Using Bibliometric Data to Define and Understand Publishing Network Equity in Anesthesiology.

BACKGROUND: Anesthesiology departments and professional organizations increasingly recognize the need to embrace diverse membership to effectively care for patients, to educate our trainees, and to contribute to innovative research. 1 Bibliometric analysis uses citation data to determine the patterns of interrelatedness within a scientific community. Social network analysis examines these patterns to elucidate the network's functional properties. Using these methodologies, an analysis of contemporary scholarly work was undertaken to outline network structure and function, with particular focus on the equity of node and graph-level connectivity patterns. METHODS: Using the Web of Science, this study examines bibliographic data from 6 anesthesiology-specific journals between January 1, 2017, and August 26, 2022. The final data represent 4453 articles, 19,916 independent authors, and 4436 institutions. Analysis of coauthorship was performed using R libraries software. Collaboration patterns were assessed at the node and graph level to analyze patterns of coauthorship. Influential authors and institutions were identified using centrality metrics; author influence was also cataloged by the number of publications and highly cited papers. Independent assessors reviewed influential author photographs to classify race and gender. The Gini coefficient was applied to examine dispersion of influence across nodes. Pearson correlations were used to investigate the relationship between centrality metrics, number of publications, and National Institutes of Health (NIH) funding. RESULTS: The modularity of the author network is significantly higher than would be predicted by chance (0.886 vs random network mean 0.340, P < .01), signifying strong community formation. The Gini coefficient indicates inequity across both author and institution centrality metrics, representing moderate to high disparity in node influence. Identifying the top 30 authors by centrality metrics, number of published and highly cited papers, 79.0% were categorized as male; 68.1% of authors were classified as White (non-Latino) and 24.6% Asian. CONCLUSIONS: The highly modular network structure indicates dense author communities. Extracommunity cooperation is limited, previously demonstrated to negatively impact novel scientific work. 2 , 3 Inequitable node influence is seen at both author and institution level, notably an imbalance of information transfer and disparity in connectivity patterns. There is an association between network influence, article publication (authors), and NIH funding (institutions). Female and minority authors are inequitably represented among the most influential authors. This baseline bibliometric analysis provides an opportunity to direct future network connections to more inclusively share information and integrate diverse perspectives, properties associated with increased academic productivity. 3 , 4.

Rebooting the Electronic Health Record.

Justifications for the widespread adoption and integration of an electronic health record (EHR) have long leaned on the purported benefits of the technology. However, the performance of the EHR has been underwhelming relative to the promises of immediate access to relevant patient information, clinical decision supports, computerized ordering, and transferable patient data. In this narrative review, we provide an overview of the historical problems and limitations of the EHR, detail the core principles that define agile processes that may overcome the barriers faced by the current EHR, and re-imagine what an integrated, seamless EHR that serves its users and patients might look like. Moving forward, the EHR should be redesigned using a middle-out framework and empowering dual-type champions to maintain the sustainable diffusion of future innovations.

Critical Information from High Fidelity Arterial and Venous Pressure Waveforms During Anesthesia and Hemorrhage.

PURPOSE: Peripheral venous pressure (PVP) waveform analysis is a novel, minimally invasive, and inexpensive method of measuring intravascular volume changes. A porcine cohort was studied to determine how venous and arterial pressure waveforms change due to inhaled and infused anesthetics and acute hemorrhage. METHODS: Venous and arterial pressure waveforms were continuously collected, while each pig was under general anesthesia, by inserting Millar catheters into a neighboring peripheral artery and vein. The anesthetic was varied from inhaled to infused, then the pig underwent a controlled hemorrhage. Pearson correlation coefficients between the power of the venous and arterial pressure waveforms at each pig's heart rate frequency were calculated for each variation in the anesthetic, as well as before and after hemorrhage. An analysis of variance (ANOVA) test was computed to determine the significance in changes of the venous pressure waveform means caused by each variation. RESULTS: The Pearson correlation coefficients between venous and arterial waveforms decreased as anesthetic dosage increased. In an opposing fashion, the correlation coefficients increased as hemorrhage occurred. CONCLUSION: Anesthetics and hemorrhage alter venous pressure waveforms in distinctly different ways, making it critical for researchers and clinicians to consider these confounding variables when utilizing pressure waveforms. Further work needs to be done to determine how best to integrate PVP waveforms into clinical decision-making.

Development and Evaluation of a Risk-Adjusted Measure of Intraoperative Hypotension in Patients Having Nonemergent, Noncardiac Surgery.

