Association Between Handover of Anesthesia Care and Adverse Postoperative Outcomes Among Patients Undergoing Major Surgery | Anesthesiology | JAMA | JAMA Network
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Figure 1.  Cohort Build and Missing Data for Surgeries With Complete Handover vs No Handover
Cohort Build and Missing Data for Surgeries With Complete Handover vs No Handover

aBilling code for replacement anesthesiologist not used as intended (1 institution) refers to 1 Ontario institution which systematically billed the code used to define the main exposure in this study for an alternative purpose (ie, the postoperative care of patients with complicated medical needs in the postanesthetic care unit). Since it was not possible to positively determine which exposures among these patients were intraoperative vs postoperative, all patients who underwent surgery at this institution were excluded.

bTo move from the complete case cohort (256 424 patients) to the subgroup analysis cohort (308 014 patients), 51 670 patients missing data on years since graduation for the primary anesthesiologist were added to the complete case cohort, and 80 patients were subtracted who also had missing data on duration of surgery.

Figure 2.  Risk of Adverse Outcomes (Complete Intraoperative Handover of Anesthesia Care vs no Handover Groups) in the Prespecified Subgroups
Risk of Adverse Outcomes (Complete Intraoperative Handover of Anesthesia Care vs no Handover Groups) in the Prespecified Subgroups

See Statistical Analysis for calculation methods of subgroup effects. Because of missing data, years since graduation for the primary anesthesiologist was excluded as a covariate in these analyses (Figure 1).

aData were plotted in the year the fiscal year ended (end date, March 31).

bSmall cell sizes (≤5) cannot be reported and were obscured to create ambiguity.

Table 1.  Baseline Characteristics of the Patients Before and After Inverse Probability of Exposure Weightinga
Baseline Characteristics of the Patients Before and After Inverse Probability of Exposure Weightinga
Table 2.  Main Outcomes in the Study Cohorta
Main Outcomes in the Study Cohorta
Table 3.  Details of Complications (Exploratory Analyses)a
Details of Complications (Exploratory Analyses)a
1.
Vandenbroucke  JP, von Elm  E, Altman  DG,  et al; STROBE Initiative.  Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration.  PLoS Med. 2007;4(10):e297.PubMedGoogle ScholarCrossref
2.
Benchimol  EI, Smeeth  L, Guttmann  A,  et al; RECORD Working Committee.  The reporting of studies conducted using observational routinely-collected health data (RECORD) statement.  PLoS Med. 2015;12(10):e1001885-e22.PubMedGoogle ScholarCrossref
3.
Irony  TZ.  The “utility” in composite outcome measures: measuring what is important to patients.  JAMA. 2017;318(18):1820-1821.PubMedGoogle ScholarCrossref
4.
Austin  PC.  The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies.  Stat Med. 2010;29(20):2137-2148.PubMedGoogle ScholarCrossref
5.
Haukoos  JS, Lewis  RJ.  The propensity score.  JAMA. 2015;314(15):1637-1638.PubMedGoogle ScholarCrossref
6.
Ukoumunne  OC, Williamson  E, Forbes  AB, Gulliford  MC, Carlin  JB.  Confounder-adjusted estimates of the risk difference using propensity score–based weighting.  Stat Med. 2010;29(30):3126-3136..PubMedGoogle ScholarCrossref
7.
Austin  PC, Stuart  EA.  Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.  Stat Med. 2015;34(28):3661-3679.PubMedGoogle ScholarCrossref
8.
Sterne  JAC, White  IR, Carlin  JB,  et al.  Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.  BMJ. 2009;338:b2393.PubMedGoogle ScholarCrossref
9.
Howard  SK, Rosekind  MR, Katz  JD, Berry  AJ.  Fatigue in anesthesia: implications and strategies for patient and provider safety.  Anesthesiology. 2002;97(5):1281-1294.PubMedGoogle ScholarCrossref
10.
Ahmed  N, Devitt  KS, Keshet  I,  et al.  A systematic review of the effects of resident duty hour restrictions in surgery: impact on resident wellness, training, and patient outcomes.  Ann Surg. 2014;259(6):1041-1053.PubMedGoogle ScholarCrossref
11.
Hudson  CCC, McDonald  B, Hudson  JKC, Tran  D, Boodhwani  M.  Impact of anesthetic handover on mortality and morbidity in cardiac surgery: a cohort study.  J Cardiothorac Vasc Anesth. 2015;29(1):11-16.PubMedGoogle ScholarCrossref
12.
Hyder  JA, Bohman  JK, Kor  DJ,  et al.  Anesthesia care transitions and risk of postoperative complications.  Anesth Analg. 2016;122(1):134-144.PubMedGoogle ScholarCrossref
13.
Saager  L, Hesler  BD, You  J,  et al.  Intraoperative transitions of anesthesia care and postoperative adverse outcomes.  Anesthesiology. 2014;121(4):695-706.PubMedGoogle ScholarCrossref
14.
Terekhov  MA, Ehrenfeld  JM, Dutton  RP, Guillamondegui  OD, Martin  BJ, Wanderer  JP.  Intraoperative care transitions are not associated with postoperative adverse outcomes.  Anesthesiology. 2016;125(4):690-699.PubMedGoogle ScholarCrossref
15.
Tenedios  CN, O’Leary  SJ, Desai  SP.  A Historical Examination of Nurse Anesthesia Practice in the United States and Other G-7 Countries.  J Anesth Hist. 2016;2(3):120. doi:10.1016/j.janh.2016.03.019Google ScholarCrossref
16.
Weiser  TG, Haynes  AB, Molina  G,  et al.  Estimate of the global volume of surgery in 2012: an assessment supporting improved health outcomes.  Lancet. 2015;385(suppl 2):S11.PubMedGoogle ScholarCrossref
17.
Weir  E, Schabas  R, Wilson  K, Mackie  C.  A Canadian framework for applying the precautionary principle to public health issues.  Can J Public Health. 2010;101(5):396-398.PubMedGoogle Scholar
18.
Abraham  J, Kannampallil  T, Patel  VL.  A systematic review of the literature on the evaluation of handoff tools: implications for research and practice.  J Am Med Inform Assoc. 2014;21(1):154-162.PubMedGoogle ScholarCrossref
Original Investigation
January 9, 2018

