Cancellation of Elective Surgery and Intensive Care Unit Capacity in New York State: A Retrospective Cohort Analysis.

BACKGROUND: In response to the coronavirus disease 2019 (COVID-19) pandemic, New York State ordered the suspension of all elective surgeries to increase intensive care unit (ICU) bed capacity. Yet the potential impact of suspending elective surgery on ICU bed capacity is unclear. METHODS: We retrospectively reviewed 5 years of New York State data on ICU usage. Descriptions of ICU utilization and mechanical ventilation were stratified by admission type (elective surgery, emergent/urgent/trauma surgery, and medical admissions) and by geographic location (New York metropolitan region versus the rest of New York State). Data are presented as absolute numbers and percentages and all adult and pediatric ICU patients were included. RESULTS: Overall, ICU admissions in New York State were seen in 10.1% of all hospitalizations (n = 1,232,986/n = 12,251,617) and remained stable over a 5-year period from 2011 to 2015. Among n = 1,232,986 ICU stays, sources of ICU admission included elective surgery (13.4%, n = 165,365), emergent/urgent admissions/trauma surgery (28.0%, n = 345,094), and medical admissions (58.6%, n = 722,527). Ventilator utilization was seen in 26.3% (n = 323,789/n = 1232,986) of all ICU patients of which 6.4% (n = 20,652), 32.8% (n = 106,186), and 60.8% (n = 196,951) was for patients from elective, emergent, and medical admissions, respectively. New York City holds the majority of ICU bed capacity (70.0%; n = 2496/n = 3566) in New York State. CONCLUSIONS: Patients undergoing elective surgery comprised a small fraction of ICU bed and mechanical ventilation use in New York State. Suspension of elective surgeries in response to the COVID-19 pandemic may thus have a minor impact on ICU capacity when compared to other sources of ICU admission such as emergent/urgent admissions/trauma surgery and medical admissions. More study is needed to better understand how best to maximize ICU capacity for pandemics requiring heavy use of critical care resources.

The Impact of a Real-Time Locating System within the Perioperative Environment on Physicians and Patients' Families.

BACKGROUND: Humber River Hospital has implemented a real-time location system (RTLS) within the operating room in order to provide real-time information about patients' status and manage the many components involved during the perioperative journey. OBJECTIVE: The aim of this study was to explore both physicians' and family members' perceptions of the functionality and efficiency of the RTLS within the perioperative environment. METHODS: Semi-structured interviews were conducted with physicians and patients' family members to elicit various perspectives regarding the use of RTLSs throughout the perioperative process. Interviews were recorded and transcribed to extract key themes. RESULTS: Three themes gleaned from physician interviews were system weaknesses, perceptions of potential benefit, and benefits to family members. Three themes uncovered from family member interviews included convenience, ameliorating anxiety, and reducing interruptions. CONCLUSION: Overall, physicians reported that the RTLS had potential to enhance workflow but that significant improvement regarding its implementation and use was needed to reach its full benefit. Family members were unanimous that it provides them with all the tracking information they desire.

Effect of a Cognitive Aid on Reducing Sugammadex Use and Associated Costs: A Time Series Analysis.

BACKGROUND: The authors observed increased pharmaceutical costs after the introduction of sugammadex in our institution. After a request to decrease sugammadex use, the authors implemented a cognitive aid to help choose between reversal agents. The purpose of this study was to determine if sugammadex use changed after cognitive aid implementation. The authors' hypothesis was that sugammadex use and associated costs would decrease. METHODS: A cognitive aid suggesting reversal agent doses based on train-of-four count was developed. It was included with each dispensed reversal agent set and in medication dispensing cabinet bins containing reversal agents. An interrupted time series analysis was performed using pharmaceutical invoices and anesthesia records. The primary outcome was the number of sugammadex administrations. Secondary outcomes included total pharmaceutical acquisition costs of neuromuscular blocking drugs and reversal agents, adverse respiratory events, emergence duration, and number of neuromuscular blocking drug administrations. RESULTS: Before cognitive aid implementation, the number of sugammadex administrations was increasing at a monthly rate of 20 per 1,000 general anesthetics (P < 0.001). Afterward, the monthly rate was 4 per 1,000 general anesthetics (P = 0.361). One month after cognitive aid implementation, the number of sugammadex administrations decreased by 281 per 1,000 general anesthetics (95% CI, 228 to 333, P < 0.001). In the final study month, there were 509 fewer sugammadex administrations than predicted per 1,000 general anesthetics (95% CI, 366 to 653; P < 0.0001), and total pharmaceutical acquisition costs per 1,000 general anesthetics were $11,947 less than predicted (95% CI, $4,043 to $19,851; P = 0.003). There was no significant change in adverse respiratory events, emergence duration, or administrations of rocuronium, vecuronium, or atracurium. In the final month, there were 75 more suxamethonium administrations than predicted per 1,000 general anesthetics (95% CI, 32 to 119; P = 0.0008). CONCLUSIONS: Cognitive aid implementation to choose between reversal agents was associated with a decrease in sugammadex use and acquisition costs.

