Comparing Anesthesia and Surgery Controlled Time for Primary Total Knee and Hip Arthroplasty Between an Academic Medical Center and a Community Hospital: Retrospective Cohort Study.

BACKGROUND: Osteoarthritis is a significant cause of disability, resulting in increased joint replacement surgeries and health care costs. Establishing benchmarks that more accurately predict surgical duration could help to decrease costs, maximize efficiency, and improve patient experience. We compared the anesthesia-controlled time (ACT) and surgery-controlled time (SCT) of primary total knee (TKA) and total hip arthroplasties (THA) between an academic medical center (AMC) and a community hospital (CH) for 2 orthopedic surgeons. OBJECTIVE: This study aims to validate and compare benchmarking times for ACT and SCT in a single patient population at both an AMC and a CH. METHODS: This retrospective 2-center observational cohort study was conducted at the University of Colorado Hospital (AMC) and UCHealth Broomfield Hospital (CH). Cases with current procedural terminology codes for THA and TKA between January 1, 2019, and December 31, 2020, were assessed. Cases with missing data were excluded. The primary outcomes were ACT and SCT. Primary outcomes were tested for association with covariates of interest. The primary covariate of interest was the location of the procedure (CH vs AMC); secondary covariates of interest included the American Society of Anesthesiologists (ASA) classification and anesthetic type. Linear regression models were used to assess the relationships. RESULTS: Two surgeons performed 1256 cases at the AMC and CH. A total of 10 THA cases and 12 TKA cases were excluded due to missing data. After controlling for surgeon, the ACT was greater at the AMC for THA by 3.77 minutes and for TKA by 3.58 minutes (P<.001). SCT was greater at the AMC for THA by 11.14 minutes and for TKA by 14.04 minutes (P<.001). ASA III/IV classification increased ACT for THA by 3.76 minutes (P<.001) and increased SCT for THA by 6.33 minutes after controlling for surgeon and location (P=.008). General anesthesia use was higher at the AMC for both THA (29.2% vs 7.3%) and TKA (23.8% vs 4.2%). No statistically significant association was observed between either ACT or SCT and anesthetic type (neuraxial or general) after adjusting for surgeon and location (all P>.05). CONCLUSIONS: We observed lower ACT and SCT at the CH for both TKA and THA after controlling for the surgeon of record and ASA classification. These findings underscore the efficiency advantages of performing primary joint replacements at the CH, showcasing an average reduction of 16 minutes in SCT and 4 minutes in ACT per case. Overall, establishing more accurate benchmarks to improve the prediction of surgical duration for THA and TKA in different perioperative environments can increase the reliability of surgical duration predictions and optimize scheduling. Future studies with study populations at multiple community hospitals and academic medical centers are needed before extrapolating these findings.

New frontiers in intraoperative neurophysiologic monitoring: a narrative review.

Background and Objective: Neurological insults during surgery arise from anatomic and/or physiologic perturbations. Intraoperative neurophysiologic monitoring (IONM) fills a critical role of ensuring that any neurological insults during certain surgical procedures are caught in real-time to prevent patient harm. IONM provides immediate feedback to the surgeon and anesthesiologist about the need for an intervention to prevent a neurologic deficit postoperatively. As important as it seems to have IONM available to any patient having surgery where a neurological injury is possible, the truth is that IONM is unavailable to large swaths of people around the world. This review is intended to bring attention to all of the ways IONM is critically important for a variety of surgeries and highlight the barriers preventing most patients around the world from benefiting from the technology. Expansion of IONM to benefit patients from all over the world is the new frontier. Methods: We searched all English language original papers and reviews using Embase and MEDLINE/PubMed databases published from 1995 to 2022. Different combinations of the following search terms were used: intraoperative neuromonitoring, neurosurgery, low-income countries, cost, safety, and efficacy. Key Content and Findings: We describe common IONM modalities used during surgery as well as explore barriers to implementation of IONM in resource-limited regions. Additionally, we describe ongoing efforts to establish IONM capabilities in new locations around the world. Conclusions: In this paper, we performed a review of the literature on IONM with an emphasis on the basic understanding of clinical applications and the barriers for expansion into resource-limited settings. Finally, we provide our interpretation of "new frontiers" in IONM quite literally facilitating access to the tools and education so a hospital in Sub-Saharan Africa can incorporate IONM for their high-risk surgeries.

Airway and Hemodynamic Considerations for the Anesthetic Management of an Intraluminal Tracheal Plasmacytoma.

Central airway obstruction due to tracheal tumors presents unique challenges to the anesthesiologist. We present the case of a 44-year-old male taken to the OR for biopsy and resection of an undiagnosed tracheal mass. Intraoperative management was complicated by bleeding and significant hemodynamic instability, necessitating rapid surgical and anesthetic intervention. This ultimately led to abortion of surgical resection. Pathologic examination revealed a primary tracheal plasmacytoma, a rare type of tracheal tumor. Here, we describe anesthetic and hemodynamic considerations for a tracheal plasmacytoma. We discuss the approach to airway management in variable intrathoracic tracheal obstruction and the unpredictability of tracheal tumors.

Benchmarking of Anesthesia and Surgical Control Times by Current Procedural Terminology (CPT®) Codes.

Over half of hospital revenue results from perioperative patient care, thus emphasizing the importance of efficient resource utilization within a hospital's suite of operating rooms (ORs). Predicting surgical case duration, including Anesthesia-controlled time (ACT) and Surgical-controlled time (SCT) has been significantly detailed throughout the literature as a means to help manage and predict OR scheduling. However, this information has previously been divided by surgical specialty, and only limited benchmarking data regarding ACT and SCT exists. We hypothesized that advancing the granularity of the ACT and SCT from surgical specialty to specific Current Procedural Terminology (CPT®) codes will produce data that is more accurate, less variable, and therefore more useful for OR schedule modeling and management. This single center study was conducted using times from surgeries performed at the University of Colorado Hospital (UCH) between September 2018 - September 2019. Individual cases were categorized by surgical specialty based on the specialty of the primary attending surgeon and CPT codes were compiled from billing data. Times were calculated as defined by the American Association of Clinical Directors. I2 values were calculated to assess heterogeneity of mean ACT and SCT times while Levene's test was utilized to assess heterogeneity of ACT and SCT variances. Statistical analyses for both ACT and SCT were calculated using JMP Statistical Discovery Software from SAS (Cary, NC) and R v3.6.3 (Vienna, Austria). All surgical cases (n = 87,537) performed at UCH from September 2018 to September 2019 were evaluated and 30,091 cases were included in the final analysis. All surgical subspecialties, with the exception of Podiatry, showed significant variability in ACT and SCT values between CPT codes within each surgical specialty. Furthermore, the variances of ACT and SCT values were also highly variable between CPT codes within each surgical specialty. Finally, benchmarking values of mean ACT and SCT with corresponding standard deviations are provided. Because each mean ACT and SCT value varies significantly between different CPT codes within a surgical specialty, using this granularity of data will likely enable improved accuracy in surgical schedule modeling compared to using mean ACT and SCT values for each surgical specialty as a whole. Furthermore, because there was significant variability of ACT and SCT variances between CPT codes, incorporating variance into surgical schedule modeling may also improve accuracy. Future investigations should include real-time simulations, logistical modeling, and labor utilization analyses as well as validation of benchmarking times in private practice settings.