Modelling the economic constraints and consequences of anaesthesia associate expansion in the UK National Health Service: a narrative review.

Shortages in the physician anaesthesia workforce have led to proposals to introduce new staff groups, notably in the UK National Health Service (NHS) Anaesthesia Associates (AAs) who have shorter training periods than doctors and could potentially contribute to workflow efficiencies in several ways. We analysed the economic viability of the most efficient staffing model, previously endorsed by both the UK Royal College of Anaesthetists and the Association of Anaesthetists, wherein one physician supervises two AAs across two operating lists (1:2 model). For this model to be economically rational (something which neither national organisation considered), the employment cost of the two AAs should be equal to or less than that of a single supervisor physician (i.e. AAs should be paid <50% of the supervisor's salary). As the supervisor can be an autonomous specialty and specialist (SAS) doctor, this sets the economically viable AA salary envelope at less than £40,000 per year. However, we report that actual advertised AA salaries greatly exceed this, with even student AAs paid up to £48,472. Economically, one way to justify such salaries is for AAs to become autonomous such that they eventually replace SAS doctors at a lower cost. We discuss some other options that might increase AA productivity to justify these salaries (e.g. ≥1:3 staffing ratios), but the medico-political consequences of each of them are also profound. Alternatively, the AA programme should be terminated as economically nonviable. These results have implications for any country seeking to introduce new models of working in anaesthesia.

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.

Patient selection for nonoperating room anesthesia.

PURPOSE OF REVIEW: Given the rapid growth of nonoperating room anesthesia (NORA) in recent years, it is essential to review its unique challenges as well as strategies for patient selection and care optimization. RECENT FINDINGS: Recent investigations have uncovered an increasing prevalence of older and higher ASA physical status patients in NORA settings. Although closed claim data regarding patient injury demonstrate a lower proportion of NORA cases resulting in a claim than traditional operating room cases, NORA cases have an increased risk of claim for death. Challenges within NORA include site-specific differences, limitations in ergonomic design, and increased stress among anesthesia providers. Several authors have thus proposed strategies focusing on standardizing processes, site-specific protocols, and ergonomic improvements to mitigate risks. SUMMARY: Considering the unique challenges of NORA settings, meticulous patient selection, risk stratification, and preoperative optimization are crucial. Embracing data-driven strategies and leveraging technological innovations (such as artificial intelligence) is imperative to refine quality control methods in targeted areas. Collaborative efforts led by anesthesia providers will ensure personalized, well tolerated, and improved patient outcomes across all phases of NORA care.

Multivariable Cost Frontiers-Qualitative Financial Analyses Using Operational Metrics From the Implementation of a Surgery Fellowship.

OBJECTIVE: We expand the application of cost frontiers and introduce a novel approach using qualitative multivariable financial analyses. SUMMARY BACKGROUND DATA: With the creation of a 5 + 2-year fellowship program in July 2016, the Division of Vascular Surgery at the University of Vermont Medical Center altered the underlying operational structure of its inpatient services. METHOD: Using WiseOR (Palo Alto, CA), a web-based OR management data system, we extracted the operating room metrics before and after August 1, 2016 service for each 4-week period spanning from September 2015 to July 2017. The cost per minute modeled after Childers et al's inpatient OR cost guidelines was multiplied by the after-hours utilization to determine variable cost. Zones with corresponding cutoffs were used to graphically represent cost efficiency trends. RESULTS: Caseload/FTE for attending surgeons increased from 11.54 cases per month to 13.02 cases per month ( P = 0.0771). Monthly variable costs/FTE increased from $540.2 to $1873 ( P = 0.0138). Monthly revenue/FTE increased from $61,505 to $70,277 ( P = 0.2639). Adjusted monthly reve-nue/FTE increased from $60,965 to $68,403 ( P = 0.3374). Average monthly percent of adjusted revenue/FTE lost to variable costs increased from 0.85% to 2.77% ( P = 0.0078). Adjusted monthly revenue/case/FTE remained the same from $5309 to $5319 ( P = 0.9889). CONCLUSION: In summary, we demonstrate that multivariable cost (or performance) frontiers can track a net increase in profitability associated with fellowship implementation despite diminishing returns at higher caseloads.

A machine learning approach to predicting early and late postoperative reintubation.