Patient Survey of Referral From One Surgeon to Another to Reduce Maximum Waiting Time for Elective Surgery and Hours of Overutilized Operating Room Time.

BACKGROUND: Studies of shared (patient-provider) decision making for elective surgical care have examined both the decision whether to have surgery and patients' understanding of treatment options. We consider shared decision making applied to case scheduling, since implementation would reduce labor costs. METHODS: Study questions were presented in sequence of waiting times, starting with 4 workdays. "Assume the consultant surgeon (ie, the surgeon in charge) you met in clinic did not have time available to do your surgery within the next 4 workdays, but his/her colleague would have had time to do your surgery within the next 4 workdays. Would you have wanted to discuss with a member of the surgical team (eg, the scheduler or the surgeon) the availability of surgery with a different, equally qualified surgeon at Mayo Clinic who had time available within the next 4 workdays, on a date of your choosing?" There were 980 invited patients who underwent lung resection or cholecystectomy between 2011 and 2016; 135 respondents completed the study and 6 respondents dropped out after the study questions were displayed. RESULTS: The percentages of patients whose response to the study questions was "4 days" were 58.8% (40/68) among lung resection patients and 58.2% (39/67) among cholecystectomy patients. The 97.5% 2-sided confidence interval for the median maximum wait was 4 days to 4 days. Patients' choices for the waiting time sufficient to discuss having another surgeon perform the procedure did not differ between procedures (P = .91). Results were insensitive to patients' sex, age, travel time to hospital, or number of office visits before surgery (all P ≥ .20). CONCLUSIONS: Our results indicate that bringing up the option with the patient of changing surgeons when a colleague is available and has the operating room time to perform the procedure sooner is being respectful of most patients' individual preferences (ie, patient-centered).

Implications of Perioperative Team Setups for Operating Room Management Decisions.

BACKGROUND: Team performance has been studied extensively in the perioperative setting, but the managerial impact of interprofessional team performance remains unclear. We hypothesized that the interplay between anesthesiologists and surgeons would affect operating room turnaround times, and teams that worked together over time would become more efficient. METHODS: We analyzed 13,632 surgical cases at our hospital that involved 64 surgeons and 48 anesthesiologists. We detrended and adjusted the data for potential confounders including age, American Society of Anesthesiologists physical status, and surgical list (scheduled cases of specific surgical specialties). The surgical lists were categorized as ear, nose, and throat surgery; trauma surgery; general surgery; and gynecology. We assessed the relationship between turnaround times and assignment of different anesthesiologists to specific surgeons using a Monte Carlo simulation. RESULTS: We found significant differences in team performances among the different surgical lists but no team learning. We constructed managerial decision tables for the assignment of anesthesiologists to specific surgeons at our hospital. We defined a decision algorithm based on these tables. Our analysis indicated that had this algorithm been used in staffing the operating room for the surgical cases represented in our data, median turnaround times would have a reduction potential of 6.8% (95% confidence interval 6.3% to 7.1%). CONCLUSIONS: A surgeon is usually predefined for scheduled surgeries (surgical list). Allocation of the right anesthesiologist to a list and to a surgeon can affect the team performance; thus, this assignment has managerial implications regarding the operating room efficiency affecting turnaround times and thus potentially overutilized time of a list at our hospital.

Resident Physicians Improve Nontechnical Skills When on Operating Room Management and Leadership Rotation.

