Preventing Prolonged Times to Awakening While Mitigating the Risk of Patient Awareness: Gas Man Computer Simulations of Sevoflurane Consumption From Brief, High Fresh Gas Flow Before the End of Surgery.

Prolonged times to tracheal extubation are associated with adverse patient and economic outcomes. We simulated awakening patients from sevoflurane after long-duration surgery at 2% end-tidal concentration, 1.0 minimum alveolar concentration (MAC) in a 40-year-old. Our end-of-surgery target was 0.5 MAC, the Michigan Awareness Control Study's threshold for intraoperative alerts. Consider an anesthetist who uses a 1 liter/minute gas flow until surgery ends. During surgical closure, the inspired sevoflurane concentration is reduced from 2.05% to 0.62% (i.e., MAC-awake). The estimated time to reach 0.5 MAC is 28 minutes. From a previous study, 28 minutes exceeded ≥95% of surgical closure times for all 244 distinct surgical procedures (N=23,343 cases). Alternatively, the anesthetist uses 8 liters/minute gas flow with the vaporizer at MAC-awake for 1.8 minutes, which reduces the end-tidal concentration to 0.5 MAC. The anesthetist then increases the vaporizer to keep end-tidal 0.5 MAC until the surgery ends. An additional simulation shows that, compared with simulated end-tidal agent feedback control, this approach consumed 0.45 mL extra agent. Simulation results are the same for an 80-year-old patient. The extra 0.45 mL has a global warming potential comparable to driving 26 seconds at 40 kilometers (25 miles) per hour, comparable to route modification to avoid potential roadway hazards.

Association Between the Community Prevalence of COVID-19 and Daily Unscheduled Absences of Anesthesiologists, Nurse Anesthetists, and Residents in an Academic Anesthesia Department.

Introduction An "unscheduled absence" refers to an occurrence when an employee does not appear for work and the absence was not approved in advance by an authorized supervisor. Daily unscheduled absences need to be forecasted when doing staff scheduling to maintain an acceptable risk of being unable to run all anesthetizing locations and operating rooms planned. The number of extra personnel to be scheduled needs to be at least twice as large as the mean number absent. In an earlier historical cohort study, we found that our department's modeled risks of being unavailable unexpectedly differed among types of anesthesia practitioners (e.g., anesthesiologists and nurse anesthetists) and among weekdays (i.e., Mondays, Fridays, and workdays adjacent to holidays versus other weekdays). In the current study, with two extra years of data, we examined the effect of the coronavirus COVID-19 pandemic on the frequency of unscheduled absences. Methods There were 50 four-week periods studied at a large teaching hospital in the United States, from August 30, 2018 to June 29, 2022. The sample size of 120,687 person-assignment days (i.e., a person assigned to work on a given day) included 322 anesthesia practitioners (86 anesthesiologists, 88 certified registered nurse anesthetists, 99 resident and fellow physicians, and 49 student nurse anesthetists). The community prevalence of COVID­19 was estimated using the percentage positive among asymptomatic patients tested before surgery and other interventional procedures at the hospital. Results Each 1% increase in the prevalence of COVID-19 among asymptomatic patients was associated with a 1.131 increase in the odds of unscheduled absence (P < 0.0001, 99% confidence interval 1.086 to 1.178). Using an alternative model with prevalence categories, unscheduled absences were substantively more common when the COVID-19 prevalence exceeded 2.50%, P [Formula: see text] 0.0002. For example, there was a 1% unscheduled absence rate among anesthesiologists working Mondays and Fridays early in the pandemic when the prevalence of COVID-19 among asymptomatic patients was 1.3%. At a 1% unscheduled absence rate, 67 would be the minimum scheduled to maintain a <5.0% risk for being unable to run all 65 anesthetizing locations. In contrast, there was a 3% unscheduled absence rate among nurse anesthetists working Mondays and Fridays during the Omicron variant surge when the prevalence was 4.5%. At a 3% unscheduled absence rate, 70 would be the minimum scheduled to maintain the same risk of not being able to run 65 rooms. Conclusions Increases in the prevalence of COVID-19 asymptomatic tests were associated with more unscheduled absences, with no detected threshold. This quantitative understanding of the impact of communicable diseases on the workforce potentially has broad generalizability to other fields and infectious diseases.

Case duration prediction and estimating time remaining in ongoing cases.