Accurate estimation of surgical risks is important for informing the process of shared decision making and informed consent. Postoperative reintubation (POR) is a severe complication that is associated with postoperative morbidity. Previous studies have divided POR into early POR (within 72 h of surgery) and late POR (within 30 days of surgery). Using data provided by American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP), machine learning classification models (logistic regression, random forest classification, and gradient boosting classification) were utilized to develop scoring systems for the prediction of combined, early, and late POR. The risk factors included in each scoring system were narrowed down from a set of 37 pre and perioperative factors. The scoring systems developed from the logistic regression models demonstrated strong performance in terms of both accuracy and discrimination across the different POR outcomes (Average Brier score, 0.172; Average c-statistic, 0.852). These results were only marginally worse than prediction using the full set of risk variables (Average Brier score, 0.145; Average c-statistic, 0.870). While more work needs to be done to identify clinically relevant differences between the early and late POR outcomes, the scoring systems provided here can be used by surgeons and patients to improve the quality of care overall.

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.

A Mobile App for the Precise Measurement of Healthcare Provider Activity Times to Support Time-Driven Activity Based Costing Studies.

The duration of activities performed by healthcare providers are pivotal to Time-Driven Activity-Based Costing (TDABC) models. This study examines the use of a smartphone mobile application technology to record activity times. This study validates the accuracy of activity times recorded on a smartphone mobile application, dTool, compared to observed length of time recordings in the operating room. For analysis, we performed two one-sided tests for the measurements "Case Start" and "Case End". Equivalence bounds were specified in terms of raw mean difference of 1 min (upper) and -1 min (lower). The total number of comparisons in the observer protocol was 72 (32 "case start" patient comparisons and 40 "case end" patient comparisons measured over 45 individual OR cases). Given equivalence bounds of -1.000 and 1.000 (on a raw scale) and an alpha of 0.05, both equivalence tests were significant: provider and third-party observer protocol presented t(40) = 3.228 and p = < 0.001; observer timing protocol presented t(68.68) = 56.762, p = < 0.001. Conclusions: With this novel smartphone technology, a healthcare provider can reliably self-record activity LoT using dTool while providing patient care. Future TDABC studies incorporating this technology will reduce the potential operational barriers to implementation.

Monitoring Perioperative Services Using 3D Multi-Objective Performance Frontiers.

The Acute Care Surgery model has been widely adopted by hospitals across the United States, with Acute Care Surgery services managing Emergency General Surgery patients that were previously being treated by General Surgery. In this analysis, we evaluate the impact of an Acute Care Surgery service model on General Surgery at the University of Vermont Medical Center using three metrics: under-utilized time, spillover time, and a financial ratio of work Relative Value Units over clinical Full Time Equivalents. These metrics are evaluated and used to identify three-dimensional Pareto optimality of General Surgery prior to and after the October 2015 tactical allocation to the Acute Care Surgery model. Our analysis was further substantiated using a Markov Chain Monte Carlo model for Bayesian Inference. We applied multi-objective Pareto and Bayesian breakpoint analysis to three operating room metrics to assess the impact of new operating room management decisions. In the two-dimensional space of Fig. 2, panel a), the post-tactical allocation front lies closer to the origin representing more optimal solutions for productivity and under-utilized time. The post-tactical allocation front is also closer to the origin for productivity and spillover time as shown in the two-dimensional space of Fig. 2, panel b). The results of the three-dimensional multi-objective analysis of Fig. 3 illustrate that the GS post-tactical allocation Pareto-surface is contained within a much smaller volume of space than the GS pre-tactical allocation Pareto-surface. The post-tactical allocation Pareto-surface is slightly lower along the z-axis, representing lower productivity than the pre-tactical allocation surface. This methodology might contribute to the external benchmarking and monitoring of perioperative services by visualizing the operational implications following tactical decisions in operating room management.

The Power Law in Operating Room Management.