BACKGROUND: Anesthesiology residency primarily emphasizes the development of medical knowledge and technical skills. Yet, nontechnical skills (NTS) are also vital to successful clinical practice. Elements of NTS are communication, teamwork, situational awareness, and decision making. METHODS: The first 10 consecutive senior residents who chose to participate in this 2-week elective rotation of operating room (OR) management and leadership training were enrolled in this study, which spanned from March 2013 to March 2015. Each resident served as the anesthesiology officer of the day (AOD) and was tasked with coordinating OR assignments, managing care for 2 to 4 ORs, and being on call for the trauma OR; all residents were supervised by an attending AOD. Leadership and NTS techniques were taught via a standardized curriculum consisting of leadership and team training articles, crisis management text, and daily debriefings. Resident self-ratings and attending AOD and charge nurse raters used the Anaesthetists' Non-Technical Skills (ANTS) scoring system, which involved task management, situational awareness, teamwork, and decision making. For each of the 10 residents in their third year of clinical anesthesiology training (CA-3) who participated in this elective rotation, there were 14 items that required feedback from resident self-assessment and OR raters, including the daily attending AOD and charge nurse. Results for each of the items on the questionnaire were compared between the beginning and the end of the rotation with the Wilcoxon signed-rank test for matched samples. Comparisons were run separately for attending AOD and charge nurse assessments and resident self-assessments. Scaled rankings were analyzed for the Kendall coefficient of concordance (ω) for rater agreement with associated χ and P value. RESULTS: Common themes identified by the residents during debriefings were recurrence of challenging situations and the skills residents needed to instruct and manage clinical teams. For attending AOD and charge nurse assessments, resident performance of NTS improved from the beginning to the end of the rotation on 12 of the 14 NTS items (P < .05), whereas resident self-assessment improved on 3 NTS items (P < .05). Interrater reliability (across the charge nurse, resident, and AOD raters) ranged from ω = .36 to .61 at the beginning of the rotation and ω = .27 to .70 at the end of the rotation. CONCLUSIONS: This rotation allowed for teaching and resident assessment to occur in a way that facilitated resident education in several of the skills required to meet specific milestones. Resident physicians are able to foster NTS and build a framework for clinical leadership when completing a 2-week senior elective as an OR manager.

Comparison of minute distribution frequency for anesthesia start and end times from an anesthesia information management system and paper records.

Use of an anesthesia information management system (AIMS) has been reported to improve accuracy of recorded information. We tested the hypothesis that analyzing the distribution of times charted on paper and computerized records could reveal possible rounding errors, and that this effect could be modulated by differences in the user interface for documenting certain event times with an AIMS. We compared the frequency distribution of start and end times for anesthesia cases completed with paper records and an AIMS. Paper anesthesia records had significantly more times ending with "0" and "5" compared to those from the AIMS (p < 0.001). For case start times, AIMS still exhibited end-digit preference, with times whose last digits had significantly higher frequencies of "0" and "5" than other integers. This effect, however, was attenuated compared to that for paper anesthesia records. For case end times, the distribution of minutes recorded with AIMS was almost evenly distributed, unlike those from paper records that still showed significant end-digit preference. The accuracy of anesthesia case start times and case end times, as inferred by statistical analysis of the distribution of the times, is enhanced with the use of an AIMS. Furthermore, the differences in AIMS user interface for documenting case start and case end times likely affects the degree of end-digit preference, and likely accuracy, of those times.

Use of natural user interfaces for image navigation during laparoscopic surgery: initial experience.

BACKGROUND: Surgical environments require special aseptic conditions for direct interaction with the preoperative images. We aim to test the feasibility of using a set of gesture control sensors combined with voice control to interact in a sterile manner with preoperative information and an integrated operating room (OR) during laparoscopic surgery. MATERIAL AND METHODS: Two hepatectomies and two partial nephrectomies were performed by three experienced surgeons in a porcine model. The Kinect, Leap Motion, and MYO armband in combination with voice control were used as natural user interfaces (NUIs). After surgery, surgeons completed a questionnaire about their experience. RESULTS: Surgeons required <10 min training with each NUI. They stated that NUIs improved the access to preoperative patient information and kept them more focused on the surgical site. The Kinect system was reported as the most physically demanding NUI and the MYO armband in combination with voice commands as the most intuitive and accurate. The need to release one of the laparoscopic instruments in order to use the NUIs was identified as the main limitation. CONCLUSIONS: The presented NUIs are feasible to directly interact in a more intuitive and sterile manner with the preoperative images and the integrated OR functionalities during laparoscopic surgery.

[Digital technology in clinical surgery and rehabilitation]. / Tsifrovye tekhnologii v klinicheskoi khirurgii i reabilitatsii.