Association Between Handover of Anesthesia Care and Adverse Postoperative Outcomes Among Patients Undergoing Major Surgery

Author Affiliations
  • 1Department of Anesthesia and Perioperative Medicine, University of Western Ontario, London, Ontario, Canada
  • 2Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada
  • 3Institute of Clinical Evaluative Sciences, Western Site (ICES Western), London, Ontario, Canada
  • 4Arthur Labatt School of Nursing, University of Western Ontario, London, Ontario, Canada
  • 5Department of Surgery, University of Western Ontario, London, Ontario, Canada
  • 6Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Ontario, Canada
  • 7Department of Anesthesia and Pain Management, Toronto General Hospital, Toronto, Ontario, Canada
  • 8Department of Anesthesia, University of Toronto, Toronto, Ontario, Canada
  • 9Institute of Clinical Evaluative Sciences, Central Site (ICES Central), Toronto, Ontario, Canada
  • 10Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
JAMA. 2018;319(2):143-153. doi:10.1001/jama.2017.20040
Key Points

Question  Is there an association between complete intraoperative handover of anesthesia care and adverse postoperative outcomes?

Findings  In this retrospective cohort study that included 313 066 adults undergoing major surgery, complete intraoperative handover of anesthesia care compared with no handover was significantly associated with a higher risk of a composite of all-cause death, hospital readmission, or major postoperative complications over 30 days (44% vs 29%).

Meaning  Complete handover of intraoperative anesthesia care was associated with adverse postoperative outcomes.

Abstract

Importance  Handing over the care of a patient from one anesthesiologist to another occurs during some surgeries and might increase the risk of adverse outcomes.

Objective  To assess whether complete handover of intraoperative anesthesia care is associated with higher likelihood of mortality or major complications compared with no handover of care.

Design, Setting, and Participants  A retrospective population-based cohort study (April 1, 2009-March 31, 2015 set in the Canadian province of Ontario) of adult patients aged 18 years and older undergoing major surgeries expected to last at least 2 hours and requiring a hospital stay of at least 1 night.

Exposure  Complete intraoperative handover of anesthesia care from one physician anesthesiologist to another compared with no handover of anesthesia care.

Main Outcomes and Measures  The primary outcome was a composite of all-cause death, hospital readmission, or major postoperative complications, all within 30 postoperative days. Secondary outcomes were the individual components of the primary outcome. Inverse probability of exposure weighting based on the propensity score was used to estimate adjusted exposure effects.

