Franklin Dexter

Purpose: Earlier, patients developed surgical site infection for 2.0% of cases without Staphylococcus aureus transmission through anesthesia work areas, 11% with S. aureus transmitted susceptible to prophylactic antibiotic, and 18% with transmission of antibiotic-resistant isolates. A randomized trial and an effectiveness study both found that anesthesiologists who used basic preventive measures (e.g., alcohol releasing intravenous caps) and received feedback on colony-forming units per surface area sampled (CFU) had reduced S. aureus transmission and postoperative healthcare-associated infections. We used prospectively collected data to evaluate whether CFU would be a reliable criterion for hospitals to assess anesthesiologists' contributions to postoperative infections.

Methods: During the summer of 2025, reservoirs (e.g., anesthetist's hands at case start/end) were sampled during 81 cesarean delivery cases performed in the same operating room. There were ≤ 15 reservoirs sampled per case.

Results: 52/1016 reservoir samples had S. aureus detected, more often with greater CFU (P = 0.0063). The 159/1016 samples with < 100 CFU had no S. aureus. Total CFU of all reservoirs for each case to total S. aureus isolates was 2.50 × 109 per S. aureus (standard error 0.53 × 109, N = 81 cases). CFU and S. aureus transmission were uncorrelated (all 15 reservoirs' unadjusted P ≥ 0.12, Holm-Bonferroni P > 0.99).

Conclusions: With substantive contamination (≥ 100 CFU), so few isolates are S. aureus that surrogate measures of insufficient disinfection (e.g., ATP bioluminescence) are inaccurate markers both of S. aureus isolation and transmission. The lack of association between contamination and transmission shows that feedback on CFU provides information on the effectiveness of disinfection, not on S. aureus transmission.

All patients scheduled for outpatient surgery or admission on the day of surgery need a designated time to be ready for the operating room. Searches were performed in Scopus. The principal causes of variability in operating room times were not related to surgeon behavior and scheduling, but process variability of the surgical procedures and parameter uncertainty due to few historical data on which to estimate operating room times. The ready time and fasting time of each patient can be chosen in such a system, incorporating the probability of preceding cases being cancelled and/or cases being moved among operating rooms, by selecting the optimal critical quantile of the ratios of actual start times to scheduled start times, counting from the start of the workday. We provide a Supplemental Excel file with the corresponding statistical implementation for reader's data. We also include a Supplemental PDF with details of the search protocols and statistical findings so that our narrative review serves as a single reference to be provided to the administrator, clinician, or other professional concerned with evidence-based approaches to choosing patient-ready and arrival times.

The Maximum Surgical Blood Ordering Schedule (MSBOS) is a procedure-specific lookup table for preoperative blood product ordering based on historical institutional transfusion rates.
We developed an optimal MSBOS algorithm that minimizes the probability that an adult patient will need a red blood cell transfusion that exceeds the MSBOS reservation, constrained by a prespecified overall crossmatch-to-transfusion ratio (e.g., 1.50 or 2.00). We provide Microsoft Excel 365 and Stata implementations. We tested the mathematics using 192,822 surgical cases across 2430 procedure codes over 7.8 years at a teaching hospital.
The probability distribution of units of red blood cells transfused did not follow Poisson distributions (i.e., suitability of MSBOS reservations cannot accurately be calculated from each patient's probability of transfusion or not). However, for 100% of procedures, there were monotonic decreases in the probabilities of extra units transfused (e.g., most patients 0 units, some 1-2 units, and few 3-4 units). We used this general shape for calculating the optimal MSBOS. Comparing this priority-based model with an alternative policy based on the mean units transfused per patient, MSBOS reservations were identical for the vast majority of procedures. When differences occurred, the priority-based assignment usually recommended higher reservation levels than the alternative heuristic: 288 procedures higher, and 14 lower, mostly by one unit. With the overall crossmatch-to-transfusion (CT) ratio preset at ≤2.00, the mean (standard deviation) of the ratio across the 135 categories each with at least one crossmatched unit was 1.787 (0.977). In other words, priority-based assignment results in large inequality of the crossmatch to transfusion ratio among procedures. The priority-based assignment maintained the ≤2.00 crossmatch-to-transfusion ratio while achieving a 37.9% decrease in the total hospital blood bank units (surgical and non-surgical) transfused but unreserved. Therefore, inventory par levels can be lower. This approach would have the greatest benefit for hospitals with blood banks using electronic crossmatching that are remotely located from the operating rooms suites and do not have red cell dispensing kiosks.
Our methodology provides an automated, optimal MSBOS for hospital blood bank inventory management that minimizes the probability that a patient will need a red blood cell transfusion that exceeds the reserved units, subject to the desired overall crossmatch to transfusion ratio. The optimal MSBOS can be used with our earlier methodology for automated decision-making for which patients have blood type and antibody screening.