This article is devoted to a very actual and insufficiently imagine in the literature theme - innovation and digital technologies in clinical surgery and rehabilitation. AIM: To schow posibilities of modern digital and information technologies in clinical practice based on the experience of the Pirogov Center. MATERIAL AND METHODS: Analysis of experience in the application of innovative technologies, robotic surgery, intraoperative navigation computer, robotic systems in medical rehabilitation, integrated operating room, surgical video communication systems in service of those doing the Pirogov Center for the past 10 years. RESULTS: Shows the feasibility of the considered technologies in modern clinical practice clinics. CONCLUSION: The experience of the Pirogov Center indicates that the extensive use in clinical practice of modern health care facilities of the latest high-tech equipment in conjunction with the introduction of process automation and digital integrated technology management and medical-diagnostic activity is an essential reserve to increase the activity of providing specialized, including high-tech medical care, carrying out a variety of scientific and educational activities.

Use of simulation to assess a statistically driven surgical scheduling system.

BACKGROUND: To maximize operating room (OR) utilization, better estimates of case duration lengths are needed. We used computerized simulation to determine whether scheduling OR cases using a statistically driven system that incorporates patient and surgery-specific factors in the process of case duration prediction improves OR throughput and utilization. METHODS: We modeled surgical and anesthetic length of vascular surgical procedures as a function of patient and operative characteristics using a multivariate linear regression approach (Predictive Modeling System [PMS]). Mean historical operative time per surgeon (HMS) and mean anesthetic time were also calculated for each procedure type. A computerized simulation of scheduling in a single OR performing vascular operations was then created using either the PMS or the HMS. RESULTS: Compared to HMS, scheduling the operating room using the PMS increased throughput by a minimum of 15% (99.8% cumulative probability, P < 0.001). The PMS was slightly more likely to lead to overtime (mean 13% versus 11% of operative days during a calendar year, P < 0.001). However, the overtime lasted longer in the HMS group (mean 140 versus 95 min per day of overtime, P < 0.001). PMS was associated with lower OR underutilization rate (mean 23% versus 34% of operative days, P < 0.001) and less lengthy OR underutilization (mean 120 versus 193 min per day of underutilization, P < 0.001). CONCLUSIONS: This computerized simulation demonstrates that using the PMS for scheduling in a single operating room increases throughput and other measures of surgical efficiency.

Controlled Substance Reconciliation Accuracy Improvement Using Near Real-Time Drug Transaction Capture from Automated Dispensing Cabinets.

BACKGROUND: Accurate accounting of controlled drug transactions by inpatient hospital pharmacies is a requirement in the United States under the Controlled Substances Act. At many hospitals, manual distribution of controlled substances from pharmacies is being replaced by automated dispensing cabinets (ADCs) at the point of care. Despite the promise of improved accountability, a high prevalence (15%) of controlled substance discrepancies between ADC records and anesthesia information management systems (AIMS) has been published, with a similar incidence (15.8%; 95% confidence interval [CI], 15.3% to 16.2%) noted at our institution. Most reconciliation errors are clerical. In this study, we describe a method to capture drug transactions in near real-time from our ADCs, compare them with documentation in our AIMS, and evaluate subsequent improvement in reconciliation accuracy. METHODS: ADC-controlled substance transactions are transmitted to a hospital interface server, parsed, reformatted, and sent to a software script written in Perl. The script extracts the data and writes them to a SQL Server database. Concurrently, controlled drug totals for each patient having care are documented in the AIMS and compared with the balance of the ADC transactions (i.e., vending, transferring, wasting, and returning drug). Every minute, a reconciliation report is available to anesthesia providers over the hospital Intranet from AIMS workstations. The report lists all patients, the current provider, the balance of ADC transactions, the totals from the AIMS, the difference, and whether the case is still ongoing or had concluded. Accuracy and latency of the ADC transaction capture process were assessed via simulation and by comparison with pharmacy database records, maintained by the vendor on a central server located remotely from the hospital network. For assessment of reconciliation accuracy over time, data were collected from our AIMS from January 2012 to June 2013 (Baseline), July 2013 to April 2014 (Next Day Reports), and May 2014 to September 2015 (Near Real-Time Reports) and reconciled against pharmacy records from the central pharmacy database maintained by the vendor. Control chart (batch means) methods were used between successive epochs to determine if improvement had taken place. RESULTS: During simulation, 100% of 10,000 messages, transmitted at a rate of 1295 per minute, were accurately captured and inserted into the database. Latency (transmission time to local database insertion time) was 46.3 ± 0.44 milliseconds (SEM). During acceptance testing, only 1 of 1384 transactions analyzed had a difference between the near real-time process and what was in the central database; this was for a "John Doe" patient whose name had been changed subsequent to data capture. Once a transaction was entered at the ADC workstation, 84.9% (n = 18 bins; 95% CI, 78.4% to 91.3%) of these transactions were available in the database on the AIMS server within 2 minutes. Within 5 minutes, 98.2% (n = 18 bins; 95% CI, 97.2% to 99.3%) were available. Among 145,642 transactions present in the central pharmacy database, only 24 were missing from the local database table (mean = 0.018%; 95% CI, 0.002% to 0.034%). Implementation of near real-time reporting improved the controlled substance reconciliation error rate compared to the previous Next Day Reports epoch, from 8.8% to 5.2% (difference = -3.6%; 95% CI, -4.3% to -2.8%; P < 10). Errors were distributed among staff, with 50% of discrepancies accounted for by 12.4% of providers and 80% accounted for by 28.5% of providers executing transactions during the Near Real-Time Reports epoch. CONCLUSIONS: The near real-time system for the capture of transactional data flowing over the hospital network was highly accurate, reliable, and exhibited acceptable latency. This methodology can be used to implement similar data capture for transactions from their drug ADCs. Reconciliation accuracy improved significantly as a result of implementation. Our approach may be of particular utility at facilities with limited pharmacy resources to audit anesthesia records for controlled substance administration and reconcile them against dispensing records.