Results  Of the 313 066 patients in the cohort, 56% were women; the mean (SD) age was 60 (16) years; 49% of surgeries were performed in academic centers; 72% of surgeries were elective; and the median duration of surgery was 182 minutes (interquartile [IQR] range, 124-255). A total of 5941 (1.9%) patients underwent surgery with complete handover of anesthesia care. The percentage of patients undergoing surgery with a handover of anesthesiology care progressively increased each year of the study, reaching 2.9% in 2015. In the unweighted sample, the primary outcome occurred in 44% of the complete handover group compared with 29% of the no handover group. After adjustment, complete handovers were statistically significantly associated with an increased risk of the primary outcome (adjusted risk difference [aRD], 6.8% [95% CI, 4.5% to 9.1%]; P < .001), all-cause death (aRD, 1.2% [95% CI, 0.5% to 2%]; P = .002), and major complications (aRD, 5.8% [95% CI, 3.6% to 7.9%]; P < .001), but not with hospital readmission within 30 days of surgery (aRD, 1.2% [95% CI, −0.3% to 2.7%]; P = .11).

Conclusions and Relevance  Among adults undergoing major surgery, complete handover of intraoperative anesthesia care compared with no handover was associated with a higher risk of adverse postoperative outcomes. These findings may support limiting complete anesthesia handovers.

Introduction

Handovers of anesthesia care from one anesthesiologist to another can occur intraoperatively due to personal or professional commitments, illness, or fatigue. Handovers can be temporary (initial clinician hands over care to another clinician for a break and then returns) or complete (initial clinician hands over care completely to another clinician and is no longer available).

During handovers, the outgoing clinician must communicate important facts about the patient and the surgery to the incoming clinician while continuing to provide patient care. This is a potentially vulnerable time for the patient because all information required for safe anesthesia care must be transferred between clinicians in a busy environment with many distractions. If crucial details are omitted, the patient may be at increased risk of adverse events. Alternatively, a sufficiently rested clinician taking over for a fatigued clinician may improve quality of care and result in fewer adverse events.

Uncertainty regarding the effect of intraoperative anesthesia handovers on mortality and major morbidity continues to exist. The hypothesis of this large, population-based, multicenter observational study was that the complete intraoperative handover of anesthesia care from one anesthesiologist to another was not associated with higher mortality or major complications up to 30 days postoperatively, relative to the standard case of anesthesia care.

Methods
Study Design, Setting, and Data Sources

Quiz Ref IDThis population-based, retrospective cohort study used administrative health care data from the Canadian province of Ontario and followed the STROBE (strengthening the reporting of observational studies in epidemiology)1 and RECORD (reporting of studies conducted using observational routinely collected health data)2 reporting guidelines. All residents of Ontario (approximately 14 million) obtain health care services from a government-administered single-payer system. A unique, encoded identifier permitted linkage across several administrative databases, which were then analyzed at the Institute for Clinical Evaluative Sciences (ICES). Data were obtained from the Canadian Institute for Health Information’s Discharge Abstract Database (CIHI-DAD; in-hospital outcomes), the National Ambulatory Care Reporting System (CIHI-NACRS; emergency department [ED] visits), the Same Day Surgery Database (CIHI-SDS), the Ontario Health Insurance Plan (physician billings), the Corporate Provider Database (physician demographic data from Ontario’s Ministry of Health and Long-Term Care), and the Registered Persons Database (patient demographics and vital status). Ethics approval was granted through the Sunnybrook Health Sciences Centre Research Ethics Board (Toronto, Ontario), which waived the requirement for informed consent from participants.

Participants

Adult patients (≥18 years) were identified who underwent major surgeries expected to have duration of at least 2 hours and require postoperative admission to hospital for at least 1 night between April 1, 2009, and March 31, 2015. Major surgeries were targeted within the broad subgroup domains of neurosurgery; cardiac; vascular; thoracic; and abdominal, pelvic, and urologic surgery, as identified by surgeon experts using Canadian Classification of Health Intervention (CCI) codes (eTable 1 in the Supplement).

