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Background: Up to half of all surgical adverse events are due to non-technical errors, making non-technical skill assessment and improvement a priority. No specific tools are available to retrospectively identify non-technical errors that have occurred in surgical patient care. This original study aimed to develop and provide evidence of validity and inter-rater reliability for the System for Identification and Categorization of Non-technical Error in Surgical Settings (SICNESS)., Methods: A literature review, modified Delphi process, and two pilot phases were used to develop and test the SICNESS tool. For each pilot, 12 months of surgical mortality data from the Australian and New Zealand Audit of Surgical Mortality were assessed by two independent reviewers using the SICNESS tool. Main outcomes included tool validation through modified Delphi consensus, and inter-rater reliability for: non-technical error identification and non-technical error categorization using Cohen's κ coefficient, and overall agreement using Fleiss' κ coefficient., Results: Version 1 of the SICNESS was used for pilot 1, including 412 mortality cases, and identified and categorized non-technical errors with strong-moderate inter-rater reliability. Non-technical error exemplars were created and validated through Delphi consensus, and a novel mental model was developed. Pilot 2 included an additional 432 mortality cases. Inter-rater reliability was near perfect for leadership (κ 0.92, 95% c.i. 0.82 to 1.00); strong for non-technical error identification (κ 0.89, 0.84 to 0.93), communication and teamwork (κ 0.89, 0.79 to 0.99), and decision-making (κ 0.85, 0.79 to 0.92); and moderate for situational awareness (κ 0.79, 0.71 to 0.87) and overall agreement (κ 0.69, 0.66 to 0.73)., Conclusion: The SICNESS is a reliable and valid tool, enabling retrospective identification and categorization of non-technical errors associated with death, occurring in real surgical patient interactions., (© The Author(s) 2024. Published by Oxford University Press on behalf of BJS Foundation Ltd.)

Background: The Gompertz-Makeham law describes a characteristic pattern of mortality in human populations where the death rate is near constant between ages 18 and 30 yr (Makeham law) and rises exponentially thereafter (Gompertz law). This pattern has not been described in surgical populations, but if true, it would have important implications for understanding surgical risk and design and interpretation of surgical risk models. The aim of this study was to determine whether the Gompertz-Makeham law applies to perioperative mortality risk and the conditions under which it may apply., Methods: This study examined the relationship between age and 1-month postoperative all-cause mortality risk in a 10-yr New Zealand administrative dataset comprising 5,615,100 surgical procedures from 2007 to 2016. The dataset includes patient and surgical factors including procedures, American Society of Anesthesiologists (ASA; Schaumburg, Illinois) Physical Status score, diagnoses, and other relevant details. Semilogarithmic graphs of mortality risk and age were plotted. Linear regression models were fitted, with regression line slope and Pearson correlation coefficient calculated., Results: The primary outcome occurred in 114,782 (2.0%) of 5,615,100 included participants. The Gompertz-Makeham law seems to apply to the national surgical population as a whole (slope = 0.0241; R2 = 0.971). The law applies in all subgroups studied including sex, ASA Physical Status, surgical acuity, surgical severity category, cancer status, and ethnicity (slopes, 0.0066 to 0.0307; R2, 0.771 to 0.990). Important interactions were found between age, mortality risk, and three high-risk groups (cancer diagnosis, ASA Physical Status IV to V, and high surgical severity)., Conclusions: The Gompertz-Makeham law seems to apply in a national cohort of surgical patients. The inflection point for increased 1-month risk is apparent at age 30 yr. A strict exponential rise in mortality risk occurs thereafter. This finding improves the understanding of surgical risk and suggests a concept-driven approach to improve modeling of age and important interactions in future surgical risk models., (Copyright © 2024 American Society of Anesthesiologists. All Rights Reserved.)

Aim: To describe disparities in post-operative mortality experienced by Indigenous Māori compared to non-Indigenous New Zealanders., Methods: We completed a national study of all those undergoing a surgical procedure between 2005 and 2017 in New Zealand. We examined 30-day and 90-day post-operative mortality for all surgical specialties and by common procedures. We compared age-standardised rates between ethnic groups (Māori, Pacific, Asian, European, MELAA/Other) and calculated hazard ratios (HRs) using Cox proportional hazards regression modelling adjusted for age, sex, deprivation, rurality, comorbidity, ASA score, anaesthetic type, procedure risk and procedure specialty., Results: From nearly 3.9 million surgical procedures (876,976 acute, 2,990,726 elective/waiting list), we observed ethnic disparities in post-operative mortality across procedures, with the largest disparities occurring between Māori and Europeans. Māori had higher rates of 30- and 90-day post-operative mortality across most broad procedure categories, with the disparity between Māori and Europeans strongest for elective/waiting list procedures (eg, elective/waiting list musculoskeletal procedures, 30-day mortality: adj. HR 1.93, 95% CI 1.56-2.39)., Conclusions: The disparities we observed are likely driven by a combination of healthcare system, process and clinical team factors, and we have presented the key mechanisms within these factors., Competing Interests: Dr Ongley is Chair of the Perioperative Mortality Review Committee for HQSC. Dr McLeod reports grants from HRC during the conduct of this study.