BACKGROUND: Intraoperative hypotension is common and associated with organ injury and death, although randomized data showing a causal relationship remain sparse. A risk-adjusted measure of intraoperative hypotension may therefore contribute to quality improvement efforts. METHODS: The measure we developed defines hypotension as a mean arterial pressure <65 mm Hg sustained for at least 15 cumulative minutes. Comparisons are based on whether clinicians have more or fewer cases of hypotension than expected over 12 months, given their patient mix. The measure was developed and evaluated with data from 225,389 surgeries in 5 hospitals. We assessed discrimination and calibration of the risk adjustment model, then calculated the distribution of clinician-level measure scores, and finally estimated the signal-to-noise reliability and predictive validity of the measure. RESULTS: The risk adjustment model showed acceptable calibration and discrimination (area under the curve was 0.72 and 0.73 in different validation samples). Clinician-level, risk-adjusted scores varied widely, and 36% of clinicians had significantly more cases of intraoperative hypotension than predicted. Clinician-level score distributions differed across hospitals, indicating substantial hospital-level variation. The mean signal-to-noise reliability estimate was 0.87 among all clinicians and 0.94 among clinicians with >30 cases during the 12-month measurement period. Kidney injury and in-hospital mortality were most common in patients whose anesthesia providers had worse scores. However, a sensitivity analysis in 1 hospital showed that score distributions differed markedly between anesthesiology fellows and attending anesthesiologists or certified registered nurse anesthetists; score distributions also varied as a function of the fraction of cases that were inpatients. CONCLUSIONS: Intraoperative hypotension was common and was associated with acute kidney injury and in-hospital mortality. There were substantial variations in clinician-level scores, and the measure score distribution suggests that there may be opportunity to reduce hypotension which may improve patient safety and outcomes. However, sensitivity analyses suggest that some portion of the variation results from limitations of risk adjustment. Future versions of the measure should risk adjust for important patient and procedural factors including comorbidities and surgical complexity, although this will require more consistent structured data capture in anesthesia information management systems. Including structured data on additional risk factors may improve hypotension risk prediction which is integral to the measure's validity.

Interview Data Highlight Importance of "Same-State" on Anesthesiology Residency Match.

BACKGROUND: The US residency application, interview, and match processes are costly and time-intensive. We sought to quantify the importance of an applicant being from the same-state as a residency program in terms of how this impacted the number of interviews needed to match. METHODS: We examined data from interview scheduling software used by 32 programs located in 31 US states and 1300 applicants for the US anesthesiology recruitment cycles from 2015 to 2018. Interviewee data (distance from program, region, numbers of interviews, and program at which interview occurred) were analyzed to quantify the effect of the interviewee being from the same state as the residency program on the odds of matching to that program. Other variables of interest (medical school, current address, US Medical Licensing Exam [USMLE] Step 1 and 2 clinical knowledge [CK] scores, Alpha Omega Alpha [AOA] status, medical school ranking) were also examined as controls. Confidence intervals (CI) were calculated for the ratios of odds ratios. RESULTS: An interviewee living in the same state as the interviewing program could have 5.42 fewer total interviews (97.5% CI, 3.02-7.81) while having the same odds of matching. The same state effect had an equivalent value as an approximately 4.14 USMLE points-difference from the program's mean (97.5% CI was 2.34-5.94 USMLE points). Addition of whether the interviewee belonged to an affiliated medical school did not significantly improve the model; same-state remained significant (P < .0001) while affiliated medical school was not (P = .40). CONCLUSIONS: Our analysis of anesthesiology residency recruitment using previously unstudied interview data shows that same-state locality is a viable predictor of residency matching and should be strongly considered when evaluating whether to interview an applicant.

Overlapping Surgery: A Case Study in Operating Room Throughput and Efficiency.

A keystone of operating room (OR) management is proper OR allocation to optimize access, safety, efficiency, and throughput. Access is important to surgeons, and overlapping surgery may increase patient access to surgeons with specialized skill sets and facilitate the training of medical students, residents, and fellows. Overlapping surgery is commonly performed in academic medical centers, although recent public scrutiny has raised debate about its safety, necessitating monitoring. This article introduces a system to monitor overlapping surgery, providing a surgeon-specific Key Performance Indicator, and discusses overlapping surgery as an approach toward OR management goals of efficiency and throughput.

Analysis to Establish Differences in Efficiency Metrics Between Operating Room and Non-Operating Room Anesthesia Cases.