Patients having multiple surgeries within the accrual period were only included in the cohort for their first eligible surgery. Patients who had surgery within the same surgical subgroup within the previous year were excluded to reduce the probability of complicated surgeries requiring revision or reoperation soon after initial operations (patients were still included if they had surgeries within another surgical subgroup at any time or within the same subgroup if more than 1 year had passed after the previous surgery). In addition, after examining the initial cohort, it was discovered that one Ontario institution systematically billed the code used to define the main exposure in this study for an alternative purpose—specifically, the postoperative care of patients requiring complicated care in the postanesthetic care unit. Because it could not be positively determined which exposures were intraoperative vs postoperative, all patients who had surgery at this institution were excluded (Figure 1).

Exposure of Interest

Quiz Ref IDThe exposure of interest in this study was the complete intraoperative handover of anesthesia care from one physician anesthesiologist (the primary anesthesiologist) to another physician anesthesiologist (the replacement anesthesiologist). In Ontario, this transition is specifically captured by a unique billing code (E005C). This code is submitted by the replacement anesthesiologist and identifies a surgery in which a replacement anesthesiologist entirely took over a case from the primary anesthesiologist. This billing code was expected to be accurate since it is the only mechanism used to remunerate the replacement anesthesiologist. Patients were considered to be exposed to a complete handover if the code was billed on the day of surgery or the day after surgery (to account for handovers occurring after midnight).

Outcomes

The primary outcome was a composite3 of all-cause death, readmission to any hospital in the province, or major postoperative complications, all within 30 days of the index surgery. Secondary outcomes were the 3 separate components of the primary outcome, the incidence of postoperative intensive care unit (ICU) admission, hospital length of stay, and the number of ED visits in Ontario within 90 days of the index surgery.

Major complications were defined by CCI intervention codes, International Classification of Diseases, Tenth Revision (ICD-10) diagnostic codes, and the Ontario Health Insurance Plan physician billings (eTable 2 in the Supplement). Major complications were only included if they were diagnosed for the first time postoperatively (ie, atrial fibrillation present before surgery was not counted as a complication). All outcomes were specified a priori.

Statistical Analysis

Analyses were conducted using Stata version 15. Patients in the exposed (handover) and nonexposed (no handover) groups were likely to differ systematically due to confounding by indication. For example, it was probable that handovers occurred more commonly during longer-duration surgeries. Therefore, we controlled for measured confounding using inverse probability of exposure weighting (IPEW) based on propensity scores.4,5 The propensity score was estimated using multivariable logistic regression with receipt of a handover as the dependent variable and covariates decided upon a priori as the independent variables (sex, age, comorbidities with a 5-year look-back window [hypertension, coronary artery disease, congestive heart failure, peripheral vascular disease, diabetes, previous stroke or transient ischemic attack, chronic liver disease, cancer, chronic renal disease, and chronic obstructive pulmonary disease], duration of the surgery [reported in deciles], years since medical school graduation for the primary anesthesiologist, region within the province, type of hospital [academic or not], whether the surgery was elective or urgent/emergent, and the type of surgery [eTable 3 in the Supplement]). Observations were then weighted according to the inverse of the calculated probability of receiving the exposure that the participant actually received and analyzed using the teffects ipw package in Stata. Results were expressed as potential outcome means (which reflect the outcomes in the inverse probability of exposure-weighted pseudosample6), adjusted risk differences (aRDs), and adjusted relative risks (aRRs). The balance of covariates pre- and postweighting was assessed using standardized differences.7 For the primary analysis, planned a priori, complete case analysis was implemented when data were missing.

A priori subgroup analysis was planned for the fiscal year of surgery, whether the surgery was elective vs urgent/emergent, and for major surgical subgroup. Homogeneity of subgroup effects were tested via a test of interaction. Results were assessed for robustness to analytical technique by reanalyzing the main outcomes with the following methods: (1) multivariable logistic regression; (2) a doubly robust IPEW with regression adjustment model4 (using the Stata teffects ipwra package); (3) IPEW after excluding the variable with the most missing data (years since medical graduation for the primary anesthesiologist [for which no administrative data were available for fiscal year 2015]); (4) IPEW after adding calendar year of surgery as a covariate; (5) median imputation for missing data for duration of surgery (ie, the median duration of surgery for each surgical subtype was imputed into each record that was missing duration of surgery according to the type of surgery the patient underwent); and (6) multiple imputation for missing data for surgical duration and years since medical school graduation for the primary anesthesiologist (using a multivariate normal regression, iterative Markov chain Monte Carlo method [using the Stata mi impute mvn package and incorporating all covariates in the imputation model including the primary outcome8] to calculate 20 multiply imputed data sets). Reanalysis of the primary outcome was performed after incorporating age and duration of surgery into the analysis as polynomial variables. A P value of less than .05 was considered statistically significant. All hypothesis tests were 2-sided. No corrections were made for multiple comparisons, therefore the comparisons of individual complications between exposure groups were interpreted as exploratory analyses.

