Lack of association between intraoperative handoff of care and postoperative complications: a retrospective observational study

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.

Association of anesthesia handovers with perioperative and short-term outcomes after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy

BACKGROUND

Anesthesiologists transition patient care to combat clinician fatigue and accommodate shift limitations. Studies exploring the association of increased handovers with patient outcomes have conflicting findings. Here, we investigate the association of anesthesia handovers with perioperative outcomes in patients undergoing cytoreductive surgery and hyperthermic intraperitoneal chemotherapy.

METHODS

Patients undergoing cytoreductive surgery and hyperthermic intraperitoneal chemotherapy at a single institution from 2017 to 2022 were stratified by the number of anesthesia attending and nonattending (nurse anesthetist/resident) handovers (0-1 or ≥2). Primary outcomes were intensive care unit and hospital length of stay, in addition to 30-day serious morbidity. Logistic and negative binomial regression models were adjusted for covariates related to patient and case complexity.

RESULTS

A total of 182 patients were included. Median operative time was 720 minutes (interquartile range, 540-900 minutes). Most cases had fewer than 2 attending handovers (n = 147, 81% vs ≥2 handovers n = 35, 19%) and 2 nonattending handovers (n = 120, 71% vs ≥2 handovers n = 53, 29%). In adjusted models, there were no differences in 30-day serious morbidity and intensive care unit or hospital length of stay between the attending handover groups (0-1 vs ≥2). Patients with ≥2 non-attending handovers had similar odds of 30-day serious morbidity compared with the 0-1 group (odds ratio, 1.613, 95% confidence interval, 0.733-3.550, P = .235), but a longer total hospital (incidence rate ratio, 1.301, 95% confidence interval, 1.071-1.579, P = .008) and intensive care unit length of stay (incidence rate ratio 1.548, 95% confidence interval, 1.038-2.049, P = .030).

CONCLUSIONS

Multiple anesthesia handovers were not associated with an increased risk of serious morbidity for patients undergoing cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. However, increased handovers (≥2) between nonattending providers was associated with longer hospital and intensive care unit length of stays.

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.

An evidence synthesis on perioperative Handoffs: A call for balanced sociotechnical solutions

SIGNIFICANCE

Perioperative handoffs interconnect the preoperative, intraoperative, and postoperative phases underlying surgical care to maintain care continuity -yet are prone to coordination and communication failures.

OBJECTIVE

To synthesize evidence on factors affecting the safety and quality of perioperative handoff conduct and process.

MATERIALS AND METHODS

A search of PubMed, EMBASE, and CINAHL was conducted to include observational, descriptive studies of preoperative, intraoperative, and postoperative handoffs published in English language, peer-reviewed journals. Data analysis was informed by the Systems Engineering Initiative for Patient Safety (SEIPS) framework describing the relationship between the work-system, work processes, and outcomes. Study quality was assessed using the Quality Scoring System.

RESULTS

Twenty-three studies were included. Eighteen studies focused on postoperative handoffs, with one on preoperative, three on intraoperative and only one that looked at preoperative/postoperative handoffs combined. The SEIPS framework elucidated the complex inter-related factors (enablers and barriers) related to perioperative handoff safety. While some studies found that the use of standardized handoff tools and protocols and interdisciplinary teamwork were frequently-reported enablers, other studies identified the lack of structured handoff tools and protocols, poor teamwork and communication, and improper use of documentation tools were top-cited barriers affecting handoff quality. Suggestions to ensure handoff safety and quality included implementing structured handoff checklists and protocols and building interprofessional teamwork competencies for effective communication.

DISCUSSION AND CONCLUSION

Our review highlights an urgency to develop more holistic sociotechnical solutions that can create and sustain a balance between technical innovations in tools and technologies and the non-technical interventions/training needed to improve interpersonal relations and teamwork competencies - taken together, can improve the quality and safety of perioperative handoff practice.

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.