In this issue of the British Journal of Anaesthesia, Jiao and colleagues applied a neural network model for surgical case durations to predict the operating room times remaining for ongoing anaesthetics. We review estimation of case durations before each case starts, showing why their scientific focus is useful. We also describe managerial epidemiology studies of historical data by the scheduled procedure or distinct combinations of scheduled procedures included in each surgical case. Most cases have few or no historical data for the scheduled procedures. Generalizability of observational results such as theirs, and automatic computer assisted clinical and managerial decision-making, are both facilitated by using structured vocabularies when analysing surgical procedures.

The anesthetizing sites supervised to anesthesiologist ratio is an invalid surrogate for group productivity in academic anesthesia departments when used without consideration of the corresponding managerial decisions.

When the anesthesiologist does not individually perform the anesthesia care, then to make valid comparisons among US anesthesia departments, one must consider the staffing ratio (i.e., how many cases each anesthesiologist supervises when working with Certified Registered Nurse Anesthetists [CRNAs] or Certified Anesthesiologist Assistants [CAA]). The staffing ratio also must be considered when accurately measuring group productivity. In this narrative review, we consider anesthesia departments with non-physician anesthesia providers and anesthesiology residents. We investigate the validity of such departments assessing the overall ratio of anesthetizing sites supervised per anesthesiologist as a surrogate for group clinical productivity. The sites/anesthesiologist ratio can be estimated accurately using the arithmetic mean calculated by anesthesiologist, the harmonic mean calculated by case, or the harmonic mean calculated by CRNA or CAA, but not by the arithmetic mean ratio by case. However, there is lack of validity to benchmarking the percentage time that anesthesiologists are supervising the maximum possible number of CRNAs or CAAs when some of the anesthesiologists also are supervising resident physicians. Assignments can differ in the total number anesthesiologists needed while every anesthesiologist is supervising as many sites as possible. Similarly, there is lack of validity to limiting assessment to the anesthesiologists supervising only CRNAs or CAAs. There also is lack of validity to limiting assessment only to cases performed by supervised CRNAs or CAAs. When cases can be assigned to anesthesiology residents or CRNAs or CAAs, increasing sites/anesthesiologist while limiting consideration to the CRNAs or CAAs creates incentive for the CRNAs or CAAs to be assigned cases, even when lesser productivity is the outcome. Decisions also can increase sites/anesthesiologist without increasing productivity (e.g., when one anesthesiologist relieves another before the end of the regular workday). A suitable alternative approach to fallaciously treating the sites/anesthesiologist ratio as a surrogate for productivity is that, when a teaching hospital supplies financial support, a responsibility of the anesthesia department is to explain annually the principal factors affecting productivity at each facility it manages and to show annually that decisions were made that maximized productivity, subject to the facilities' constraints.

Sustained management of the variability in work hours among anesthesiologists providing patient care in operating rooms and not on call to work late if necessary.

STUDY OBJECTIVE: We evaluated a department's long-term (6.5-year) success of achieving an overall and individual incidence of anesthesiologists working late of approximately 20% of days when not on call to work late, if necessary, and providing care in operating rooms. DESIGN: Historical cohort study, January 2014 through September 2020. SETTING: Inpatient surgical suite of large teaching hospital. MAIN RESULTS: The percentage of days worked past 5:00 PM was mean (standard deviation) 17.7% (5.0%) of days, 99% confidence interval (CI) 15.0% to 20.4%. There was considerable variability among quarters, the coefficient of variation being 28% (99% CI 20% to 45%). This was caused, in part, by anesthesiologists less often working late during January-March versus July-September (14.0% [4.5%] versus 21.6% [3.2%]; P = 0.0031; N = 7 years each). The N = 67 anesthesiologists not on call differed in their percentages of workdays finishing after 5:00 PM (P < 0.0001). While the mean was 18% (6%), the coefficient of variation was 37% (29% to 49%). There were no significant outliers. In contrast, not only were there differences among anesthesiologists in the relative risks of working late when receiving relief versus when not handing off a case (P < 0.0001), there were outliers. CONCLUSIONS: An anesthesia department aiming for a 20% incidence of anesthesiologists having to work late when not on call can achieve this objective, long-term, within a few percent (e.g., 2%). Seasonal variation can contribute to variability among quarters in the overall departmental incidence. Individual anesthesiologists can have variability among themselves, though, and that is caused by large heterogeneity in their relative risks of working late when receiving relief versus when not handing off a case. For departments choosing to provide information to anesthesiologists to increase predictability, factors to consider should include season of the year and the individual anesthesiologist.

Comparisons of unscheduled absences among categories of anesthesia practitioners, including anesthesiologists, nurse anesthetists, and anesthesia residents.