Implications of Patient Age and ASA Physical Status for Operating Room Management Decisions.

BACKGROUND: In elderly, high-risk patients, operating room (OR) turnaround times are especially difficult to estimate, and the managerial implications of patient age and ASA physical status for OR management decisions remain unclear. We hypothesized that evaluating patient age and ASA physical status in the right model would improve accuracy of turnaround time estimates and, thus, would have decisive implications for OR management. METHODS: By using various multivariate techniques, we modeled turnaround times of 13,632 OR procedures with respect to multiple variables including surgical list, age, ASA physical status, duration of the procedure, and duration of the preceding procedure. We first assessed correlations and general descriptive features of the data. Then, we constructed decision tables for OR management consisting of 50th and 95th percentiles of age/ASA-dependent estimates of turnaround times. In addition, we applied linear and generalized linear multivariate models to predict turnaround times. The forecasting power of the models was assessed in view of single cases but also in view of critical managerial key figures (50th and 95th percentile turnaround times). The models were calibrated on 80% of the data, and their predictive value was tested on the remaining 20%. We considered our data in a Monte Carlo simulation to deduce actual reductions of overutilized OR time when applying the results as presented in this work. RESULTS: Using the best models, we achieved an increase in predictive accuracy of 7.7% (all lists), ranging from 2.5% (general surgery) to 21.0% (trauma surgery) relative to age/ASA-independent medians of turnaround times. All models decreased the forecasting error, signifying a relevant increase in planning accuracy. We constructed a management decision table to estimate age/ASA-dependent turnaround time for OR scheduling at our hospital. CONCLUSIONS: The decision tables allow OR managers at our hospital to schedule procedures more accurately. Evaluation of patient age and ASA physical status as variables can help to better predict turnaround times, which can facilitate scheduling, for example, to schedule overlapping induction rooms, to reduce overutilized OR time by optimizing allocation of patients to several ORs, and to improve logistics of prioritizing transportation of advanced age/high ASA physical status patients to the OR.

Effect of Individual Surgeons and Anesthesiologists on Operating Room Time.

BACKGROUND: Variability in operating room (OR) time causes overutilization and underutilization of the available ORs. There is evidence that for a given type of procedure, the surgeon is the major source of variability in OR time. The primary aim was to quantify the variability between surgeons and anesthesiologists. As illustration, the value of modeling the individual surgeons and anesthesiologist for OR time prediction was estimated. METHODS: OR data containing 16,480 cases were obtained from a general surgery department. The total amount of variability in OR time accounted for by the type of procedure, first and second surgeon, and the anesthesiologist was determined with the use of linear mixed models. The effect on OR time prediction was evaluated as reduction in overtime and idle time per case. RESULTS: Differences between first surgeons can account for only 2.9% (2.0%-4.2%) of the variability in OR time. Differences between anesthesiologists can account for 0.1% (0.0%-0.3%) of the variability in OR time. Incorporating the individual surgeons and anesthesiologists led to an average reduction of overtime and idle time of 1.8 (95% confidence interval, 1.7-2.0, 10.5% reduction) minutes and 3.0 (95% confidence interval, 2.8%-3.2, 17.0% reduction) minutes, respectively. CONCLUSIONS: In comparison with the type of procedure, differences between surgeons account for a small part of OR time variability. The impact of differences between anesthesiologists on OR time is negligible. A prediction model incorporating the individual surgeons and anesthesiologists has an increased precision, but improvements are likely too marginal to have practical consequences for OR scheduling.