Background: Preoperative risk prediction is important for guiding clinical decision-making and resource allocation. Clinicians frequently rely solely on their own clinical judgement for risk prediction rather than objective measures. We aimed to compare the accuracy of freely available objective surgical risk tools with subjective clinical assessment in predicting 30-day mortality., Methods and Findings: We conducted a prospective observational study in 274 hospitals in the United Kingdom (UK), Australia, and New Zealand. For 1 week in 2017, prospective risk, surgical, and outcome data were collected on all adults aged 18 years and over undergoing surgery requiring at least a 1-night stay in hospital. Recruitment bias was avoided through an ethical waiver to patient consent; a mixture of rural, urban, district, and university hospitals participated. We compared subjective assessment with 3 previously published, open-access objective risk tools for predicting 30-day mortality: the Portsmouth-Physiology and Operative Severity Score for the enUmeration of Mortality (P-POSSUM), Surgical Risk Scale (SRS), and Surgical Outcome Risk Tool (SORT). We then developed a logistic regression model combining subjective assessment and the best objective tool and compared its performance to each constituent method alone. We included 22,631 patients in the study: 52.8% were female, median age was 62 years (interquartile range [IQR] 46 to 73 years), median postoperative length of stay was 3 days (IQR 1 to 6), and inpatient 30-day mortality was 1.4%. Clinicians used subjective assessment alone in 88.7% of cases. All methods overpredicted risk, but visual inspection of plots showed the SORT to have the best calibration. The SORT demonstrated the best discrimination of the objective tools (SORT Area Under Receiver Operating Characteristic curve [AUROC] = 0.90, 95% confidence interval [CI]: 0.88-0.92; P-POSSUM = 0.89, 95% CI 0.88-0.91; SRS = 0.85, 95% CI 0.82-0.87). Subjective assessment demonstrated good discrimination (AUROC = 0.89, 95% CI: 0.86-0.91) that was not different from the SORT (p = 0.309). Combining subjective assessment and the SORT improved discrimination (bootstrap optimism-corrected AUROC = 0.92, 95% CI: 0.90-0.94) and demonstrated continuous Net Reclassification Improvement (NRI = 0.13, 95% CI: 0.06-0.20, p < 0.001) compared with subjective assessment alone. Decision-curve analysis (DCA) confirmed the superiority of the SORT over other previously published models, and the SORT-clinical judgement model again performed best overall. Our study is limited by the low mortality rate, by the lack of blinding in the 'subjective' risk assessments, and because we only compared the performance of clinical risk scores as opposed to other prediction tools such as exercise testing or frailty assessment., Conclusions: In this study, we observed that the combination of subjective assessment with a parsimonious risk model improved perioperative risk estimation. This may be of value in helping clinicians allocate finite resources such as critical care and to support patient involvement in clinical decision-making., Competing Interests: The authors have declared that no competing interests exist.

Background: Peer review of surgical deaths can identify deficits in individual and systemic delivery of healthcare, ultimately informing quality improvement., Methods: From 2008 to 2016, cases reported to the Australia and New Zealand Audit of Surgical Mortality were analysed. Variables associated with peer-judged adverse events were sought., Results: Of 21 045 cases evaluated, 24.8% incurred at least one adverse event judgement. The proportion of cases with reported adverse event significantly decreased over time. Following adjustment for demographic and clinical characteristics, significant negative patient-related associations were advanced age, greater American Society of Anesthesiologists grade, and neurological and malignant comorbidities. Significant associations were also found with systemic or organizational factors, including state/territory, surgical specialty and hospital regionality., Conclusion: Examination of this peer-reviewed database revealed systemic or organizational predictors of adverse events that may have implications for quality improvement at an institutional or jurisdictional level. The extent to which these associations are due to the peer-review process itself should be the focus of further research., (© 2019 Royal Australasian College of Surgeons.)