BACKGROUND: An "unscheduled absence" refers to an occurrence when an employee does not appear for work and the absence was without advance approval by an authorized supervisor. Recently we estimated the prevalence of unscheduled absences in a cohort of certified registered nurse anesthetists at the University of Miami. We performed a historical cohort study for all types of anesthesia practitioners at the University of Iowa. METHODS: Two-years of person-assignment days were studied. The total population was 62,951 regular operating room days among 293 people. There were 56,437 days among 203 practitioners with multiple workdays over multiple quarters. RESULTS: In the total population, the 91 nurse anesthetists had 1.48% person-days with an unscheduled absence, comparable to the 1.74% from University of Miami. Most unscheduled absences (99% lower confidence limit 80.1%) resulted in the person being absent from an operating room clinical assignment for just 1 day. Compared with nurse anesthetists, residents and fellows had proportionately fewer unscheduled absences (odds ratio 0.24 [0.13-0.45], P<.0001), as did anesthesiologists (0.49 [0.30-0.79], P=.0002). Among all practitioners, Mondays, Fridays, and days adjacent to holidays had significantly more unscheduled absences than Tuesdays, Wednesdays, and Thursdays (1.45 [1.19-1.76], P<.0001). CONCLUSIONS: To have an adequate daily workforce, anesthesia clinical directors need to estimate the daily expected percentage of assigned anesthesia practitioners who will be absent. Potential inter-group differences should be considered. We provide a worked example showing how to use the results to decide numbers of practitioners to plan daily.

Comparison of the effect of three different adjuvants on the analgesic duration of single injection interscalene brachial plexus block: a prospective, randomized, triple blinded clinical trial.

BACKGROUND AND OBJECTIVES: Use of regional anesthesia can result in faster recovery and better patient satisfaction. Addition of perineural adjuncts to local anesthetics may improve the duration of analgesia, but there is a paucity of data comparing them in a single randomized trial. We compared the effects of three adjuncts clonidine, dexamethasone, and buprenorphine, on the duration of analgesia of interscalene brachial plexus block. METHODS: 160 patients, undergoing elective shoulder surgery, were randomized to four groups to receive an interscalene block with one of the following solutions: ropivacaine alone, ropivacaine with clonidine 75 µg, ropivacaine with dexamethasone 8 mg, or ropivacaine with buprenorphine 300 µg. The primary outcome variable was the duration of analgesia; secondary outcome measures were time to onset of the block, and the duration of sensory and motor blocks. RESULTS: There was no statistically significant difference in the total analgesia time among the four groups; p=0.11. The pairwise comparison in analgesic time and 99% CI were: control versus clonidine (-1.94 hours (-7.33 to 3.12)), control versus dexamethasone (-4.16 hours (-9.50 to 0.58)) and control versus buprenorphine (-1.1 hours (-5.34 to 3.23)). There was no differences in block set-up time, or total sensory and motor block duration among the groups. CONCLUSION: There was no significant improvement in the duration of analgesia with addition of any of the three adjuncts to interscalene blocks. However, there was a larger than expected variability in patient response, hence the study may have been underpowered for the primary outcome.

The influence of the type and design of the anesthesia record on ASA physical status scores in surgical patients: paper records vs. electronic anesthesia records.

BACKGROUND: The American Society of Anesthesiologists Physical Status classification (ASA PS) of surgical patients is a standard element of the preoperative assessment. In early 2013, the Department of Anesthesia was notified that the distribution of ASA PS scores for sampled patients at the University of Iowa had recently begun to deviate from national comparison data. This change appeared to coincide with the transition from paper records to a new electronic Anesthesia Information Management System (AIMS). We hypothesized that the design of the AIMS was unintentionally influencing how providers assigned ASA PS values. METHODS: Primary analyses were based on 12-month blocks of data from paper records and AIMS. For the purpose of analysis, ASA PS was dichotomized to ASA PS 1 and 2 vs. ASA PS >2. To ensure that changes in ASA PS were not due to "real" changes in our patient mix, we examined other relevant covariates (e.g. age, weight, case distribution across surgical services, emergency vs. elective surgeries etc.). RESULTS: There was a 6.1 % (95 % CI: 5.1-7.1 %) absolute increase in the fraction of ASA PS 1&2 classifications after the transition from paper (54.9 %) to AIMS (61.0 %); p < 0.001. The AIMS was then modified to make ASA PS entry clearer (e.g. clearly highlighting ASA PS on the main anesthesia record). Following the modifications, the AS PS 1&2 fraction decreased by 7.7 % (95 % CI: 6.78-8.76 %) compared to the initial AIMS records (from 61.0 to 53.3 %); p < 0.001. There were no significant or meaningful differences in basic patient characteristics and case distribution during this time. CONCLUSION: The transition from paper to electronic AIMS resulted in an unintended but significant shift in recorded ASA PS scores. Subsequent design changes within the AIMS resulted in resetting of the ASA PS distributions to previous values. These observations highlight the importance of how user interface and cognitive demands introduced by a computational system can impact the recording of important clinical data in the medical record.