Comparing Policies for Case Scheduling Within 1 Day of Surgery by Markov Chain Models.

BACKGROUND: In previous studies, hospitals' operating room (OR) schedules were influenced markedly by decisions made within a few days of surgery. At an academic hospital, 46% of ORs had their last case scheduled or changed within 1 working day of surgery, and a private hospital had 64%. Many of these changes were for patients who were admitted before surgery (i.e., inpatient cases). In this study, we investigate the impact on OR productivity of how cases are scheduled within 1 working day before the day of surgery. METHODS: We consider the case-scheduling choice between 2 ORs. We compare 3 scheduling policies: Best Fit Descending, Worst Fit Descending, and Worst Fit Ascending. "Descending" strategies consider new cases from longest to shortest, whereas "Ascending" considers new cases from shortest to longest. Best Fit schedules each new case into the OR with sufficient but the least remaining underutilized OR time for the case. Worst Fit does the same but with the most remaining time. For our application, Best Fit chooses a later start time, whereas Worst Fit chooses an earlier start time. In our computational model, cases are of 2 possible durations, brief or long. Case cancellation is incorporated explicitly, and the number of new cases to schedule depends on the current number of scheduled cases in each OR, both new from previous studies. The number of cases in each OR is modeled as a Markov chain, evolving between 2 periods, corresponding to 1 day and 0 days before the day of surgery. For each scheduling policy, we evaluate the mean overutilized OR time and productivity. Our sensitivity analyses cover many cancellation rates, arrival settings, case durations, and initial conditions (i.e., how cases are scheduled into the 2 ORs preceding 1 workday before the day of surgery). RESULTS: Best Fit Descending and Worst Fit Descending achieved almost the same overutilized time and productivity. Worst Fit Ascending caused greater overutilized time (as much as 6.6 minutes more per OR) and thus lesser productivity (as much as 1.6% less) compared with Best Fit Descending or Worst Fit Descending. When the staff were scheduled for less time than the optimal allocated OR time, there were nearly the same differences between the staff productivity resulting from the use of Worst Fit Ascending rather than Worst Fit Descending or Best Fit Descending. CONCLUSIONS: Scheduling office decision making within 1 day before surgery should be based on statistical forecasts of expected total OR workload (i.e., forecasts that include the addition of non-elective cases and the subtraction of cases that cancel). As long as a case is not scheduled into overutilized time when less overutilized time could be achieved in another OR, and cases are considered in descending sequence of scheduled durations, the differences in overutilized time and productivity among the scheduling policies are small. Cognitive bias in staff scheduling causes a significant reduction in productivity, but the differences among scheduling policies are nearly the same as when there is no bias.

Postintervention Patency: A Comparison of Stenting versus Patch Angioplasty for Dysfunctional Hemodialysis Access Sites.

BACKGROUND: Arteriovenous access dysfunction is commonly caused by venous outflow stenosis, leading to thrombosis of the conduit. Given that there are limited lifetime hemodialysis access sites, the preservation of existing sites through novel means is of high priority. This study compares the efficacy of balloon angioplasty and stent placement to surgical patch angioplasty for upper arm (brachium) thrombosed or dysfunctional hemodialysis access sites in a group of patients at a single institution. METHODS: Using the operating room log and electronic medical record system, we retrospectively examined the outcomes of 52 consecutive patients (3 were lost to follow-up), who had either stent placement (34 patients) or patch angioplasty (15 patients) for hemodialysis access salvage to calculate postintervention patency. RESULTS: Initial postinterventional patency (PIP1) for patch angioplasty compared with stent placement was not statistically significant at any time during a mean 6-month follow-up (60% vs. 67.65% at 1 month, 33.33% vs. 41.18% at 3 months, and 13.33% vs. 17.65% at 6 months, respectively; P = 0.75). Patency after secondary reintervention (PIP2) was longer for patients who had stent placement as the initial intervention (n = 15) than patients who had patch angioplasty (n = 5; 100% vs. 80% at 1 month, 66.68% vs. 80% at 3 months, and 46.67% vs. 40% at 6 months, respectively), but again there was no statistically significant difference between the 2 groups (P = 0.84). At last, the initial PIP1 of arteriovenous fistula (AVF) and arteriovenous graft (AVG) salvaged before occlusion was significantly different from that of occluded access sites (40% vs. 10% at 6 months, P = 0.024). CONCLUSIONS: Our data suggest that AVF had a longer postinterventional primary patency than AVG though the difference did not reach statistical significance. Stents extended PIP1 for the thrombosed or failing arteriovenous access longer than patch angioplasty, but the difference was not statistically significant. Patency is longer if intervention is made before graft thrombosis. Our data also indicate better prolongation of patency with a second reintervention (PIP2) if the first intervention was a stent placement. Patch angioplasty appears to be a less attractive alternative for correction of venous outflow stenosis given the more invasive and occasionally technically difficult procedure.

