Association of Anesthesiologist Handovers With Short-term Outcomes for Patients Undergoing Cardiac Surgery

The Impact of Intraoperative Anesthesiology Provider Handovers on Postoperative Complications After Hepatopancreatobiliary (HPB) Surgery

BACKGROUND

The objective of this study is to assess the possible association between intraoperative anesthesia team handovers and increased 90-day major complications following HPB surgery.

METHODS

This is a single-center retrospective cohort study of patients who underwent HPB surgery. Anesthesiologist handover (AH) occurred when a complete transfer of care to a receiving anesthesiologist. total anesthesia team handovers (TH) occurred when both anesthesiologist and supervised provider transferred care. The primary outcome was 90-day major complications, defined as an ACCORDION score of ≥ 3.

RESULTS

Ninety-day major complications occurred in 35 (21.6%) of TH and 96 (21.9%) of AH patients. With adjustment of other covariates, no significant association was found between AH (OR, 1.358, 95% CI, 0.935-1.973, p = 0.1079) or TH (OR, 1.157, 95% CI, 0.706-1.894, p = 0.5633) and 90-day major complications.

CONCLUSIONS

In a high-volume HPB center, anesthesia team handovers were not associated with an increased risk of patients having a major complication within 90 days after HPB surgery.

Proposed Quality Metrics for Congenital Cardiac Anesthesia: A Scoping Review

Congenital cardiac anesthesiologists practice in a unique environment with high risk for morbidity and mortality. Quality metrics can be used to focus clinical initiatives on evidence-based care and provide a target for local quality improvement measures. However, there has been no comprehensive review on appropriate quality metrics for congenital cardiac anesthesia to date. Members of the Quality and Safety Committee for the Congenital Cardiac Anesthesia Society proposed 31 possible candidate topics for metrics. Using a scoping review strategy, 3649 abstracts were reviewed with 30 articles meeting final criteria. Of these, 5 candidate metrics were unanimously proposed for local collection and national benchmarking efforts: use of a structured handover in the intensive care unit, use of an infection prevention bundle, use of blood conservation strategies, early extubation of cardiopulmonary bypass cases, and cardiac arrest under the care of a cardiac anesthesiologist. Many metrics were excluded due to a lack of primary data and perceived complexity beyond the scope of cardiac anesthesia practice. There is a need to develop more primary data including linking process measures with outcomes, developing risk-stratification for our patients, and collecting national data for benchmarking purposes.

Patient and Operational Factors Do Not Substantively Affect the Annual Departmental Quality of Anesthesiologists' Clinical Supervision and Nurse Anesthetists' Work Habits

INTRODUCTION

Although safety climate, teamwork, and other non-technical skills in operating rooms probably influence clinical outcomes, direct associations have not been shown, at least partially due to sample size considerations. We report data from a retrospective cohort of anesthesia evaluations that can simplify the design of prospective observational studies in this area. Associations between non-technical skills in anesthesia, specifically anesthesiologists' quality of clinical supervision and nurse anesthetists' work habits, and patient and operational factors were examined.

METHODS

Eight fiscal years of evaluations and surgical cases from one hospital were included. Clinical supervision by anesthesiologists was evaluated daily using a nine-item scale. Work habits of nurse anesthetists were evaluated daily using a six-item scale. The dependent variables for both groups of staff were binary, whether all items were given the maximum score or not. Associations were tested with patient and operational variables for the entire day.

RESULTS

There were 40,718 evaluations of faculty anesthesiologists by trainees, 53,772 evaluations of nurse anesthetists by anesthesiologists, and 296,449 cases that raters and ratees started together. Cohen's d values were small (≤0.10) for all independent variables, suggesting a lack of any clinically meaningful association between patient and operational factors and evaluations given the maximum scores. For supervision quality, the day's count of orthopedic cases was a significant predictor of scores (P = 0.0011). However, the resulting absolute marginal change in the percentage of supervision scores equal to the maximum was only 0.8% (99% confidence interval: 0.2% to 1.4%), i.e., too small to be of clinical or managerial importance. Neurosurgical cases may have been a significant predictor of work habits (P = 0.0054). However, the resulting marginal change in the percentage of work habits scores equal to the maximum, an increase of 0.8% (99% confidence interval: 0.1% to 1.6%), which was again too small to be important.

CONCLUSIONS

When evaluating the effect of assigning anesthesiologists and nurse anesthetists with different clinical performance quality on clinical outcomes, supervision quality and work habits scores may be included as independent variables without concern that their effects are confounded by association with the patient or case characteristics. Clinical supervision and work habits are measures of non-technical skills. Hence, these findings suggest that non-technical performance can be judged by observing the typical small sample size of cases. Then, associations can be tested with administrative data for a far greater number of patients because there is unlikely to be a confounding association between patient and case characteristics and the clinicians' non-technical performance.

