolonization, vascular care, hand hygiene, and environmental cleaning. Associated surveillance of S. aureus transmission quantifies the effectiveness of these basic measures to prevent transmission of pathogenic bacteria and viruses to patients and clinicians, including Coronavirus Disease 2019 (COVID-19). To measure transmission, the observational units are pairs of successive surgical cases in the same operating room on the same day. In this prospective cohort study, we measured sampling times for inexperienced and experienced personnel. METHODS: OR PathTrac kits included 6 samples collected before the start of surgery and 7 after surgery. The time for consent also was recorded. We obtained 1677 measurements of time among 132 cases. RESULTS: Sampling times were not significantly affected by technician's experience, type of anesthetic, or patient's American Society of Anesthesiologists' Physical Status. Sampling times before the start of surgery averaged less than 5 min (3.39 min [SE 0.23], P < 0.0001). Sampling times after surgery took approximately 5 min (4.39 [SE 0.25], P = 0.015). Total sampling times averaged less than 10 min without consent (7.79 [SE 0.50], P < 0.0001), and approximately 10 min with consent (10.22 [0.56], P = 0.70). CONCLUSIONS: For routine use of monitoring S. aureus transmission, when done by personnel already present in the operating rooms of the cases, the personnel time budget can be 10 min per case.

Parametric Statistical Inference for Comparing Means and Variances.

Purpose: The purpose of this tutorial is to provide visual scientists with various approaches for comparing two or more groups of data using parametric statistical tests, which require that the distribution of data within each group is normal (Gaussian). Non-parametric tests are used for inference when the sample data are not normally distributed or the sample is too small to assess its true distribution. Methods: Methods are reviewed using retinal thickness, as measured by optical coherence tomography (OCT), as an example for comparing two or more group means. The following parametric statistical approaches are presented for different situations: two-sample t-test, Analysis of Variance (ANOVA), paired t-test, and the analysis of repeated measures data using a linear mixed-effects model approach. Results: Analyzing differences between means using various approaches is demonstrated, and follow-up procedures to analyze pairwise differences between means when there are more than two comparison groups are discussed. The assumption of equal variance between groups and methods to test for equal variances are examined. Examples of repeated measures analysis for right and left eyes on subjects, across spatial segments within the same eye (e.g. quadrants of each retina), and over time are given. Conclusions: This tutorial outlines parametric inference tests for comparing means of two or more groups and discusses how to interpret the output from statistical software packages. Critical assumptions made by the tests and ways of checking these assumptions are discussed. Efficient study designs increase the likelihood of detecting differences between groups if such differences exist. Situations commonly encountered by vision scientists involve repeated measures from the same subject over time, measurements on both right and left eyes from the same subject, and measurements from different locations within the same eye. Repeated measurements are usually correlated, and the statistical analysis needs to account for the correlation. Doing this the right way helps to ensure rigor so that the results can be repeated and validated.

Decision models for distinguishing between clinically insignificant and significant tumors in prostate cancer biopsies: an application of Bayes' Theorem to reduce costs and improve outcomes.

Prostate cancer is the second leading cause of death from cancer, behind lung cancer, for men in the U. S, with nearly 30,000 deaths per year. A key problem is the difficulty in distinguishing, after biopsy, between significant cancers that should be treated immediately and clinically insignificant tumors that should be monitored by active surveillance. Prostate cancer has been over-treated; a recent European randomized screening trial shows overtreatment rates of 40%. Overtreatment of insignificant tumors reduces quality of life, while delayed treatment of significant cancers increases the incidence of metastatic disease and death. We develop a decision analysis approach based on simulation and probability modeling. For a given prostate volume and number of biopsy needles, our rule is to treat if total length of cancer in needle cores exceeds c, the cutoff value, with active surveillance otherwise, provided pathology is favorable. We determine the optimal cutoff value, c*. There are two misclassification costs: treating a minimal tumor and not treating a small or medium tumor (large tumors were never misclassified in our simulations). Bayes' Theorem is used to predict the probabilities of minimal, small, medium, and large cancers given the total length of cancer found in biopsy cores. A 20 needle biopsy in conjunction with our new decision analysis approach significantly reduces the expected loss associated with a patient in our target population about to undergo a biopsy. Longer needles reduce expected loss. Increasing the number of biopsy cores from the current norm of 10-12 to about 20, in conjunction with our new decision model, should substantially improve the ability to distinguish minimal from significant prostate cancer by minimizing the expected loss from over-treating minimal tumors and delaying treatment of significant cancers.