Results
Patients

This study included 313 066 patients (307 125 in the no handover group; 5941 in the complete handover group) (Figure 1). There were missing data for 2 variables: 51 670 (16.5%) patients were missing data on years since medical school graduation for the primary anesthesiologist, and 5052 (1.6%) patients were missing data on the duration of surgery (Figure 1). The total number of complete handovers for all surgeries (ie, not just the surgeries meeting inclusion criteria for this cohort study) in Ontario from 2004 until 2015 increased every year as did the yearly percentage of patients in this cohort whose surgery had a complete handover during the study period (eFigure in the Supplement). Important baseline differences between the no handover and complete handover groups were noted on several characteristics (Table 1).

Unadjusted Main Outcomes

The primary outcome (all-cause death, hospital readmission, or major complication within 30 days of the index surgery) occurred in 90 306 (29%) of the no handover group and in 2583 (44%) of the complete handover group (risk difference [RD], 14.1% [95% CI, 12.8% to 15.3%]). Having a complete handover was associated with worse outcomes for each component of the primary outcome (Table 2). The mean hospital length of stay was longer in the complete handover group as was the mean number of ED visits within 90 days of the index surgery, postoperative admissions to an ICU, and the proportion of the study cohort with any ED visit (Table 2).

Adjusted Main Outcomes

After adjustment, a complete handover of anesthesia care remained statistically significantly associated with an increased incidence of the primary outcome (Table 2; adjusted risk difference [aRD], 6.8% [95% CI, 4.5% to 9.1%]) and an increase in all-cause death and major complications within 30 days of the index surgery but not with hospital readmissions. The mean hospital length of stay was longer in the complete handover group, as was the incidence of postoperative ICU admission (Table 2).

Sensitivity Analyses

Across multiple sensitivity analyses, similar point estimates and 95% CIs were found, including when the variable with the most missing data was excluded from the statistical models (allowing for analysis of 308 014 patients), when multiple imputation was performed (allowing for analysis of 313 066 patients), and when age and/or duration of surgery were incorporated into the analysis as polynomial variables (eTable 4 and eTable 5 in the Supplement).

Secondary Outcomes

After adjustment in exploratory analyses, complete handover was statistically significantly associated with a higher incidence of postoperative ventilation for 48 hours or more, a major disruption of the surgical wound, bleeding, pneumonia, an unplanned return to the operating room, and new-onset hemodialysis (Table 3).

Subgroup Analyses

In subgroup analyses, heterogeneity was observed in the subgroup of year of surgery for the hospital readmission and major complication outcomes, for the subgroup of type of surgery for the primary outcome, and for the all-cause death and major complication outcomes. No statistically significant heterogeneity was observed between elective or urgent/emergent surgeries (Figure 2; and eTable 6 in the Supplement).

Discussion

Quiz Ref IDIn this large population-based study, a clinically important and statistically significant detrimental association between the complete handover of anesthesia care during major surgery and adverse postoperative outcomes was found. On average, for every 15 patients exposed to a complete anesthesia handover, 1 additional patient would be expected to experience the primary outcome. Intraoperative handovers were also associated with an increase in ICU admissions and longer hospital lengths of stay.

In Ontario, the absolute number of complete handovers is increasing year-by-year. Knowing that fatigue exacerbates many human limitations,9 some departments have implemented policies of restricted duty hours for medical staff, residents, or both.10 It is likely that these policies have some effect on the increase in the volume of handovers (since the policies may require anesthesiologists to hand over the care of more partially completed surgeries to colleagues when their working hours end).