Background: Many multivariable models to calculate mortality risk after surgery are limited by insufficient sample size at development or by application to cohorts distinct from derivation populations. The aims of this study were to validate the Surgical Outcome Risk Tool (SORT) for a New Zealand population and to develop an extended NZRISK model to calculate 1-month, 1-year and 2-year mortality after non-cardiac surgery., Methods: Data from the New Zealand National Minimum Data Set for patients having surgery between January 2013 and December 2014 were used to validate SORT. A random 75 per cent split of the data was used to develop the NZRISK model, which was validated in the other 25 per cent of the data set., Results: External validation of SORT in the 360 140 patients who underwent surgery in the study period showed good discrimination (area under the receiver operating characteristic curve (AUROC) value of 0·906) but poor calibration (McFadden's pseudo-R 2 0·137, calibration slope 5·32), indicating it was invalid in this national surgical population. Internal validation of the NZRISK model, which incorporates sex and ethnicity in addition to the variables used in SORT for 1-month, 1-year and 2-year outcomes, demonstrated excellent discrimination with AUROC values of 0·921, 0·904 and 0·895 respectively, and excellent calibration (McFadden's pseudo-R 2 0·275, 0·308 and 0·312 respectively). Calibration slopes were 1·12, 1·02 and 1·02 respectively., Conclusion: The SORT performed poorly in this national population. However, inclusion of sex and ethnicity in the NZRISK model improved performance. Calculation of mortality risk beyond 30 days after surgery adds to the utility of this tool for shared decision-making., (© 2019 BJS Society Ltd Published by John Wiley & Sons Ltd.)

Background: A proposition for the Wellington hospital thrombosis service to manage periprocedure anticoagulation bridging was made after a number of cancellations and key incidents were caused by lack of a consistent management approach. We provided individual bridging assessments, with implementation, communication, and education. The only funded anticoagulants in New Zealand at that time were dabigatran, warfarin, and enoxaparin., Methods: On initiation of the bridging service, we prospectively collected data on 600 consecutive patients referred to the periprocedure bridging service between May 2015 and February 2017. We recorded the 30-day major bleeding events, thrombotic events, and related mortality. We followed the patients up for 30 days postprocedure. As part of this process, we ensured optimal transition back to their initial anticoagulant., Conclusion: We found low rates of major bleeding 1.9% and thrombosis 0.8% at day 30 comparable to randomized controlled trials. Of the 222 patients taking dabigatran experienced no major bleeding events. We believe using a specialist coagulation service is optimal to ensure surgery can proceed safely., (© 2019 International Society on Thrombosis and Haemostasis.)

Objective: The Victorian Audit of Surgical Mortality (VASM) is part of the Australian and New Zealand Audit of Surgical Mortality, aiming to identify factors associated with surgical mortality. A quality assurance method was utilised to rectify system issues through error rate checks of VASM data points. This method ensured data collected and entered in the audit database were accurate., Method: Clinical data was collected using case record forms (CRFs), entered from paper forms by VASM staff or by the surgeon into an online interface. Closed audited cases from 1 January 2012 to 31 December 2016 were analysed. From 5528 closed cases, 485 (8.8%) were reviewed, containing a total of 1117 CRFs and 169,789 data fields. Each CRF entered was visually inspected in the database against the source document by an independent audit staff member. The error rate for each period was calculated and considered acceptable below 10 per 10,000 fields., Results: Text errors made up the majority of data entry errors regardless of how the case was submitted., Conclusion: Application of error rate checks is beneficial to maintain good clinical data. This activity improved and streamlined the data collection process to reduce errors associated with data entry. Once the entry system was stabilised, a reduction in error rate was observed showing potential for further improvements. We acknowledge that errors cannot be entirely eliminated and it is unrealistic. By investigating the rigour of the data management processes based on research guidelines, the findings can contribute to improve quality of clinical audits., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objective: This article outlines the formation of the Australian and New Zealand Audit of Surgical Mortality (ANZASM) and describes its objectives, governance, functioning and challenges., Background: A nationwide audit of surgical mortality provides an overview of the leading causes of death in patients who require surgical care. It identifies system or process errors, trends in deficiency of care and helps develop strategies to reduce deaths in the surgical arena., Methods: A standardized tool is used to systematically collect data after every surgical death. Patient details are reviewed by a peer surgeon (and in certain cases a second) to identify issues with patient management and hospital processes. The treating surgeon is then offered confidential feedback and alternate views on patient management., Results: From January 2009 to December 2012, 19,096 deaths were reported to the ANZASM. Eighty-six percent of the audited deaths occurred in patients requiring an emergency admission. Significant criticism of patient care was reported in 13% of cases with 16% of clinical issues perceived to be preventable. Western Australia, which first began the audit process, has shown a 30% reduction in surgical deaths., Conclusions: Nationwide mortality audits are a useful and worthwhile exercise. Recommendations identified in the audit reports direct educational workshops and seminars to address these issues. They allow Departments of Health to make informed decisions in their hospitals. Through this model, and the lessons learnt, we would encourage other countries planning to set up their own audits to follow a similar concept.

