Exceedance Probabilities of Log-normal Distributions for One Group, Two Groups, and Meta-analysis of Multiple Two-group Studies, With Application to Analyses of Prolonged Times to Tracheal Extubation.

Many randomized trials measure means and standard deviations of anesthesia recovery time (e.g., times to tracheal extubation). We show how to use generalized pivotal methods to compare the probabilities of exceeding a tolerance limit (e.g., > 15 min, prolonged times to tracheal extubation). The topic is important because the economic benefits of faster anesthesia emergence depend on reducing variability, not means, especially prevention of very long recovery times. Generalized pivotal methods are applied using computer simulation (e.g., using two Excel formulas for one group and three formulas for two group comparisons). The endpoint for each study with two groups is the ratio between groups of the probabilities of times exceeding a threshold or the ratio of the standard deviations. Confidence intervals and variances for the incremental risk ratio of the exceedance probabilities and for ratios of standard deviations are calculated using studies' sample sizes, sample means in the time scale of recovery times, and sample standard deviations in the time scale. Ratios are combined among studies using the DerSimonian-Laird estimate of the heterogeneity variance estimate, with Knapp-Hartung adjustment for the relatively small (N = 15) numbers of studies in the meta-analysis. We show larger absolute variability among studies' results when analyzed based on exceedance probabilities rather than standard deviations. Therefore, if an investigator's primary goal is to quantify reductions in the variability of recovery times (e.g., times until patients are ready for post-anesthesia care unit discharge), we recommend analyzing the standard deviations. When exceedance probabilities themselves are relevant, they can be analyzed from the original studies' summary measures.

Circumferential trabecular meshwork cell density in the human eye.

The cells residing in the trabecular meshwork (TM) fulfill important roles in the maintenance of the tissue and the regulation of intraocular pressure (IOP). Here we examine (i) TM cell distribution along the circumference of the human eye, (ii) differences in TM cell density between regions of high and low outflow, and (iii) whether TM cell distribution in eyes from donors with primary open angle glaucoma (POAG) differs from that of normal eyes. Toward this end, the TM cell density from 12 radial segments around the circumference of the TM of human donor eyes (n = 6) with and without POAG was determined using histochemical methods. Areas of high, median, and low outflow were mapped in a different set of human donor eyes that were perfused in organ culture, and TM cell densities in these areas were determined in normal (n = 11) and POAG eyes (n = 6). Our analysis of 1380 tissue sections taken from the first set of six eyes shows that the average TM cell density of these six eyes ranges from 15.5 to 23.7 cells/100 µm and is negatively correlated to the maximum IOP recorded for each donor eye (R2 = 0.91). Considerable differences in TM cell density exist among sections taken from the same segment of an individual eye (average standard deviation = 2.35 cells/100 µm). Less variability is observed among the segment averages across the eye's circumference (average standard deviation = 1.03 cells/100 µm). Variations in cell density are similar between normal and POAG eyes and are not correlated with the anatomic position of examined segments (p = 0.745). The analysis of the second set of eyes shows that TM regions of high outflow display a TM cell density similar to regions of median or low outflow in both normal and POAG eyes. Together these findings demonstrate that (i) statistically significant differences in TM cell density exist along the circumference of each eye (ii) TM cellularity is not correlated with segmental flow and (iii) eyes with POAG, while displaying reduced TM cellularity, do not exhibit higher TM cell variability than normal eyes. Finally, statistical analysis of sections and segments indicates that measurements from 12 sections taken from 2 segments provide a reliable and cost-effective estimate of a human eye's TM cell density.

Association between leniency of anesthesiologists when evaluating certified registered nurse anesthetists and when evaluating didactic lectures.