While a number of studies have examined efficiency metrics in the operating rooms (ORs), there are few studies addressing non-operating room anesthesia (NORA) metrics. The standards established in the realm of OR studies may not apply to ongoing investigations of NORA efficiency. We hypothesize that there are significant differences in these commonly used metrics. Using retrospective data from a single tertiary care hospital in the 2015 calendar year, we measured turnover times, cancellation rates, first case start delays, and scheduling error (actual time minus scheduled time) for the OR and NORA settings. On average, TOTs for NORA cases were approximately 50% shorter than OR cases (16.21 min vs. 37.18 min), but had a larger variation (11.02 min vs. 8.12 min). NORA cases were 64% as likely to be cancelled compared to OR cases. In contrast, NORA cases had an average first case start delay that was two times greater than that of OR cases (24.45 min vs. 10.58 min), along with over double the standard deviation (11.97 min vs. 5.90 min). Case times for NORA settings tended to be overestimated (-4.07 min versus -2.12 min), but showed less variation (8.61 min vs. 17.92 min). In short, there are significant differences in common efficiency metrics between OR and NORA cases. Future studies should elucidate and validate appropriate efficiency benchmarks for the NORA setting.

Operating Room Management at the Edge of Order and Chaos.

The operating room (OR) management literature tends to view management problems as having finite solutions and assumes that equilibrium exists in the intricate encounters that occur every day. In this article, we review complexity theory and assess its applicability to the strategic, tactical, and operational issues facing OR managers. By building on complexity theory and its assumptions, we also show that as complex systems, ORs resemble high-reliability organizations more than they resemble ultra-safe organizations. This distinction and the limitations of the current, linear modeling may have potential implications for the future of OR management research and practice. Opening the door to complexity, understanding the underpinnings of high-reliability organizations, and admitting that OR systems are complex adaptive systems, will lead to self-governing, transparent processes that envision the OR as a living, growing, sustainable human endeavor.

The July Spike in Operating Room Management: Reality or Perception?

Background Some research has found increased incidence of medical errors in teaching hospitals at the beginning of the academic year and have termed this the "July Phenomenon." Objective Our primary hypothesis was that the "July Phenomenon" for anesthesiology and surgical residents might manifest itself as operational inefficiency, measured by monthly total operating room (OR) minutes. Secondary measures were monthly elective overutilized minutes (OR workload minus OR allocated time, after 5:30 pm at our institution), 80th percentile number of ORs running at 7:00 pm, and mean last room end time. Methods Data were collected retrospectively from a 525-bed academic tertiary care hospital from January 2010 to September 2014 and were deconstructed to assess for a seasonal component using local regression (Loess). Variable month length was addressed by transforming the monthly totals to average daily minutes and overutilized minutes. Linear regression quantified significance for all primary and secondary analyses. Results In the regressions, monthly average minutes showed no significant difference in July (P = .65) compared to the baseline month of April. There were no significant differences for any month for overutilized minutes or 80th percentile number ORs working at 7:00 pm. Only August was significant (P = .005) for mean last room end time. Conclusions Data from a single institution study did not show a "July Phenomenon" in the number of operating minutes, overutilized minutes, or the number of ORs working late in July.

The Heart of the Matter: Increasing Quality and Charge Capture from Intraoperative Transesophageal Echocardiography.

Although transesophageal echocardiography is routinely performed at our institution, there is no easy way to document the procedure in the electronic medical record and generate a bill compliant with reimbursement requirements. We present the results of a quality improvement project that used agile development methodology to incorporate intraoperative transesophageal echocardiography into the electronic medical record. We discuss improvements in the quality of clinical documentation, technical workflow challenges overcome, and cost and time to return on investment. Billing was increased from an average of 36% to 84.6% when compared with the same time period in the previous year. The expected recoupment of investment for this project is just 18 weeks.

Bariatric surgery operating room time--size matters.

BACKGROUND: The goal of this study was to document the relationship between BMI and the components of bariatric surgical operating room (OR) time. METHODS: The Stanford Translational Research Integrated Database Environment identified all patients who underwent laparoscopic Roux-en-Y gastric bypass procedures at Stanford University Medical Center between May 2008 and November 2013. The 434 patients were divided into 3 groups: group 1 (n = 213) BMI ≥35 to <45 kg/m(2), group 2 (n = 188) BMI ≥45.0 to <60 kg/m(2), and group 3 (n = 33) BMI ≥60 kg/m(2). The primary variable measured was total operating room time, defined as beginning when the patient entered the OR until the moment the patient physically left the OR. Secondary variables were anesthetic induction time, nursing preparation time, operation time, time for emergence from anesthesia, and total length of hospital stay. RESULTS: Increasing BMI was associated with increased total OR time (group 1 = 202 min, group 2 = 215 min, group 3 = 235 min), mainly due to longer operation time (group 1 = 147 min, group 2 = 154 min, group 3 = 163 min). Anesthetic induction (group 1 = 17 min, group 2 = 18 min, group 3 = 23 min) and emergence times (group 1 = 12 min, group 2 = 12 min, group 3 = 22 min) were also significantly longer in the largest patients. CONCLUSIONS: Operating room schedules and plans for resource utilization should recognize that the same bariatric procedure will require more time for patients with BMI >60 kg/m(2) than for smaller bariatric patients.