Importance of operating room case scheduling on analyses of observed reductions in surgical site infections from the purchase and installation of capital equipment in operating rooms.

BACKGROUND: We review the impact of the consequences of operating room (OR) management decision making on power analyses for observational studies of surgical site infections (SSIs) among patients receiving care in ORs with interventions versus without interventions involving physical changes to ORs. Examples include ventilation systems, bactericidal lighting, and physical alterations to ORs. METHODS: We performed a narrative review of operating room management and surgical site infection articles. We used 10-years of operating room data to estimate parameters for use in statistical power analyses. RESULTS: Creating pivot tables or monthly control charts of SSI per case by OR and comparing among ORs with or without intervention is not recommended. This approach has low power to detect a difference in SSI rates among the ORs with or without the intervention. The reason is that appropriate OR case scheduling decision making causes risk factors for SSI to differ among ORs, even when stratifying by surgical specialty. Such risk factors include case duration, urgency, and American Society of Anesthesiologists' Physical Status. Instead, analyze SSI controlling for the OR, where the patient had surgery, and matching patients using these variables is preferable. With α = 0.05, 600 cases per OR, 5 intervention ORs, and 5 or 1 control patients for each intervention patient, reasonable power (≅94% or 78%, respectively) can be achieved to detect reductions (3.6% to 2.4%) in the incidence of SSI between ORs with or without the intervention. CONCLUSIONS: By using this matched cohort design, the effect of the purchase and installation of capital equipment in ORs on SSI can be evaluated meaningfully.

Peripapillary Retinal Pigment Epithelium Layer Shape Changes From Acetazolamide Treatment in the Idiopathic Intracranial Hypertension Treatment Trial.

Purpose: Recent studies indicate that the amount of deformation of the peripapillary retinal pigment epithelium and Bruch's membrane (pRPE/BM) toward or away from the vitreous may reflect acute changes in cerebrospinal fluid pressure. The study purpose is to determine if changes in optic-nerve-head (ONH) shape reflect a treatment effect (acetazolamide/placebo + weight management) using the optical coherence tomography (OCT) substudy of the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT) at baseline, 3, and 6 months. Methods: The pRPE/BM shape deformation was quantified and compared with ONH volume, peripapillary retinal nerve fiber layer (pRNFL), and total retinal (pTR) thicknesses in the acetazolamide group (39 subjects) and placebo group (31 subjects) at baseline, 3, and 6 months. Results: Mean changes of the pRPE/BM shape measure were significant and in the positive direction (away from the vitreous) for the acetazolamide group (P < 0.01), but not for the placebo group. The three OCT measures reflecting the reduction of optic disc swelling were significant in both treatment groups but greater in the acetazolamide group (P < 0.01). Conclusions: Change in the pRPE/BM shape away from the vitreous reflects the effect of acetazolamide + weight management in reducing the pressure differential between the intraocular and retrobulbar arachnoid space. Weight management alone was also associated with a decrease in optic nerve volume/edema but without a significant change in the pRPE/BM shape, implying an alternative mechanism for improvement in papilledema and axoplasmic flow, independent of a reduction in the pressure differential. (ClinicalTrials.gov number, NCT01003639.).

Quantifying the Diversity and Similarity of Surgical Procedures Among Hospitals and Anesthesia Providers.

In this Statistical Grand Rounds, we review methods for the analysis of the diversity of procedures among hospitals, the activities among anesthesia providers, etc. We apply multiple methods and consider their relative reliability and usefulness for perioperative applications, including calculations of SEs. We also review methods for comparing the similarity of procedures among hospitals, activities among anesthesia providers, etc. We again apply multiple methods and consider their relative reliability and usefulness for perioperative applications. The applications include strategic analyses (e.g., hospital marketing) and human resource analytics (e.g., comparisons among providers). Measures of diversity of procedures and activities (e.g., Herfindahl and Gini-Simpson index) are used for quantification of each facility (hospital) or anesthesia provider, one at a time. Diversity can be thought of as a summary measure. Thus, if the diversity of procedures for 48 hospitals is studied, the diversity (and its SE) is being calculated for each hospital. Likewise, the effective numbers of common procedures at each hospital can be calculated (e.g., by using the exponential of the Shannon index). Measures of similarity are pairwise assessments. Thus, if quantifying the similarity of procedures among cases with a break or handoff versus cases without a break or handoff, a similarity index represents a correlation coefficient. There are several different measures of similarity, and we compare their features and applicability for perioperative data. We rely extensively on sensitivity analyses to interpret observed values of the similarity index.