Daily evaluations of certified registered nurse anesthetists' (CRNAs') work habits by anesthesiologists should be adjusted for rater leniency. The current study tested the hypothesis that there is a pairwise association by rater between leniencies of evaluations of CRNAs' daily work habits and of didactic lectures. The historical cohorts were anesthesiologists' evaluations over 53 months of CRNAs' daily work habits and 65 months of didactic lectures by visiting professors and faculty. The binary endpoints were the Likert scale scores for all 6 and 10 items, respectively, equaling the maximums of 5 for all items, or not. Mixed effects logistic regression estimated the odds of each ratee performing above or below average adjusted for rater leniency. Bivariate errors in variables least squares linear regression estimated the association between the leniency of the anesthesiologists' evaluations of work habits and didactic lectures. There were 29/107 (27%) raters who were more severe in their evaluations of CRNAs' work habits than other anesthesiologists (two-sided P < 0.01); 34/107 (32%) raters were more lenient. When evaluating lectures, 3/81 (4%) raters were more severe and 8/81 (10%) more lenient. Among the 67 anesthesiologists rating both, leniency (or severity) for work habits was not associated with that for lectures (P = 0.90, unitless slope between logits 0.02, 95% confidence interval -0.34 to 0.30). Rater leniency is of large magnitude when making daily clinical evaluations, even when using a valid and psychometrically reliable instrument. Rater leniency was context dependent, not solely a reflection of raters' personality or rating style.

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.

Futility of Cluster Designs at Individual Hospitals to Study Surgical Site Infections and Interventions Involving the Installation of Capital Equipment in Operating Rooms.

Anesthesia workspaces are integral components in the chains of many intraoperative bacterial transmission events resulting in surgical site infections (SSI). Matched cohort designs can be used to compare SSI rates among operating rooms (ORs) with or without capital equipment purchases (e.g., new anesthesia machines). Patients receiving care in intervention ORs (i.e., with installed capital equipment) are matched with similar patients receiving care in ORs lacking the intervention. We evaluate statistical power of an alternative design for clinical trials in which, instead, SSI incidences are compared directly among ORs (i.e., the ORs form the clusters) at single hospitals (e.g., the 5 ORs with bactericidal lights vs. the 5 other ORs). Data used for parameter estimates were SSI for 24 categories of procedures among 338 hospitals in the State of California, 2015. Estimated statistical power was ≅8.4% for detecting a reduction in the incidence of SSI from 3.6% to 2.4% over 1 year with 5 intervention ORs and 5 control ORs. For ≅80% statistical power, >20 such hospitals would be needed to complete a study in 1 year. Matched paired cluster designs pair similar ORs (e.g., 2 cardiac ORs, 1 to intervention and 1 to control). With 5 pairs, statistical power would be even less than the estimated 8.4%. Cluster designs (i.e., analyses by OR) are not suitable for comparing SSI among ORs at single hospitals. Even though matched cohort designs are non-randomized and thus have lesser validity, matching patients by their risk factors for SSI is more practical.

Validation of a New Method to Automatically Select Cases With Intraoperative Red Blood Cell Transfusion for Audit.

BACKGROUND: Hospitals review allogeneic red blood cell (RBC) transfusions for appropriateness. Audit criteria have been published that apply to 5 common procedures. We expanded on this work to study the management decision of selecting which cases involving transfusion of at least 1 RBC unit to audit (review) among all surgical procedures, including those previously studied. METHODS: This retrospective, observational study included 400,000 cases among 1891 different procedures over an 11-year period. There were 12,616 cases with RBC transfusion. We studied the proportions of cases that would be audited based on criteria of nadir hemoglobin (Hb) greater than the hospital's selected transfusion threshold, or absent Hb or missing estimated blood loss (EBL) among procedures with median EBL <500 mL. This threshold EBL was selected because it is approximately the volume removed during the donation of a single unit of whole blood at a blood bank. Missing EBL is important to the audit decision for cases in which the procedures' median EBL is <500 mL because, without an indication of the extent of bleeding, there are insufficient data to assume that there was sufficient blood loss to justify the transfusion. RESULTS: Most cases (>50%) that would be audited and most cases (>50%) with transfusion were among procedures with median EBL <500 mL (P < .0001). Among cases with transfusion and nadir Hb >9 g/dL, the procedure's median EBL was <500 mL for 3.0 times more cases than for procedures having a median EBL ≥500 mL. A greater percentage of cases would be recommended for audit based on missing values for Hb and/or EBL than based on exceeding the Hb threshold among cases of procedures with median EBL ≥500 mL (P < .0001). There were 3.7 times as many cases with transfusion that had missing values for Hb and/or EBL than had a nadir Hb >9 g/dL and median EBL for the procedure ≥500 mL. CONCLUSIONS: An automated process to select cases for audit of intraoperative transfusion of RBC needs to consider the median EBL of the procedure, whether the nadir Hb is below the hospital's Hb transfusion threshold for surgical cases, and the absence of either a Hb or entry of the EBL for the case. This conclusion applies to all surgical cases and procedures.