The evolution of perioperative transfusion testing and blood ordering.

The evolution of modern anesthesia and surgical practices has been accompanied by enhanced supportive procedures in blood banking and transfusion medicine. There is increased focus on the preparation and the use of blood components including, but not limited to, preventing unnecessary type and screen/crossmatch orders, decreasing the time required to provide compatible red blood cells (RBCs), and reducing the waste of limited blood and personnel resources. The aim of this review is to help the anesthesiologist and surgical staff identify patients at highest risk for surgical bleeding. In addition, this review examines how anesthesia and transfusion medicine can efficiently and safely allocate blood components for surgical patients who require transfusions. The following databases were searched: PubMed, EMBASE, Google Scholar, and the Cochrane Library from January 1970 through March 2014. Subsequent reference searches of retrieved articles were also assessed. Several innovations have drastically changed the procedures by which blood is ordered, inventoried, and the speed in which blood is delivered for patient care. Before entering an operating room, patient blood management provides guidance to clinicians about when and how to treat preoperative anemia and intra- and postoperative strategies to limit the patient's exposure to blood components. Timely updates of the recommendations for blood orders (maximum surgical blood ordering schedule) have enhanced preoperative decision making regarding the appropriateness of the type and screen versus the type and crossmatch order. The updated maximum surgical blood ordering schedule reflects modern practices, such as laparoscopy, improved surgical techniques, and use of hemostatic agents resulting in a more streamlined process for ordering and obtaining RBCs. The electronic (computer) crossmatch and electronic remote blood issue have also dramatically reduced the amount of time required to obtain crossmatch-compatible RBCs when compared with the more traditional serologic crossmatch methods. These changes in blood banking methods have resulted in more efficient delivery of blood to surgical patients.

Management implications for the perioperative surgical home related to inpatient case cancellations and add-on case scheduling on the day of surgery.

BACKGROUND: The American Society of Anesthesiologists has embraced the concept of the Perioperative Surgical Home as a means through which anesthesiologists can add value to the health systems in which they practice. One key listed element of the Perioperative Surgical Home is to support "scheduling initiatives to reduce cancellations and increase efficiency." In this study, we explored the potential benefits of the Perioperative Surgical Home with respect to inpatient cancellations and add-on case scheduling. We evaluated 6 hypotheses related to the timing of inpatient cancellations and preoperative anesthesia evaluations. METHODS: Inpatient cancellations were studied during 26 consecutive 4-week intervals between July 2012 and June 2014 at a tertiary care academic hospital. All timestamps related to scheduling, rescheduling, and cancellation activities were retrieved from the operating room (OR) case scheduling system. Timestamps when patients were seen by anesthesia residents were obtained from the preoperative evaluation system database. Batch mean methods were used to calculate means and SE. For cases cancelled, we determined whether, for "most" (>50%) cancellations, a subsequent procedure (of any type) was performed on the patient within 7 days of the cancellation. Comparisons with most and other fractions were assessed using the 1 group, 1-sided Student t test. We evaluated whether a few procedures were highly represented among the cancelled cases via the Herfindahl (Simpson's) index, comparing it with <0.15. The rate of scheduling activity was assessed by computing the number of OR scheduling office decisions in each 1-hour bin between 6:00 AM and 3:59 PM. These values were compared with ≥1 decision per hour at the study hospital. RESULTS: Data from 24,735 scheduled inpatient cases were assessed. Cases cancelled after 7 AM on the day before or at any time on the scheduled day of surgery accounted for 22.6% ± 0.5% (SE) of the scheduled minutes all scheduled cases, and 26.8% ± 0.4% of the case volume (i.e., number of cases). Most (83.1% ± 0.6%, P < 10) cases performed were evaluated on the day before surgery. Most (67.6% ± 1.6%, P < 10) minutes of cancelled cases were evaluated on the day before surgery. Most (62.3% ± 1.5%, P < 10) cases were seen earlier than 6:00 PM of the day before surgery. The Herfindahl index among cancelled procedures was 0.021 ± 0.001 (P < 10 compared not only to <0.15 but also to <0.05), showing large heterogeneity among the cancelled procedures. A subsequent procedure was not performed for most cancelled cases (50.6% ± 0.9% compared with >50%, P = 0.12), implying that the indication for the cancelled procedure no longer existed or the patient/family decided not to proceed with surgery. When only cancellations on the scheduled day of surgery were considered, the cancellation rate was 14.0% ± 0.3% of scheduled inpatient minutes and 11.8% ± 0.2% of scheduled inpatient cases. There were 0.59 ± 0.02 OR schedule decisions per hour per 10 ORs between 6:00 AM and 3:59 PM (P < 10, corresponding to ≥1 decision per hour at the 36 OR study hospital). CONCLUSIONS: The study hospital had a high inpatient cancellation rate, despite the fact that most patients whose cases were cancelled were seen by an anesthesia resident by 6:00 PM of the day before surgery. This finding suggests that further efforts to reduce the cancellations by seeing patients sooner on the day before surgery, or seeing even more patients the day before surgery, would not be an economically useful focus of the Perioperative Surgical Home. The wide heterogeneity among cancelled cases indicates that focusing on a few procedures would not materially affect the overall cancellation rate. The relatively low rate of subsequent performance of a procedure on patients whose cases had been cancelled suggests that trying to decrease the cancellation rate might be medically counterproductive. The hourly rate of decisions in the scheduling office during regular work hours on the day of surgery highlights the importance of decisions made at the OR control desk and scheduling office throughout the day to reduce the hours of overused OR time. These data suggest that efforts of the Perioperative Surgical Home related to inpatient cancellations should focus on management decision-making to mitigate the disruptions to the planned OR schedule caused by inpatient case cancellations and add-on cases, more so than on efforts to reduce inpatient cancellation rates.