Previous studies were from single institutions and included patients undergoing either narrow11,12 or broad13,14 ranges of surgeries. Three studies11-13 had CIs for the primary outcome that were consistent with a significant association between handovers and harm, the largest of which13 found that each anesthesia care transition was associated with increased odds of in-hospital mortality and major complications (odds ratio 1.08 for each transition [95% CI, 1.05 to 1.10]). The fourth study14 was compatible with the others since its 95% CI for the odds of the primary outcome (0.90 to 1.02), while not statistically significant, included a potentially clinically important effect. Most studies were conducted in the United States, where anesthesia care involves certified registered nurse anesthetists, physicians, or both. This differs from some other countries including Canada,15 where physicians typically care for one patient directly.

The congruity of these results with the majority of the previous research suggests that anesthesia handovers during major surgeries are associated with unintended harmful consequences. If the percentage of handovers observed in the final year of this study cohort (2.9%) were reflected worldwide, more than 9 million patients per year would potentially undergo surgery with a complete anesthesia handover.16 Given the large number of patients and the increase in adverse outcomes observed in this study, the public health implications of its findings are concerning. The most prudent approach at the current time may therefore be to invoke the precautionary principle17 and minimize unnecessary anesthesia handovers until future research has demonstrated that these harmful associations have been attenuated. However, determining which handovers are unnecessary remains a significant challenge. For example, since fatigue will, at some point, have a measureable and detrimental effect on clinicians,9 handovers performed for reasons of fatigue may be reasonable. Determining when the risk of a fatigued clinician exceeds the potential risk of a complete handover is an important subject for future research.

Quiz Ref IDIt is possible that an improved system of anesthesia handovers (in which critical components of handovers are mandated by a checklist) would eliminate the signal of harm while maintaining lifestyle benefits for clinicians. Although attempts to improve the quality of handovers are common and invoke many differing theoretical frameworks (eg, information processing, stereotypical narratives, distributed cognition), no unified approach has been identified.18 The potential for important intangible information loss during handover remains a latent threat. Attempting to demonstrate improved outcomes with the use of handover tools is an important area of research.

Subgroup analyses demonstrated statistical evidence of heterogeneity for some of the outcomes, particularly for the type of surgery performed. However, the majority of point estimates indicate an association between handovers and both the primary and all-cause death outcomes. Although the absolute risks of these outcomes may differ among surgery types, these results indicate consistent findings of harm among most subgroups.

A strength of this study is its large sample of patients representing a wide variety of surgeries at many hospitals. This is important since the majority of previous studies excluded important patient populations (often cardiac surgery) and were conducted at single centers. Many outcome events occurred, increasing the statistical power to detect important differences. Because this was a population-based study based in the largest Canadian province, patients in this cohort are likely representative of other Canadians in terms of sex, age, socioeconomic groups, comorbidity distributions, and other important prognostic factors. Unlike other countries where there are distinct regional differences in anesthesia practice (eg, the use of nurse anesthetists), this cohort involved only physician anesthesiologists. This allowed the research to focus more directly on the issue of handovers rather than on the types of clinicians involved.

Quiz Ref IDThis study has several limitations. Because the exposure of complete handover was determined using a billing code, there is a risk of misclassification if the code was used improperly. ICD-10 diagnostic codes may not have captured all adverse postoperative outcomes. The primary anesthesiologist’s career experience was controlled for, but the career experience of the replacement anesthesiologist and the surgeon was not. It was not possible to determine the precise time of handover because this information was not captured by physician billings, which limited the ability to investigate the effect of the handover’s time of day on outcomes. Cases in which a primary anesthesiologist had the assistance of a second anesthesiologist or took breaks during an operation and then returned to the operating room were not identified; nor was the presence of anesthesia trainees during the surgeries.

Conclusions

Among adults undergoing major surgery, complete handover of intraoperative anesthesia care compared with no handover was associated with a higher risk of adverse postoperative outcomes. These findings may support limiting complete anesthesia handovers.

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Article Information

Corresponding Author: Philip M. Jones, MD, Room C3-110, University Hospital-London Health Sciences Centre, 339 Windermere Rd, London, ON, Canada N6A 5A5 (philip.jones@lhsc.on.ca).

Accepted for Publication: November 30, 2017.

Author Contributions: Ms Allen and Dr Jones had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: Jones, Allen, Bray Jenkyn, Shariff, Flier, Vogt, Wijeysundera.

Drafting of the manuscript: Jones.

Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Jones, Allen.

Obtained funding: Jones.