Operating Room Anesthesia Subspecialization Is Not Associated With Significantly Greater Quality of Supervision of Anesthesia Residents and Nurse Anesthetists.

BACKGROUND: Supervision of anesthesia residents and nurse anesthetists is a major responsibility of faculty anesthesiologists. The quality of their supervision can be assessed quantitatively by the anesthesia residents and nurse anesthetists. Supervision scores are an independent measure of the contribution of the anesthesiologist to patient care. We evaluated the association between quality of supervision and level of specialization of anesthesiologists. METHODS: We used two 6-month periods, one with no feedback to anesthesiologists of the residents' and nurse anesthetists' evaluations, and the other with feedback. Supervision scores provided by residents and nurse anesthetists were considered separately. Sample sizes among the 4 combinations ranged from n = 51 to n = 62 University of Iowa faculty. For each supervising anesthesiologist and 6-month period, we calculated the proportion of anesthetic cases attributable to each anesthesia Current Procedural Terminology code. The sum of the square of the proportions, a measurement of diversity, is known as the Herfindahl index. The inverse of this index represents the effective number of common procedures. The diversity (degree of specialization) of each faculty anesthesiologist was measured attributing each case to: (1) the anesthesiologist who supervised for the longest total period of time, (2) the anesthesiologist who started the case, or (3) the anesthesiologist who started the case, limited to cases started during "regular hours" (defined as nonholiday Monday to Friday, 07:00 AM to 02:59 PM). Inferential analysis was performed using bivariate-weighted least-squares regression. RESULTS: The point estimates of all 12 slopes were in the direction of greater specialization of practice of the evaluated faculty anesthesiologist being associated with significantly lower supervision scores. Among supervision scores provided by nurse anesthetists, the association was statistically significant for the third of the 6-month periods under the first and second ways of attributing the cases (uncorrected P < .0001). However, the slopes of the relationships were all small (eg, 0.109 ± 0.025 [SE] units on the 4-point supervision scale for a change of 10 common procedures). Among supervision scores provided by anesthesia residents, the association was statistically significant during the first period for all 3 ways of attributing the case (uncorrected P < .0001). However, again, the slopes were small (eg, 0.127 ± 0.027 units for a change of 10 common procedures). CONCLUSIONS: Greater clinical specialization of faculty anesthesiologists was not associated with meaningful improvements in quality of clinical supervision.

Measurement of faculty anesthesiologists' quality of clinical supervision has greater reliability when controlling for the leniency of the rating anesthesia resident: a retrospective cohort study.

BACKGROUND: Our department monitors the quality of anesthesiologists' clinical supervision and provides each anesthesiologist with periodic feedback. We hypothesized that greater differentiation among anesthesiologists' supervision scores could be obtained by adjusting for leniency of the rating resident. METHODS: From July 1, 2013 to December 31, 2015, our department has utilized the de Oliveira Filho unidimensional nine-item supervision scale to assess the quality of clinical supervision provided by faculty as rated by residents. We examined all 13,664 ratings of the 97 anesthesiologists (ratees) by the 65 residents (raters). Testing for internal consistency among answers to questions (large Cronbach's alpha > 0.90) was performed to rule out that one or two questions accounted for leniency. Mixed-effects logistic regression was used to compare ratees while controlling for rater leniency vs using Student t tests without rater leniency. RESULTS: The mean supervision scale score was calculated for each combination of the 65 raters and nine questions. The Cronbach's alpha was very large (0.977). The mean score was calculated for each of the 3,421 observed combinations of resident and anesthesiologist. The logits of the percentage of scores equal to the maximum value of 4.00 were normally distributed (residents, P = 0.24; anesthesiologists, P = 0.50). There were 20/97 anesthesiologists identified as significant outliers (13 with below average supervision scores and seven with better than average) using the mixed-effects logistic regression with rater leniency entered as a fixed effect but not by Student's t test. In contrast, there were three of 97 anesthesiologists identified as outliers (all three above average) using Student's t tests but not by logistic regression with leniency. The 20 vs 3 was significant (P < 0.001). CONCLUSIONS: Use of logistic regression with leniency results in greater detection of anesthesiologists with significantly better (or worse) clinical supervision scores than use of Student's t tests (i.e., without adjustment for rater leniency).