Systematic Review of Intraoperative Anesthesia Handoffs and Handoff Tools

Intraoperative handoffs between anesthesia clinicians are critical for care continuity. However, such handoffs pose a significant threat to patient safety. This systematic review synthesizes the empirical evidence on the (a) effect of intraoperative handoffs on outcomes and (b) effect of intraoperative handoff tools on outcomes. All studies on intraoperative handoffs and handoff tools published until September 2019, in any study setting and population, and with no prespecified criteria on the type of comparison and outcome were included. Data extracted from the included studies were aggregated to identify common patterns related to the type of surgery, clinician(s) involved, patient population, handoff tool, the tool design approach (where relevant), tool implementation strategies, and finally, all reported clinical and process outcomes. Quality of studies was assessed using the Newcastle-Ottawa Scale (NOS). Fourteen studies met the inclusion criteria. All included studies used adult patients. Eight studies were retrospective cohort studies that used administrative or electronic health record (EHR)-based databases to investigate the effects of intraoperative handoffs on morbidity and mortality. These studies included a total of 680,855 surgeries, with 139,426 of these surgeries having at least 1 handoff (20.47%). Seven of the studies found a positive association between intraoperative handoffs and considered outcomes. However, a pooled meta-analysis across these studies was not feasible across the retrospective studies due to differing surgical populations and varying definitions of the considered outcomes. Six studies used a nonrandomized prospective design to evaluate the effects of handoff tools on process-based outcomes such as clinician satisfaction, information transfer, handoff duration, and adherence. Five of the 6 handoff tools were checklist based. All prospective tool-based studies relied on small samples and reported a significant improvement on the considered process-based outcomes. The median quality score among retrospective (median [interquartile range {IQR}] = 9 [1]) was significantly higher than that of prospective (median [IQR] = 5 [1.5]) studies (U = 21, P = .0017). This systematic review provides a unique appraisal of the current state of intraoperative handoff research. To improve the quality and outcomes of handoffs, future efforts should focus on design and implementation of standardized handoff tools integrated within EHR systems, consider the use of similar metrics for evaluating handoff process and clinical outcomes, and improve the execution and reporting of studies using standard protocols and guidelines.

Surgical Start Time Impact on Hospital Length of Stay for Elective Inpatient Procedures

Background

Hospital length of stay (LOS) remains an important, albeit nonspecific, metric in the analysis of surgical services. Modifiable factors to reduce LOS are few in number and the ability to practically take action is limited. Surgical scheduling of elective cases remains an important task in optimizing workflow and may impact the post-surgical LOS.

Methods

Retrospective data from a single tertiary care academic institution were analyzed from elective adult surgical cases performed from 2017 through 2019. Emergent or urgent add-on cases were excluded. Variables included primary procedure, age, diabetes status, American Society of Anesthesiologists (ASA) class, and surgical start time. Analysis of the median LOS following surgery was performed using Mann-Whitney tests and Cox hazards model. Matched-cohort analysis of mean total hospitalization costs was performed using the Student’s t-test. 

Results

9,258 patients were analyzed across five surgical service lines, of which 777 patients had surgical start time after 3 PM. The median LOS for the after 3 PM group was 1 day longer than the before 3 PM start time cohort (3.0 vs 2.1, p < 0.001). Service line analysis revealed increased LOS for Orthopedics and Neurosurgery (3.0 vs 1.9, p < 0.001; 3.0 vs 2.0, p < 0.05). Multivariate analysis confirmed that start time before 3 PM predicted shorter LOS (HR = 1.214, 1.126-1.309; p < 0.001). Case-matched cost analysis for frequently performed orthopedic and neurosurgical cases with an after 3 PM start time failed to demonstrate a significant difference in total hospital charges. 

Conclusion

Optimization of surgical services scheduling to increase the proportion of elective surgical cases started before 3 PM has the potential to decrease post-surgical LOS for adult patients undergoing Orthopedic or Neurosurgical procedures. 

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.

[Safer anesthesia and duty hour limits: are handovers of personnel allowed?]

Restrictions of duty hours in medicine are an ambivalent matter with respect to patient safety. Continuity of treatment carries the risk of medical errors from declining performance capability and must be balanced against the risk of communication failure and information loss due to personnel changes. Complete intraoperative changes of anesthetists are frequently carried out in the clinical routine but possibly have the potential to negatively influence the postoperative morbidity and mortality. The relevance of anesthesiological care for the perioperative outcome also seems to vary depending on the specialist discipline involved. While standardized handover protocols seem to be only of limited effectiveness for the improvement of transfer of information, they are nevertheless a reasonable approach for optimization of interprofessional communication and reduction of treatment errors.

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.