Administrative, technical, or material support: Cherry, Bray Jenkyn, Shariff, Vogt, Wijeysundera.

Supervision: Shariff, Wijeysundera.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: Dr Wijeysundera is supported in part by a New Investigator Award from the Canadian Institutes of Health Research and a Merit Award from the Department of Anesthesia at the University of Toronto. This study was supported by the Department of Anesthesia and Perioperative Medicine at the University of Western Ontario. This project was conducted at the Institute for Clinical Evaluative Sciences (ICES) Western Site. ICES is funded by annual grants from the Ontario Ministry of Health and Long-term Care (MOHLTC). Core funding for ICES Western is provided by the Academic Medical Organization of Southwestern Ontario (AMOSO), the Schulich School of Medicine and Dentistry (SSMD), The University of Western Ontario, and the Lawson Health Research Institute (LHRI).

Role of the Funder/Sponsor: Neither the ICES nor the Ontario MOHLTC had a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Disclaimer: The opinions, results, and conclusions are those of the authors and are independent from the funding sources. No endorsement by ICES, AMOSO, SSMD, LHRI, or the MOHLTC is intended or should be inferred. Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions, and statements expressed in the material are those of the authors, and not necessarily those of CIHI.

Additional Contributions: The statistical code was verified by Lihua Li, PhD (Senior Biostatistician at ICES Western) and we would like to thank her for this contribution. She did not receive any compensation for her contribution.

References
1.
Vandenbroucke  JP, von Elm  E, Altman  DG,  et al; STROBE Initiative.  Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration.  PLoS Med. 2007;4(10):e297.PubMedGoogle ScholarCrossref
2.
Benchimol  EI, Smeeth  L, Guttmann  A,  et al; RECORD Working Committee.  The reporting of studies conducted using observational routinely-collected health data (RECORD) statement.  PLoS Med. 2015;12(10):e1001885-e22.PubMedGoogle ScholarCrossref
3.
Irony  TZ.  The “utility” in composite outcome measures: measuring what is important to patients.  JAMA. 2017;318(18):1820-1821.PubMedGoogle ScholarCrossref
4.
Austin  PC.  The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies.  Stat Med. 2010;29(20):2137-2148.PubMedGoogle ScholarCrossref
5.
Haukoos  JS, Lewis  RJ.  The propensity score.  JAMA. 2015;314(15):1637-1638.PubMedGoogle ScholarCrossref
6.
Ukoumunne  OC, Williamson  E, Forbes  AB, Gulliford  MC, Carlin  JB.  Confounder-adjusted estimates of the risk difference using propensity score–based weighting.  Stat Med. 2010;29(30):3126-3136..PubMedGoogle ScholarCrossref
7.
Austin  PC, Stuart  EA.  Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies.  Stat Med. 2015;34(28):3661-3679.PubMedGoogle ScholarCrossref
8.
Sterne  JAC, White  IR, Carlin  JB,  et al.  Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.  BMJ. 2009;338:b2393.PubMedGoogle ScholarCrossref
9.
Howard  SK, Rosekind  MR, Katz  JD, Berry  AJ.  Fatigue in anesthesia: implications and strategies for patient and provider safety.  Anesthesiology. 2002;97(5):1281-1294.PubMedGoogle ScholarCrossref
10.
Ahmed  N, Devitt  KS, Keshet  I,  et al.  A systematic review of the effects of resident duty hour restrictions in surgery: impact on resident wellness, training, and patient outcomes.  Ann Surg. 2014;259(6):1041-1053.PubMedGoogle ScholarCrossref
11.
Hudson  CCC, McDonald  B, Hudson  JKC, Tran  D, Boodhwani  M.  Impact of anesthetic handover on mortality and morbidity in cardiac surgery: a cohort study.  J Cardiothorac Vasc Anesth. 2015;29(1):11-16.PubMedGoogle ScholarCrossref
12.
Hyder  JA, Bohman  JK, Kor  DJ,  et al.  Anesthesia care transitions and risk of postoperative complications.  Anesth Analg. 2016;122(1):134-144.PubMedGoogle ScholarCrossref
13.
Saager  L, Hesler  BD, You  J,  et al.  Intraoperative transitions of anesthesia care and postoperative adverse outcomes.  Anesthesiology. 2014;121(4):695-706.PubMedGoogle ScholarCrossref
14.
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