The Acute Care Surgery model has been implemented by many hospitals in the United States. As complex adaptive systems, healthcare systems are composed of many interacting elements that respond to intrinsic and extrinsic inputs. Systems level analysis may reveal the underlying organizational structure of tactical block allocations like the Acute Care Surgery model. The purpose of this study is to demonstrate one method to identify a key characteristic of complex adaptive systems in the perioperative services. Start and end times for all surgeries performed at the University of Vermont Medical Center OR1 were extracted for two years prior to the transition to an Acute Care Surgery service and two years following the transition. Histograms were plotted for the inter-event times calculated from the difference between surgical cases. A power law distribution was fit to the post-transition histogram. The Kolmogorov-Smirnov test for goodness-of-fit at 95% level of significance shows the histogram plotted from post-transition inter-event times follows a power law distribution (K-S = 0.088, p = 0.068), indicating a Complex Adaptive System. Our analysis demonstrates that the strategic decision to create an Acute Care Surgery service has direct implications on tactical and operational processes in the perioperative services. Elements of complex adaptive systems can be represented by a power law distributions and similar methods may be applied to identify other processes that operate as complex adaptive systems in perioperative care. To make sustained improvements in the perioperative services, focus on manufacturing-based interventions such as Lean Six Sigma should instead be shifted towards the complex interventions that modify system-specific behaviors described by complex adaptive system principles when power law relationships are present.

An update on pediatric sedation techniques in nonoperating room locations.

PURPOSE OF REVIEW: To review advancements in care for pediatric patients in nonoperating room settings. RECENT FINDINGS: Advances in patient monitoring technology, utilization of Child Life specialists, and alternative staffing models are helping anesthesia providers meet the rising demand for coverage of pediatric nonoperating room anesthesia (NORA) cases. The Wake Up Safe and Pediatric Sedation Research Consortium registries are exploring outcome measures regarding the safety of pediatric anesthesia in off-site locations and have reported an increased risk for severe respiratory and cardiac adverse events when compared to OR anesthesia sites. Additionally, malpractice claims for NORA have a higher proportion of claims for death than claims in operating rooms. SUMMARY: Pediatric NORA requires thorough preparation, flexibility, and vigilance to provide safe anesthesia care to children in remote locations. Emerging techniques to reduce anesthetic exposure, improve monitoring, and alternative staffing models are expanding the boundaries of pediatric NORA to provide a safer, more satisfying experience for diagnostic and interventional procedures.

Optimizing the use of point of care testing devices for screening patients.

Point of Care Testing (POCT) devices are regularly used to improve clinical workflows in the hospital setting despite generally having inferior performance when compared to standardized laboratory analyzers. We describe a method to improve the efficacy of using a POCT device as a screening test when the laboratory values occur over a continuum and applied this methodology to the process of International Normalized Ratios (INR) screening on day of surgery. Following IRB approval, laboratory INR values on the day of surgery were extracted from the University of Vermont Medical Center operating room's electronic health record. Two separate theoretical POCT device values were simulated from the performance characterized by two prior publications (Jacobson and Hur). The sensitivities and specificities of the two theoretical devices were calculated over a range of values, in order detect an INR value greater or equal than 1.5 and 1.8. Subsequently, the percentage of the population with an INR value over each threshold was also calculated. Laboratory data from March 2008 to December 2016 were collected, and 9320 discrete INR values were compiled ranging from 0.8 to > 20. Two POCT devices were simulated using that dataset. The sensitivities and specificities over a range of values were determined, and the optimal cutoff values were identified for each device separately. Calculating the sensitivities and specificities over a range of values can optimize the clinical efficacy of a POCT device. By optimizing the use of POCT devices, hospitals may be able to improve clinical processes and reduce costs.

Water Pollution and Environmental Concerns in Anesthesiology.

Medications administered by anesthesia health care providers and subsequently excreted into the water supply system have the potential to affect ecological systems. Presently, there is a lack of literature examining which medications or metabolites enter the waste stream. Further, their potential environmental impacts are often unknown or simply not considered as an externality of medical practice. Recent work examining the practice of anesthesiology has explored the solid waste stream, and the global warming potential of anesthetic gases, however the potential aquatic impacts remain unexplored. To address the potential for waterborne pollution and environmental toxicity, we extracted the total intravenous medications (by mass) administered by anesthesiologists in 2017 at The University of Vermont Medical Center (UVMMC), a mid-size regional Level 1 trauma center in Burlington, VT. The most commonly administered medications were: cefazolin, propofol, acetaminophen, sugammadex and lidocaine. To estimate the amount of each medication that entered the wastewater stream, we used published metabolism profiles to adjust from the total amount administered to the amount excreted unchanged or as prominent metabolites. For each medication we reviewed existing literature concerning their environmental fate and impacts in water. Due to the constraints of current knowledge, it is not possible to determine the exact fate and impacts of these drugs. Some medications, like propofol, have the potential for significant bioaccumulation and persistence. Others, such as lidocaine and acetaminophen, have short half-lives in the environment but their constant delivery and excretion result in pseudo-persistence. The current literature mostly assesses acute exposure at doses higher than could be expected in the environment on select species. While significant toxicities across a variety of species have been found repeatedly, chronic low dose exposures require further study for all the medications discussed. Finally, multi-drug impacts are likely to be more impactful than single-drug toxicities. While we cannot state definitive impacts, the pharmaceuticals most used in anesthesiology have a clear toxic potential and future studies should more closely examine the relative contribution of anesthesia to pharmaceutical pollution, as well as points of intervention for minimizing these unintended consequences of healthcare delivery.