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.

Diversity and Similarity of Anesthesia Procedures in the United States During and Among Regular Work Hours, Evenings, and Weekends.

BACKGROUND: Anesthesiologists providing care during off hours (ie, weekends or holidays, or cases started during the evening or late afternoon) are more likely to care for patients at greater risk of sustaining major adverse events than when they work during regular hours (eg, Monday through Friday, from 7:00 AM to 2:59 PM). We consider the logical inconsistency of using subspecialty teams during regular hours but not during weekends or evenings. METHODS: We analyzed data from the Anesthesia Quality Institute's National Anesthesia Clinical Outcomes Registry (NACOR). Among the hospitals in the United States, we estimated the average number of common types of anesthesia procedures (ie, diversity measured as inverse of Herfindahl index), and the average difference in the number of common procedures between 2 off-hours periods (regular hours versus weekends, and regular hours versus evenings). We also used NACOR data to estimate the average similarity in the distributions of procedures between regular hours and weekends and between regular hours and evenings in US facilities. Results are reported as mean ± standard error of the mean among 399 facilities nationwide with weekend cases. RESULTS: The distributions of common procedures were moderately similar (ie, not large, <.8) between regular hours and evenings (similarity index .59 ± .01) and between regular hours and weekends (similarity index, .55 ± .02). For most facilities, the number of common procedures differed by <5 procedures between regular hours and evenings (74.4% of facilities, P < .0001) and between regular hours and weekends (64.7% of facilities, P < .0001). The average number of common procedures was 13.59 ± .12 for regular hours, 13.12 ± .13 for evenings, and 9.43 ± .13 for weekends. The pairwise differences by facility were .13 ± .07 procedures (P = .090) between regular hours and evenings and 3.37 ± .12 procedures (P < .0001) between regular hours and weekends. In contrast, the differences were -5.18 ± .12 and 7.59 ± .13, respectively, when calculated using nationally pooled data. This was because the numbers of common procedures were 32.23 ± .05, 37.41 ± .11, and 24.64 ± .12 for regular hours, evenings, and weekends, respectively (ie, >2x the number of common procedures calculated by facility). CONCLUSIONS: The numbers of procedures commonly performed at most facilities are fewer in number than those that are commonly performed nationally. Thus, decisions on anesthesia specialization should be based on quantitative analysis of local data rather than national recommendations using pooled data. By facility, the number of different procedures that take place during regular hours and off hours (diversity) is essentially the same, but there is only moderate similarity in the procedures performed. Thus, at many facilities, anesthesiologists who work principally within a single specialty during regular work hours will likely not have substantial contemporary experience with many procedures performed during off hours.

Large Heterogeneity in Mean Durations of Labor Analgesia Among Hospitals Reporting to the American Society of Anesthesiologists' Anesthesia Quality Institute.

BACKGROUND: Variability in the mean durations of labor analgesia for vaginal delivery among hospitals is unknown. Such differences in means among hospitals would influence appropriate equitable fee-for-service payment to US anesthesia groups. Equitable payment is the foundational principle of relative value unit payment, which, for anesthesia in the United States, means use of the American Society of Anesthesiologist's Relative Value Guide. METHODS: We analyzed data from the American Society of Anesthesiologists' Anesthesia Quality Institute to test whether there are large differences in mean durations of labor analgesia for vaginal delivery among US hospitals. We choose the statistical methodology for that analysis using detailed data from 2 individual hospitals. Analyses of the means were performed for the 172 hospitals reporting a total of at least 200 durations; having no greater than 5.0% of durations 1.0 hour or less; and at least 5 four-week periods each having a mean of at least one epidural every couple of days. The 172 hospitals provided for n = 5671 combinations of hospital and 4-week period and 551,707 labor epidurals, with an overall mean duration of 6.12 hours (SE, 0.001 hour). RESULTS: 55.2% of the 172 hospitals had mean durations of labor analgesia for vaginal delivery that each differed (P < 0.001) from the overall mean. Among those 55.2% were the 9.9% of hospitals with means ≤5.12 hours. Those mean durations on the low end ranged from 2.68 (SE, 0.17) to 5.10 (SE, 0.07) hours. Also, among the 55.2% were the 12.2% of hospitals with means ≥7.12 hours. Those mean durations at the high end ranged from 7.13 (SE, 0.08) to 12.03 (SE, 0.23) hours. The heterogeneity in the mean durations among hospitals would have been greater had the inclusion criteria not been applied. CONCLUSIONS: Our results show that the number of labor epidurals alone is not a valid measure to quantify obstetrical anesthesia productivity. In addition, payment to US anesthesia groups for labor analgesia based solely on the number of labor epidurals initiated is not equitable. Previous work showed lack of validity and equality of payment based on face-to-face time with the patient (i.e., like a surgical anesthetic). The use of base and time units, with one time unit per hour, is a suitable payment system.