Sequencing the cases with the smallest variability in case duration first usually means performing the shortest cases first. In the absence of downstream constraints such as full phase I post-anesthesia care unit beds (PACU), such sequencing reduces both patients’ average tardiness from scheduled start times and waiting times. However, PACU beds are often at capacity. We reviewed studies on case sequencing for operating room and non-operating anesthetizing locations.
Searches were performed in Scopus, using keywords and citations, reflecting the structure of the operating room management field. To find articles relevant to surgical sequencing constrained by PACU bed availability, a multi-step search methodology was employed. Shortest or least variable cases first were ruled out (or in) by reading and consideration of each article’s mathematical model(s) and solution algorithms.
:Twenty-six articles studied surgical case sequencing while incorporating downstream (e.g., PACU) constraints. No articles reported conditions in which the least variable or shortest cases sequenced to be performed first achieved best organizational performance. The three articles that made specific comparisons all found that the shortest cases first strategy performed relatively poorly. Managerial epidemiology studies from multiple hospitals showed that, in reality, current practice was the unsynchronized sequencing of multiple surgeons’ lists of cases. This behavior resulted in a random and thus uniform rate of admission into the PACU, achieving close to minimum peaks in bed and nursing demand, thus minimizing costs.
: The results of this narrative review show that sequencing surgical cases for the least variable and shortest cases to be performed first in operating rooms each workday is counterproductive. Unless a facility uses one of the sophisticated mathematical methods, clinical directors are recommended to change nothing and benefit from the resulting random sequencing.

Anesthesiologists are employees, and gender is a protected class. Therefore, we evaluated the effect of the anesthesiologist’s gender on anesthesia residents’ daily evaluations of the quality of their clinical supervision. Simultaneously, we evaluated the impact of the American Board of Anesthesiologists’ certification on the overall quality of supervision, as evaluated by our anesthesia resident physicians.
Evaluations with the de Oliveira Filho et al. supervision scale spanned October 2024 through September 2025 at one residency program. Mixed-effects logistic regression was used to adjust evaluation scores, maximum or not, for raters’ leniency/ severity. Weighted linear regression was performed, with the empirical Bayes predictive posterior mean estimate for each anesthesiologist’s clinical supervision performance as the dependent variable and the inverse of the squared standard errors as the weights.
From 3690 evaluations of 132 ratee anesthesiologists by 45 rating resident physicians, neither gender nor ABA board certification was significantly associated with supervision scores. The women had an estimated odds ratio of 0.78 compared to the men (P = 0.70), with a 98.3 % confidence interval of 0.47 to 1.29. Anesthesiologists without ABA certification had an estimated odds ratio of 0.69 (P = 0.15), with a 98.3 % confidence interval of 0.42 to 1.10. There was no interaction (P = 0.99).
Two earlier studies from different departments, using different approaches, found no effect of gender on faculty anesthesiologists’ evaluations of anesthesia residents. Our results complement these findings by similarly finding no significant effect on the evaluations of the anesthesiologists by the residents.

For anesthesia practitioners to contribute to reduced postoperative health-care-associated infections, they need to know which anesthetizing locations at their facilities have infections per week with confidence intervals (CI) exceeding relevant thresholds. We sought the development of more precise estimates and CIs.
We conducted a retrospective cohort study of the 2024 fiscal year of surgical cases at a large teaching hospital in Iowa (University of Iowa Health Care Medical Center, Iowa City, IA, USA), with 90-day postoperative infection codes from the International Classification of Diseases, 10th Revision, as diagnosed by surgical teams. Following earlier simulations, we used Poisson regression with heteroscedasticity-consistent robust variance estimation. We compared CI widths for new postoperative health-care-associated infections per week per room to the corresponding method of batch means, quantified as costs of Type I errors (e.g., unnecessary vs appropriate Staphylococcus aureus transmission monitoring) and Type II errors (e.g., failure to mitigate vs successful reductions in excess infections).
The 75 operating rooms and other anesthetizing locations ("rooms") studied had 1,095/42,978 (2.6%) cases with patients who developed postoperative infections. The 75 rooms × 366 days equaled 27,450 room days, with 96.2% having no patient who developed a postoperative infection (26,401), 3.7% having one infection, 0.2% having two infections, and 0.01% having three. There was no significant serial correlation between days by room or between rooms by day. The preceding case of a patient who developed a postoperative infection did not significantly increase the probability of the next case in the room being of a patient who developed an infection, all 75 Šidák-corrected P ≥ 0.32. Counts of infections per day were consistent with Poisson distributions for 73/75 rooms. The other two rooms had ratios of sample variances to sample means of 1.32 and 1.78, respectively. Among the 15 rooms with a mean of ≥ 0.50 infections per week, the 99% CIs with Poisson regression were narrower than using the method of batch means by approximately 35%. Pooling all rooms, the CI width was approximately 38% less. These reductions were equivalent to increasing sample sizes from 1.00 year to 2.35 and 2.60 years or reducing costs by 88% or 92%, respectively.
Poisson regression with robust variance estimation resulted in more precise estimates than did the method of batch means, which will lower health care costs. We recommend reporting counts of postoperative health-care-associated infections per week for each anesthetizing location by using this method.