OR Management and Metrics: How It All Fits Together for the Healthcare System.

Increased healthcare costs and diminishing returns have prompted healthcare administrators to address budget allocations to alleviate institutional costs. Current economic constraints, such as limited Medicaid and Medicare insurance payments, limit our patients' ability to receive urgent surgical interventions as well as access preventative diagnostic tools. Rather than downsizing the workforce, future sustainability must be derived upon effective cost structures supported by improved quality control measures and increased patient accessibility. Surgeries were performed during 29% of hospitalizations and comprised 48% of the $387 billion in healthcare expenditures in 2011. Further, surgical procedures managed to account for 40-70% of hospital revenues. Effective cost reduction begins at the source and in the case of hospital systems, the operating room (OR). Taking this into consideration, administrators evaluating future revenue streams should look to consider OR-based cost reduction measures as part of their first step approach. Improving OR efficiency through block time and staff optimization remain the premise of today's existing literature on OR management strategies.

Changing Anesthesia Block Allocations Improves Endoscopy Suite Efficiency.

Non-operating room anesthesia (NORA) has grown and continues to expand as a proportion of all anesthesia practice in the United States [1, 2]. While many management processes have been adapted for NORA from the traditional operating room, it is still unclear what scheduling paradigm will maximize efficiency of resource utilization in this arena. In this study, we investigate the impact of tactical a shift from a shared group to individual, provider-specific block allocations for available anesthesia time in an endoscopy suite for adult patients undergoing elective endoscopy procedures at an academic hospital. Using a retrospective and prospective analysis, we measured elective time-in-block; elective time out-of-block; under-utilized (opportunity and non-opportunity unused) time; over-utilized time; and case tardiness to determine operational efficiency and clinical productivity. Over the study period, the monthly caseload remained constant. Elective time in block increased by 156% (p < 0.0001) and elective time out of block decreased by 38% (p < 0.0001). Opportunity unused time decreased by 28% (p < 0.0001) and productivity increased by 51% (p < 0.0001). Neither over-utilized time nor case tardiness showed a significant change after the intervention. Despite the evidence base supporting traditional approaches to anesthesia block allocation involving group block allocation and non-sequential case scheduling, we have demonstrated an advantage to individual block allocation in a GI endoscopy setting. This sequential case scheduling highlights how tactical decisions in NORA environments may require a rethinking of many practices that anesthesiologists have brought with them from the traditional OR. Using these efficiency and productivity metrics, further adjustments to scheduling practices should be investigated, and connecting these metrics to other systems outcomes, such as financial productivity, is an important next step as NORA services expand into the future.

The Association of Anesthesia Clinical Directors (AACD) Glossary of Times Used for Scheduling and Monitoring of Diagnostic and Therapeutic Procedures.

The Glossary of Times Used for Scheduling and Monitoring of Diagnostic and Therapeutic Procedures also known as the Procedural Times Glossary (PTG) was originally developed with the support of the Association of Anesthesia Clinical Directors (AACD). The goal was to establish standardized terms to measure and assess the performance of operating room and procedural areas. By incorporating standardized concepts of efficiency and utilization, the PTG codified operating room metrics and facilitated benchmarking and quality improvement initiatives. In the last three decades, these concepts have also served as the basis for research in operating room management, including incorporating frameworks from diverse fields. The metrics in the PTG are divided into four categories: (1) Procedural Times; (2) Procedural and Scheduling Definitions and Time Periods; (3) Utilization and Efficiency Indices; and (4) Patient Categories. We describe each of the categories and corresponding metrics. The PTG provides the fundamental building blocks for managing operating and non-operating room suites. We hope that reintroducing these important time markers will help facilitate the reporting of standardized metrics.