Effect of Intraoperative Handovers of Anesthesia Care on Mortality, Readmission, or Postoperative Complications Among Adults: The HandiCAP Randomized Clinical Trial

IMPORTANCE

Intraoperative handovers of anesthesia care are common. Handovers might improve care by reducing physician fatigue, but there is also an inherent risk of losing critical information. Large observational analyses report associations between handover of anesthesia care and adverse events, including higher mortality.

OBJECTIVE

To determine the effect of handovers of anesthesia care on postoperative morbidity and mortality.

DESIGN, SETTING, AND PARTICIPANTS

This was a parallel-group, randomized clinical trial conducted in 12 German centers with patients enrolled between June 2019 and June 2021 (final follow-up, July 31, 2021). Eligible participants had an American Society of Anesthesiologists physical status 3 or 4 and were scheduled for major inpatient surgery expected to last at least 2 hours.

INTERVENTIONS

A total of 1817 participants were randomized to receive either a complete handover to receive anesthesia care by another clinician (n = 908) or no handover of anesthesia care (n = 909). None of the participating institutions used a standardized handover protocol.

MAIN OUTCOMES AND MEASURES

The primary outcome was a 30-day composite of all-cause mortality, hospital readmission, or serious postoperative complications. There were 19 secondary outcomes, including the components of the primary composite, along with intensive care unit and hospital lengths of stay.

RESULTS

Among 1817 randomized patients, 1772 (98%; mean age, 66 [SD, 12] years; 997 men [56%]; and 1717 [97%] with an American Society of Anesthesiologists physical status of 3) completed the trial. The median total duration of anesthesia was 267 minutes (IQR, 206-351 minutes), and the median time from start of anesthesia to first handover was 144 minutes in the handover group (IQR, 105-213 minutes). The composite primary outcome occurred in 268 of 891 patients (30%) in the handover group and in 284 of 881 (33%) in the no handover group (absolute risk difference [RD], -2.5%; 95% CI, -6.8% to 1.9%; odds ratio [OR], 0.89; 95% CI, 0.72 to 1.10; P = .27). Nineteen of 889 patients (2.1%) in the handover group and 30 of 873 (3.4%) in the no handover group experienced all-cause 30-day mortality (absolute RD, -1.3%; 95% CI, -2.8% to 0.2%; OR, 0.61; 95% CI, 0.34 to 1.10; P = .11); 115 of 888 (13%) vs 136 of 872 (16%) were readmitted to the hospital (absolute RD, -2.7%; 95% CI, -5.9% to 0.6%; OR, 0.80; 95% CI, 0.61 to 1.05; P = .12); and 195 of 890 (22%) vs 189 of 874 (22%) experienced serious postoperative complications (absolute RD, 0.3%; 95% CI, -3.6% to 4.1%; odds ratio, 1.02; 95% CI, 0.81 to 1.28; P = .91). None of the 19 prespecified secondary end points differed significantly.

CONCLUSIONS AND RELEVANCE

Among adults undergoing extended surgical procedures, there was no significant difference between the patients randomized to receive handover of anesthesia care from one clinician to another, compared with the no handover group, in the composite primary outcome of mortality, readmission, or serious postoperative complications within 30 days.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04016454.

Communication failures contributing to patient injury in anaesthesia malpractice claims☆

BACKGROUND

Communication amongst team members is critical to providing safe, effective medical care. We investigated the role of communication failures in patient injury using the Anesthesia Closed Claims Project database.

METHODS

Claims associated with surgical/procedural and obstetric anaesthesia and postoperative pain management for adverse events from 2004 or later were included. Communication was defined as transfer of information between two or more parties. Failure was defined as communication that was incomplete, inaccurate, absent, or not timely. We classified root causes of failures as content, audience, purpose, or occasion with inter-rater reliability assessed by kappa. Claims with communication failures contributing to injury (injury-related communication failures; n=389) were compared with claims without any communication failures (n=521) using Fisher's exact test, t-test, or Mann-Whitney U-tests.

RESULTS

At least one communication failure contributing to patient injury occurred in 43% (n=389) out of 910 claims (κ=0.885). Patients in claims with injury-related communication failures were similar to patients in claims without failures, except that failures were more common in outpatient settings (34% vs 26%; P=0.004). Fifty-two claims had multiple communication failures for a total of 446 injury-related failures, and 47% of failures occurred during surgery, 28% preoperatively, and 23% postoperatively. Content failures (insufficient, inaccurate, or no information transmitted) accounted for 60% of the 446 communication failures.

CONCLUSIONS

Communication failure contributed to patient injury in 43% of anaesthesia malpractice claims. Patient/case characteristics in claims with communication failures were similar to those without failures, except that failures were more common in outpatient settings.

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.