Bernoulli Cumulative Sum (CUSUM) control charts for monitoring of anesthesiologists' performance in supervising anesthesia residents and nurse anesthetists.

We describe our experiences in using Bernoulli cumulative sum (CUSUM) control charts for monitoring clinician performance. The supervision provided by each anesthesiologist is evaluated daily by the Certified Registered Nurse Anesthetists (CRNAs) and/or anesthesia residents with whom they work. Each of 9 items is evaluated (1 = never, 2 = rarely, 3 = frequently, 4 = always). The score is the mean of the 9 responses. Choosing thresholds for low scores is straightforward, <2.0 for CRNAs and <3.0 for residents. Bernoulli CUSUM detection of low scores was within 50 ± 14 (median ± quartile deviation) days rather than 182 days without use of CUSUM. The true positive detection of anesthesiologists with incidences of low scores greater than the chosen "out-of-control" rate was 14 of 14. The false-positive detection rate was 0 of 29. This CUSUM performance exceeded that of Shewhart individual control charts, for which the smallest threshold sufficiently large to detect 14 of 14 true positives had false-positive detection of 16 of 29 anesthesiologists. The Bernoulli CUSUM assumes that scores are known right away, which is untrue. However, CUSUM performance was insensitive to this assumption. The Bernoulli CUSUM assumes statistical independence of scores, which also is untrue. For example, when an evaluation of an anesthesiologist 1 day by a CRNA had a low score, there was an increased chance that another CRNA working in a different operating room on the same day would also give that same anesthesiologist a low score (P < 0.0001). This correlation among scores does affect the Bernoulli CUSUM, such that detection is more likely. This is an advantage for our continual process improvement application since it flags individuals for further evaluation by managers while maintaining confidentiality of raters.

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).

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.

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.

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).

Decreased Expression of Glial-Derived Neurotrophic Factor Receptors in Glaucomatous Human Retinas.

PURPOSE: The purpose of this study was to examine the expression of glial-derived neurotrophic factor (GDNF), the GDNF receptors GFRα1 and GFRα2, ciliary neurotrophic factor (CNTF), and the CNTF receptor CNTFRα in normal and glaucomatous human tissue. METHODS: Human retinas were collected from 8 donors that had been clinically diagnosed and treated for glaucoma, and also from 9 healthy control donors. Immunohistochemical analysis for each trophic factor and receptor was performed. The percent of each retinal section labeled with each antibody was quantified for the total retinal thickness, and separately for the retinal ganglion cell (RGC) complex + retinal nerve fiber layer (RNFL). The expression of each protein was correlated with measures of the subject's ocular histories. RESULTS: The percentage area immunopositive for GFRα2 was significantly decreased in the total retinal thickness containing all retinal layers and in the combined RGC complex + RNFL in glaucomatous eyes in both the peripapillary region and more peripheral retinal locations. We also observed a decrease in GFRα1 expression in the peripapillary RGC Complex + RNFL in glaucoma patients compared to healthy control patients. We also observed a relationship between GDNF and its receptors with several outcomes obtained from the medical record. No differences in CNTF or CNTFR labeling were observed. CONCLUSION: Decreases in GDNF receptor expression in glaucomatous tissue may limit the potential for neuroprotective therapy by supplementation with GDNF.