Influence of provider type (nurse anesthetist or resident physician), staff assignments, and other covariates on daily evaluations of anesthesiologists' quality of supervision.

BACKGROUND: At many U.S. healthcare facilities, supervision of anesthesiology residents and/or Certified Registered Nurse Anesthetists (CRNAs) is a major daily responsibility of anesthesiologists. Our department implemented a daily process by which the supervision provided by each anesthesiologist working in operating rooms was evaluated by the anesthesiology resident(s) and CRNA(s) with whom they worked the previous day. METHODS: Requests for evaluation were sent daily via e-mail to each resident and CRNA after working in an operating room. Supervision scores were analyzed after 6 months, and aligned with the cases' American Society of Anesthesiologists Relative Value Guide units. RESULTS: (1) Mean monthly evaluation completion rates exceeded 85% (residents P = 0.0001, CRNAs P = 0.0005). (2) Pairwise by anesthesiologist, residents and CRNAs mean supervision scores were correlated (P < 0.0001), but residents assigned greater scores than did CRNAs (P < 0.0001). The pairwise differences between residents and CRNAs were heterogeneous among anesthesiologists (P < 0.0001). (3) Anesthesiologist supervision scores provided by residents were: (a) greater when a resident had more units of work that day with the rated anesthesiologist (P < 0.0001), and (b) less when the anesthesiologist had more units of work that same day with other providers (P < 0.0001). However, the relationships were unimportantly small, Kendall τb = +0.083 ± 0.014 (SE) and τb = -0.057 ± 0.014, respectively. The correlations were even less among the CRNAs, τb = -0.029 ± 0.013 and τb = -0.004 ± 0.012, respectively. (4) There also was unimportantly small association between a resident's or CRNA's mean score for an anesthesiologist and the number of days worked together (τb = -0.069 ± 0.023 and τb = +0.038 ± 0.020, respectively). CONCLUSIONS: Although the attributes that residents and CRNA perceive as constituting "supervision" significantly share commonalities, supervision scores should be analyzed separately for residents and CRNAs. Although mean supervision scores differ markedly among anesthesiologists, supervision scores are influenced negligibly by staff assignments (e.g., how busy the anesthesiologist is with other operating rooms).

Value of a scheduled duration quantified in terms of equivalent numbers of historical cases.

BACKGROUND: Probabilistic estimates of case duration are important for several decisions on and soon before the day of surgery, including filling or preventing a hole in the operating room schedule, and comparing the durations of cases between operating rooms with and without use of specialized equipment to prevent resource conflicts. Bayesian methods use a weighted combination of the surgeon's estimated operating room time and historical data as a prediction for the median duration of the next case of the same combination. Process variability around that prediction (i.e., the coefficient of variation) is estimated using data from similar procedures. A Bayesian method relies on a parameter, τ, that specifies the equivalence between the scheduled estimate and the information contained in the median of a certain number of historical data. METHODS: Times from operating room entrance to exit ("case duration") were obtained for multiple procedures and surgeons at 3 U.S. academic hospitals. A new method for estimating the parameter τ was developed. RESULTS: (1) The method is reliable and has content, convergent, concurrent, and construct validity. (2) The magnitudes of the Somer's D correlations between scheduled and actual durations are small when stratified by procedure (0.05-0.14), but substantial when pooled among all cases and procedures (0.58-0.78). This pattern of correlations matches that when medians (or means) of historical durations are used. Thus, scheduled durations and historical data are essentially interchangeable for estimating the median duration of a future case. (3) Most cases (79%-88%) either have so few historical durations (0-2) that the Bayesian estimate is influenced principally by the scheduled duration, or so many historical durations (>10) that the Bayesian estimate is influenced principally by the historical durations. Thus, the balance between the scheduled duration versus historical data has little influence on results for most cases. (4) Mean absolute predictive errors are insensitive to a wide range of values (e.g., 1-10) for the parameter. The implication is that τ does not routinely need to be calculated for a given hospital, but can be set to any reasonable value (e.g., 5). CONCLUSIONS: Understanding performance of Bayesian methods for case duration is important because variability in durations has a large influence on appropriate management decisions the working day before and on the day of surgery. Both scheduled durations and historical data need to be used for these decisions. What matters is not the choice of τ but quantifying the variability using the Bayesian method and using it in managerial decisions.