Quality of Supervision as an Independent Contributor to an Anesthesiologist's Individual Clinical Value.

BACKGROUND: Although the clinical (operating room) production of individual anesthesiologists has been measured in multiple related ways (e.g., hours of direct clinical care), the same is not true for the quality of that effort. In our study, we consider the quality of clinical supervision provided by anesthesiologists who are supervising anesthesia residents and nurse anesthetists. The quality of the daily supervision can be measured reliably and validly using the scale developed by de Oliveira Filho et al. If clinical production and supervisory quality were not positively correlated, then it would be important for departments to measure the quality of clinical supervision because, essentially, the clinical value provided by an anesthesiologist would be correlated with, but not necessarily proportional to, their clinical hours. METHODS: Our department sends daily e-mail requests to anesthesia residents and nurse anesthetists to evaluate the supervision provided by each anesthesiologist with whom they worked the previous day in an operating room setting. We compared anesthesiologists' clinical activity (total operating room hours) and supervision scores obtained during the first (July 1, 2013 to December 31, 2013) and last (July 1, 2014 to December 31, 2014) of 3 consecutive 6-month periods. During the first 6 months, anesthesiologists received no feedback regarding the supervision scores. During the last 6 months, there was feedback to all anesthesiologists regarding their individual supervision scores and comments provided by residents (during the preceding 6 months) and nurse anesthetists (during the preceding 12 months). RESULTS: Anesthesiologists' mean supervision scores were not positively correlated with their total (weekly) hours of clinical activity. For the first 6 months, the correlations were r = -0.18 among scores provided by residents (P = 0.92 for positive correlation, N = 57 anesthesiologists) and r = -0.04 among scores provided by nurse anesthetists (P = 0.70, N = 61). For the last 6 months, the correlations were r = -0.28 (P = 0.98) and r = -0.10 (P = 0.79), respectively. Pairwise by anesthesiologist, the mean supervision scores provided by residents increased by 0.08 ± 0.01 points (P < 0.0001, N = 44). The mean supervision scores provided by nurse anesthetists increased by 0.28 ± 0.02 points (P < 0.0001, N = 49). CONCLUSIONS: When anesthesiologists supervise anesthesia residents and nurse anesthetists, the amount of clinical work performed and the quality of the supervision provided do not necessarily follow one another. Thus, faculty supervision scores serve as an independent measure of the contribution of an individual anesthesiologist to the care of the patient. Furthermore, when supervision quality is monitored and feedback is provided to anesthesiologists, quality can increase. The results suggest that anesthesiology department managers should not only be monitoring (and perhaps reporting) the quality of their departments' level of supervision, but also establishing processes so that individual anesthesiologists can learn about the quality of supervision they provide.