Background: The Australian and New Zealand Audit of Surgical Mortality (ANZASM) is a nationwide confidential peer review of deaths associated with surgical care. This study assesses the concordance between treating surgeons and peer reviewers in reporting clinical events and delays in management., Methods: This is a retrospective cross-sectional analysis of deaths in 2009 and 2010. Cases that went through the process of submission of details by the surgeon in a structured surgical case form (SCF), first-line assessment (FLA) and a more detailed second-line assessment (SLA) were included. Significant clinical events reported for these patients were categorized and analysed for concordance., Results: Of the 11,303 notifications of death to the ANZASM, 6507 (57.6%) were audited and 685 (10.5%) required the entire review process. Nationally, the most significant events were post-operative complications, poor preoperative assessment and delay to surgery or diagnosis. The SCF submissions reported 338 events, as compared with 1009 and 985 events reported through FLA and SLA, respectively (P = 0.01). Treating surgeons and assessors attributed 29-30% of events to factors outside the surgeon's control. Surgeons felt that delay to surgery or diagnosis was a significant event in 6.6% of cases, in contrast to 20% by assessors (P = 0.01). Preoperative management could be improved in 19% of cases according to surgeons, compared with 45 and 36% according to the assessors (P < 0.001)., Conclusion: There is significant discordance between treating surgeons and assessors. This suggests the need for in-depth analysis and possible refinement of the audit process., (© 2014 Royal Australasian College of Surgeons.)

Background: In this study, the Australian and New Zealand Audit of Surgical Mortality evaluated the effect of operative supervision on certain post-operative outcomes in the surgical death subset., Methods: This retrospective cohort study was based upon mortality data collected in 2009 which included 1673 patients who died and had surgery within 30 days of death or during the last admission. Cases were divided into three groups: consultant not supervising (group NS), consultant supervising (group S) and consultant performing the operation (group C). A comparison was done nationally and between participating states in Australia. Certain post-operative outcomes were compared between the three groups as well as between elective and emergency operations., Results: There were significant variations in the levels of operative supervision among states in Australia. Group NS (n = 468) generally had more favourable post-operative outcomes than group S (n = 147) and group C (n = 1058), with post-operative complication rates of 24.8%, 37.4% and 40.9% for groups NS, S and C, respectively. The level of operative supervision in emergency operations was half that of elective operations. Nevertheless, the post-operative complications rate was significantly lower in emergency operations (30.6%) compared with elective operations (64.4%). The same trend was seen with clinical management deficiencies and unplanned return to theatre., Conclusion: Operative supervision in emergency setting within Australian hospitals appears to be potentially inadequate. However, the available data suggest that unsupervised surgery did not result in worse post-operative outcomes. In appropriately selected cases, the data support surgical registrars performing surgery without consultant supervision., (© 2012 The Authors. ANZ Journal of Surgery © 2012 Royal Australasian College of Surgeons.)

We conducted a prospective study of non-cardiac surgical patients aged 70 years or more in 23 hospitals in Australia and New Zealand. We studied 4158 consecutive patients of whom 2845 (68%) had pre-existing comorbidities. By day 30, 216 (5%) patients had died, and 835 (20%) suffered complications; 390 (9.4%) patients were admitted to the Intensive Care Unit. Pre-operative factors associated with mortality included: increasing age (80-89 years: OR 2.1 (95% CI 1.6-2.8), p < 0.001; 90+ years: OR 4.0 (95% CI 2.6-6.2), p < 0.001); worsening ASA physical status (ASA 3: OR 3.1 (95% CI 1.8-5.5), p < 0.001; ASA 4: OR 12.4 (95% CI 6.9-22.2), p < 0.001); a pre-operative plasma albumin < 30 g.l⁻¹ (OR: 2.5 (95% CI 1.8-3.5), p < 0.001); and non-scheduled surgery (OR 1.8 (95% CI 1.3-2.5), p < 0.001). Complications associated with mortality included: acute renal impairment (OR 3.3 (95% CI 2.1-5.0), p < 0.001); unplanned Intensive Care Unit admission (OR 3.1 (95% CI 1.9-4.9), p < 0.001); and systemic inflammation (OR 2.5 (95% CI 1.7-3.7), p < 0.001). Patient factors often had a stronger association with mortality than the type of surgery. Strategies are needed to reduce complications and mortality in older surgical patients., (© 2010 The Authors. Anaesthesia © 2010 The Association of Anaesthetists of Great Britain and Ireland.)