Estimating surgical case durations and making comparisons among facilities: identifying facilities with lower anesthesia professional fees.

Consumer-driven health care relies on transparency in cost estimates for surgery, including anesthesia professional fees. Using systematic narrative review, we show that providing anesthesia costs requires that each facility (anesthesia group) estimate statistics, reasonably the mean and the 90% upper prediction limit of case durations by procedure. The prediction limits need to be calculated, for many procedures, using Bayesian methods based on the log-normal distribution. Insurers and/or governments lack scheduled durations and procedures and cannot practically infer these estimates because of the large heterogeneities among facilities in the means and coefficients of variation of durations. Consequently, the insurance industry cannot provide the cost information accurately from public and private databases. Instead, the role of insurers and/or governments can be to identify facilities with significantly briefer durations (costs to the patient) than average. Such comparisons of durations among facilities should be performed with correction for the effects of the multiple comparisons. Our review also has direct implications to the potentially more important issue of how to study the association between anesthetic durations and patient morbidity and mortality. When pooling duration data among facilities, both the large heterogeneity in the means and coefficients of variation of durations among facilities need to be considered (e.g., using "multilevel" or "hierarchical" models).

Monitoring changes in individual surgeon's workloads using anesthesia data.

PURPOSE: We investigated whether changes in the number of cases performed by surgeons can be used as an appropriate surrogate for anesthesia departments' billed units. METHODS: We used both number of cases performed and the American Society of Anesthesiologists' Relative Value Guide™ (ASA RVG) units to assess all operating room anesthetics of an anesthesia group for two sets of 13 four-week periods. The units correspond to Canadian basic units and time units. RESULTS: Although the number of ASA RVG units is an economically important variable that quantifies perioperative workload, the number of cases is a suitable surrogate for ASA RVG units when used to monitor individual surgeons. The pooled mean Pearson correlation coefficient between the two variables was r = 0.95, with 95% confidence interval 0.94 to 0.96. In addition, there were essentially none to very weak pairwise correlations among surgeons. CONCLUSIONS: Informal hospital analyses of relative changes in a surgeon's caseload over one year using anesthesia workload data or anesthesia billing data will generally give equivalent results. The principal importance of our findings is that they can be used by anesthesiologists, specifically department heads, in their role as part of operating room committees. Such committees institute plans to revise the caseload of one or a few surgeons, and they then evaluate the results of those plans. The findings of this study are applicable to all anesthesia groups and may be especially valuable to the heads of anesthesiology departments who do not have the data to repeat our analyses.

Systematic criteria for type and screen based on procedure's probability of erythrocyte transfusion.

BACKGROUND: At many hospitals, the type and screen decision is guided by the hospital's maximum surgical blood order schedule, a document that includes for each scheduled (elective) surgical procedure a recommendation of whether a preoperative type and screen be performed. There is substantial heterogeneity in the scientific literature for how that decision should be made. METHODS: Anesthesia information management system data were retrieved from the 160,207 scheduled noncardiac cases in adults of 1,253 procedures at a hospital. RESULTS: Neither assuming a Poisson distribution of mean erythrocyte units transfused, nor grouping rare procedures into larger groups based on their anesthesia Current Procedural Terminology code, was reliable. In contrast, procedures could be defined to have minimal estimated blood loss (less than 50 ml) based on low incidence of transfusion and low incidence of the hemoglobin being checked preoperatively. Among these procedures, when the lower 95% confidence limit for erythrocyte transfusion was less than 5%, type and screen was shown to be unnecessary. The method was useful based on including multiple differences from the hospital's maximum surgical blood order schedule and clinicians' test ordering (greater than or equal to 29% fewer type and screen). Results were the same with a Bayesian random effects model. CONCLUSIONS: We validated a method to determine procedures on the maximum surgical blood order schedule for which type and screen was not indicated using the estimated blood losses and incidences of transfusion.

Analysis of interventions influencing or reducing patient waiting while stratifying by surgical procedure.