A Comparison of 2 Ultrasound-Guided Approaches to the Saphenous Nerve Block: Adductor Canal Versus Distal Transsartorial: A Prospective, Randomized, Blinded, Noninferiority Trial.

BACKGROUND AND OBJECTIVES: Saphenous nerve blocks can be technically challenging. Recently described ultrasound techniques have improved the success rate of saphenous nerve blocks, but randomized controlled trials comparing these ultrasound-guided techniques are lacking. We compared 2 common ultrasound-guided approaches for saphenous nerve block: saphenous nerve block at the adductor canal (ACSNB) versus block by the distal transsartorial (DTSNB) approach. METHODS: Patients received either ACSNB or DTSNB in this prospective, randomized, blinded, noninferiority clinical trial. The primary objective was to show the noninferiority of ACSNB to DTSNB in terms of block success. Secondary outcome measures were time required to perform the block, time to onset of successful block, and the visibility of the nerve using ultrasound. RESULTS: One hundred twenty patients were randomized to receive DTSNB (n = 62) or ACSNB (n = 58). There were 9 failures in the DTSNB group (85% success) and no failures in the ACSNB group (100% success), 90% confidence interval of difference in success rates (DTSNB - ACSNB) was -0.195 to -0.031. Given that the upper confidence bound (-3.1%) was less than 10%, the success rate of ACSNB was noninferior to DTSNB. After satisfying noninferiority and observing a greater success rate of ACSNB compared with DTSNB, we also determined that ACSNB was superior to DTSNB (P = 0.003). The median time to success was significantly less for the ACSNB group: 9 minutes versus 3 minutes (P < 0.001). The grade of the ultrasound image, as judged by the provider, was significantly better in the ACSNB group (P = 0.001). CONCLUSIONS: Ultrasound-guided block of the saphenous nerve at the adductor canal is not only noninferior but also superior to block at the distal transsartorial level in terms of success rate, with additional advantages of faster block onset time and better nerve visibility under ultrasound.

Comparison of alphabetical versus categorical display format for medication order entry in a simulated touch screen anesthesia information management system: an experiment in clinician-computer interaction in anesthesia.

BACKGROUND: Anesthesia information management system (AIMS) records should be designed and configured to facilitate the accurate and prompt recording of multiple drugs administered coincidentally or in rapid succession. METHODS: We proposed two touch-screen display formats for use with our department's new EPIC touch-screen AIMS. In one format, medication "buttons" were arranged in alphabetical order (i.e. A-C, D-H etc.). In the other, buttons were arranged in categories (Common, Fluids, Cardiovascular, Coagulation etc.). Both formats were modeled on an iPad screen to resemble the AIMS interface. Anesthesia residents, anesthesiologists, and Certified Registered Nurse Anesthetists (n = 60) were then asked to find and touch the correct buttons for a series of medications whose names were displayed to the side of the entry screen. The number of entries made within 2 minutes was recorded. This was done 3 times for each format, with the 1st format chosen randomly. Data were analyzed from the third trials with each format to minimize differences in learning. RESULTS: The categorical format had a mean of 5.6 more drugs entered using the categorical method in two minutes than the alphabetical format (95% confidence interval [CI] 4.5 to 6.8, P < 0.0001). The findings were the same regardless of the order of testing (i.e. alphabetical-categorical vs. categorical - alphabetical) and participants' years of clinical experience. Most anesthesia providers made no (0) errors for most trials (N = 96/120 trials, lower 95% limit 73%, P < 0.0001). There was no difference in error rates between the two formats (P = 0.53). CONCLUSIONS: The use of touch-screen user interfaces in healthcare is increasingly common. Arrangement of drugs names in a categorical display format in the medication order-entry touch screen of an AIMS can result in faster data entry compared to an alphabetical arrangement of drugs. Results of this quality improvement project were used in our department's design of our final intraoperative electronic anesthesia record. This testing approach using cognitive and usability engineering methods can be used to objectively design and evaluate many aspects of the clinician-computer interaction in electronic health records.