Introduction
Centers for Medicare & Medicaid Services (CMS) Overall Hospital Quality Star Ratings provide public hospital quality metrics, yet may not fully account for community-level social risk factors affecting patient outcomes. This cross-sectional study of 2,348 US acute care hospitals investigated the association between CMS Overall Hospital Quality Star Ratings and hospital performance on measures of community commitment, defined by the Lown Institute’s inclusivity and community benefit metrics.
Methods
Data came from the CMS July 2024 Hospital General Information and Lown Institute Hospital Index for Social Responsibility datasets. Lown Institute inclusivity, reflecting demographic alignment between a hospital’s patient population and its surrounding community, and community benefit, reflecting selected hospital financial measures related to service to and support for vulnerable populations, were used as hospital-level proxies for community commitment.
Results
Kendall’s τb partial correlations showed that higher star ratings were weakly associated with worse hospital ranks for the Lown Institute’s inclusivity (partial τb = 0.145, 99.9% CI [0.100, 0.190]) and community benefit metrics (partial τb = 0.181, 99.9% CI [0.136, 0.226]). Ratings were also inversely associated with inclusivity subscores and Medicaid revenue share.
Conclusion
Higher CMS star ratings demonstrated weak inverse associations with hospital-level measures of community commitment related to service to and support for vulnerable communities. These findings suggest current CMS star ratings may incompletely account for the social risk profile of the populations that hospitals serve, although the modest magnitude of the associations warrants cautious interpretation. To ensure that quality ratings accurately reflect quality of care, policymakers may consider enhancing adjustment for the social risk factors present in the communities that hospitals serve.

We previously validated and implemented criteria for auditing anaesthesiologists with intraoperative transfusion based on low median blood loss of the surgical procedure or absence of anaemia before transfusion. However, obstetrical cases were excluded during implementation, as the peripartum blood management protocol does not include haemoglobin determinations, matching American College of Obstetricians and Gynaecologists recommendations. For non-obstetrical surgery, intraoperative transfusion is associated with an increased probability of postpartum transfusion. Because of the obstetrical transfusion approach, we hypothesized the opposite relationship between intrapartum and postpartum transfusion.
The retrospective cohort study included all 30 160 patients who delivered at the University of Iowa January 2013 through March 2025.
Any RBC administration during anaesthesia care reduced the odds of later transfusion (odds ratio 0.14, 99% confidence interval (CI) 0.11%-0.18%). Single-unit RBC administration during anaesthesia reduced such odds (0.09, 99% CI 0.06%-0.11%), as did multiple-unit transfusion (0.18, 99% CI 0.13%-0.24%). McNemar tests had Bonferroni-adjusted p-values <0.0001. While antepartum anaemia (haemoglobin <11 g/dL) increased the probability of transfusion by 7.41% (standard error 0.43%) outside of anaesthesia care, the RBC transfusion decision during anaesthesia care was less influenced by anaemia, 1.52% (0.22%), p < 0.0001. Many (59%, 99% CI 50%-69%) RBC units started during anaesthesia care were administered to patients who were not anaemic (haemoglobin ≥11 g/dL) at admission. Most patients with single-unit RBC transfusion and blood loss <2500 mL had stable haemodynamics.
Unlike several categories of non-obstetrical procedures, RBC transfusion during anaesthesia care for delivery was associated with a reduced probability of postpartum RBC transfusion. A reasonable approach for blood bank auditing of anaesthesiologists' obstetric RBC transfusion decision-making would be to review cases when RBC were administered, there was blood loss <2500 mL, no subsequent transfusion, and discharge haemoglobin ≥9 g/dL.