Facilitation of the coordination of presurgical care is desirable not only from the patients' perspective, but also for increasing operating room productivity of surgeons and anesthesiologists. Times from each patient's first referral to a surgeon until surgery will be available on a vast scale from regional health information exchanges. Treatments (interventions) can include, for example, case management and use of health system networks with common electronic medical records. We developed a method to compare waiting times between treatment (intervention) groups, while stratifying by procedure, despite (1) highly skewed but non-lognormally distributed data, (2) highly heterogeneous sample sizes among groups and procedures, and (3) many combinations of groups and procedures with small sample sizes, resulting in estimated means and variances having substantial uncertainty. Corresponding results obtained by analyzing data from a health system were as follows. (1) The method uses a random-effects model to accommodate procedure heterogeneity and is otherwise distribution free. Log transformation reduced the skewness in waiting time data, making the distribution-free first-order Taylor series approximation analysis of proportional changes between treatments (interventions) reasonable. However, when instead of the random-effects distribution-free analysis, the assumption was made of lognormal distributions, the estimate of treatment effect was biased. (2) Repeating the analysis without stratification by procedure also resulted in biased estimates. (3) There are nearly an unlimited number of different procedures, most rare, so that considering procedure as a random effect was appropriate. Over the ranges of estimated parameter values, prior Monte-Carlo simulation studies showed that meta-analysis using the simple method of moments was appropriate. However, because many treatment/procedure combinations have small sample sizes, confidence interval coverage for the treatment effect was too narrow other than when the degrees of freedom were corrected. Nevertheless, the resulting statistical methodology is straightforward to apply because the data needed are just the summary statistics and the method involves just a series of equations to be followed in a stepwise manner (e.g., in a spreadsheet program such as Microsoft Office Excel).

Analysis of operating room allocations to optimize scheduling of specialty rotations for anesthesia trainees.

INTRODUCTION: Because specialty workloads and corresponding operating room (OR) allocations vary among days of the week, anesthesia residents and student nurse anesthetists are sometimes assigned to cases off rotation (e.g., scheduled for cardiac surgery but assigned to urology for the day). We describe a method to create hybrid rotations of two specialties (e.g., cardiac and vascular surgery), thereby reducing the numbers of days that trainees are "pulled" from their scheduled rotations. METHODS: Raw data were the number of hours of OR time used by each surgical specialty on each workday for the preceding 9 months. These OR workloads were converted to the number of ORs to be allocated to each specialty for each day of the week on the basis of maximization of the efficiency of use of OR time. We considered all potential hybrid rotations of pairwise combinations of specialties to which trainees could be assigned. Integer linear programming was used to calculate the maximum number of trainees who could be scheduled to hybrid rotations and receive daily assignments matching those rotations. RESULTS: Validity of the results was shown by using data from a small facility for which the optimal solution could be discerned by inspection. Validity (appropriateness) of the constraints was demonstrated by the exclusion of each constraint, resulting in answers that are obviously incorrect. Novelty and usefulness of the method was evidenced by its choosing from among hundreds of thousands of potential combinations of specialties and its identifying appropriate assignments that were substantively different from current rotations. CONCLUSIONS: We developed a methodology to determine rotations consisting of combinations of specialties to be paired for purposes of trainee scheduling to reduce the incidence of daily assignments off rotation. Practically, with this method, anesthesia residents and student nurse anesthetists can be assigned cases within their scheduled rotations as often as possible.

Influence of procedure classification on process variability and parameter uncertainty of surgical case durations.

BACKGROUND: Predictive variability of operating room (OR) times influences decision making on the day of surgery including when to start add-on cases, whether to move a case from one OR to another, and where to assign relief staff. One contributor to predictive variability is process variability, which arises among cases of the same procedure(s). Another contributor is parameter uncertainty, which is caused by small sample sizes of historical data. METHODS: Process variability was quantified using absolute percentage errors of surgeons' bias-corrected estimates of OR time. The influence of procedure classification on process variability was studied using a dataset of 61,353 cases, each with 1 to 5 scheduled and actual Current Procedural Terminology (CPT) codes (i.e., a standardized vocabulary). Parameter uncertainty's sensitivity to sample size was quantified by studying ratios of 90% prediction bounds to medians. That studied dataset of 65,661 cases was used previously to validate a Bayesian method to calculate 90% prediction bounds using combinations of surgeons' scheduled estimates and historical OR times. RESULTS: (1) Process variability differed significantly among 11 groups of surgical specialty and case urgency (P < 0.0001). For example, absolute percentage errors exceeded the overall median of 22% for 57% of urgent spine surgery cases versus 42% of elective spine surgery cases. (2) Process variability was not increased when scheduled and actual CPTs differed (P = 0.23 without and P = 0.47 with stratification based on the 11 groups), because most differences represented known (planned) options inherent to procedures. (3) Process variability was not associated with incidence of procedures (P = 0.79), after excluding cataract surgery, a procedure with high relative variability. (4) Parameter uncertainty from uncommon procedures (0-2 historical cases) accounted for essentially all of the uncertainty in decisions dependent on estimates of OR times. The Bayesian method moderated the effect of small sample sizes on uncertainty in estimates of OR times. In contrast, from prior work, the use of broad categories of procedures reduces parameter uncertainty but at the expense of increased process variability. CONCLUSIONS: For procedures with few historic data, the Bayesian method allows for effective case duration prediction, permitting use of detailed procedure descriptions. Although fine resolution of scheduling procedures increases the chance of performed procedure(s) differing from scheduled procedure(s), this does not increase process variability. Future studies need both to address differences in process variability among specialties and accept the limitation that findings from one may not apply to others.

Forecasting and perception of average and latest hours worked by on-call anesthesiologists.

BACKGROUND: We studied the value of providing information to anesthesia providers about the length of time typically worked during on-call shifts. The mean time at which a shift ends can be used for purposes of trades, payments, or reverse auctions, because the mean is proportional to the total time. The 80th percentile (with a suitable upper confidence limit for uncertainty due to limited sample sizes) can be used for judging the earliest time by which after-work activities reasonably can be planned. METHODS: (A) Three years of operating room (OR) information system data were analyzed. Dependent variables were the earliest times when the numbers of ORs running were always 30 min, whereas errors of this magnitude were less for the mean (44%, P = 0.0004). CONCLUSIONS: Historical data from OR or anesthesia information management systems, or from anesthesia billing systems, can be used months before staff scheduling to provide insight to anesthesia providers on respective calls. The data are useful because experience provides limited intuition. Updates on scheduled workload available closer to the day of surgery provided only marginal increases in knowledge over the use of historical data.

Automatic updating of times remaining in surgical cases using bayesian analysis of historical case duration data and "instant messaging" updates from anesthesia providers.

BACKGROUND: Operating room (OR) whiteboards (status displays) communicate times remaining for ongoing cases to perioperative stakeholders (e.g., postanesthesia care unit, anesthesiologists, holding area, and control desks). Usually, scheduled end times are shown for each OR. However, these displays are inaccurate for predicting the time that remains in a case. Once a case scheduled for 2 h has been on-going for 1.5 h, the median time remaining is not 0.5 h but longer, and the amount longer differs among procedures. METHODS: We derived the conditional Bayesian lower prediction bound of a case's duration, conditional on the minutes of elapsed OR time. Our derivations make use of the posterior predictive distribution of OR times following an exponential of a scaled Student t distribution that depends on the scheduled OR time and several parameters calculated from historical case duration data. The statistical method was implemented using Structured Query Language (SQL) running on the anesthesia information management system (AIMS) database server. In addition, AIMS workstations were sent instant messages displaying a pop-up dialog box asking for anesthesia providers' estimates for remaining times. The dialogs caused negotiated interruptions (i.e., the anesthesia provider could reply immediately, keep the dialog displayed, or defer response). There were no announcements, education, or efforts to promote buy-in. RESULTS: After a case had been in the OR longer than scheduled, the median remaining OR time for the case changes little over time (e.g., 35 min left at 2:30 pm and also at 3:00 pm while the case was still on-going). However, the remaining time differs substantially among surgeons and scheduled procedure(s) (16 min longer [10th percentile], 35 min [50th], and 86 min [90th]). We therefore implemented an automatic method to estimate the times remaining in cases. The system was operational for >119 of each day's 120 5-min intervals. When instant message dialogs appearing on AIMS workstations were used to elicit estimates of times remaining from anesthesia providers, acknowledgment was on average within 1.2 min (95% confidence interval [CI] 1.1-1.3 min). The 90th percentile of latencies was 6.5 min (CI: 4.4-7.0 min). CONCLUSIONS: For cases taking nearly as long as or longer than scheduled, each 1 min progression of OR time reduces the median time remaining in a case by <1 min. We implemented automated calculation of times remaining for every case at a 29 OR hospital.