The Australian and New Zealand Audit of Surgical Mortality (ANZASM) is a Health Department funded program that is managed by the Royal Australasian College of Surgeons (RACS) and provides for the independent evaluation of the surgical care to patients that have died in hospital. The assessment process is summarised in the figure below (Figure 1). The assessment process begins when ANZASM is notified of a case that fulfills our inclusion criteria:

  • A patient has died in hospital having been admitted under the care of a surgeon, regardless of whether a procedure took place or,

  • A patient has died in hospital having been admitted to hospital and undergoes a procedure performed by a surgeon.

Following notification, ANZASM creates a case and the consultant surgeon provide details through an online form that is submitted through the Fellow’s Interface. These details then undergo independent assessment, including progression to case note review where necessary. Feedback is provided to the treating surgeon. The data collected from this process is subsequently analysed and disseminated through our various reports. The data contained in the current report is accurate (as of 03 November 2025) and covers the period 01 January 2023 to 31 December 2024. NSW data was unavailable for the current report.

Figure 1: Case progression through the ANZASM evaluation process

Abbreviation
Abbreviation Name
ANZASM Australian and New Zealand Audit of Surgical Mortality
ACTASM Australian Capital Territory Audit of Surgical Mortality
NTASM Northern Territory Audit of Surgical Mortality
QASM Queensland Audit of Surgical Mortality
SAASM South Australian Audit of Surgical Mortality
TASM Tasmanian Audit of Surgical Mortality
VASM Victorian Audit of Surgical Mortality
WAASM Western Australian Audit of Surgical Mortality

The evaluation process begins when ANZASM is notified of a death. Figure 2 summarises the time taken for notification of a patient death (fulfilling our inclusion criteria) to ANZASM. ANZASM creates a case and contacts the treating surgeon within 24 hours of notification. For the data contained in the current report, hospitals notify ANZASM of patient deaths on a monthly basis.

Once notified of a case surgeons submit the required surgical case form within 60 days. Figure 3 summarises the time taken for surgeons to submit their surgical case form.

Statistical Process Control (SPC) charts can be used to present data over time and allow for determinations to be made as to whether changes in a particular metric represent seasonal variation or are in response to a specific cause.

Pattern

Pattern symbol

Pattern summary

SPC – Astronomical Point

≒

An identified point that exceeds 3 sigma limits from the mean

SPC – Trend (5)

ⓣ

5 consecutively increasing or decreasing points

SPC – Two in Three

⅔

2 out of 3 consecutive points exceeding 2 sigma limits from the mean

SPC – Shift (7)

ⓢ

7 consecutive points above or below the mean

Multiple elements comprise the SPC charts:

  • 2 sigma (2σ) limits are displayed as dotted lines, representing 95% warning limits
  • 3 sigma (3σ) limits are displayed as dashed lines, representing 99.8% control limits
  • dark solid line represents the centreline, indicating the mean value of observed counts for ANZASM
  • blue dot represents improvement or a favourable direction
  • orange dot represents an unfavourable pattern
  • grey dot in the SPC chart represents the actual observed value
  • black dot in the funnel plot denotes the sites or hospitals included in the analysis
  • NHS icon (located at top right corner of the SPC chart) summarises the overall performance pattern over the entire period. An orange ( ) indicates potential special cause deterioration (i.e. in response to a special cause) while a blue ( ) indicates potential special cause improvement.

Detailed guidance on the Making Data Count approach can be found on the Making Data Count website.

Figure 2a: Duration from patient death to notification of ANZASM and case creation
Figure 2b: Duration from patient death to notification of each region and case creation
Figure 3a: Duration from surgeon notification to submission of the surgical case form to ANZASM
Figure 3b: Duration from surgeon notification to submission of the surgical case form to regional ASM

The current status of cases as they progress through the ANZASM evaluation process is summarised in Figure 4. Terminal care cases do not undergo the full evaluation process as patients were transitioned to palliative care shortly after admission and no surgical intervention took place.

Figure 4a: ANZASM case evaluation status according to year of patient death, 2023
Figure 4b: ANZASM case evaluation status according to year of patient death, 2024

The distribution of all notified ANZASM cases across surgical specialties is reported in Figure 5.

Figure 5: Proportion of all cases notified to ANZASM, 2023–2024

Note: Specialties with ≤ 5 cases were grouped into ‘Other’: Obstetrics & Gynaecology, Ophthalmology, Oral/Maxillofacial Surgery, Otolaryngology Head and Neck Surgery, Paediatric Surgery and Plastic Surgery.

The time taken to complete the evaluation process (from case creation to case closure and feedback to surgeons) is summarised in Figure 6. ANZASM cases that have completed the evaluation process as of 03 November 2025 will form the basis of the remaining analyses in this report.

Statistical Process Control (SPC) charts can be used to present data over time and allow for determinations to be made as to whether changes in a particular metric represent seasonal variation or are in response to a specific cause.

Pattern

Pattern symbol

Pattern summary

SPC – Astronomical Point

≒

An identified point that exceeds 3 sigma limits from the mean

SPC – Trend (5)

ⓣ

5 consecutively increasing or decreasing points

SPC – Two in Three

⅔

2 out of 3 consecutive points exceeding 2 sigma limits from the mean

SPC – Shift (7)

ⓢ

7 consecutive points above or below the mean

Multiple elements comprise the SPC charts:

  • 2 sigma (2σ) limits are displayed as dotted lines, representing 95% warning limits
  • 3 sigma (3σ) limits are displayed as dashed lines, representing 99.8% control limits
  • dark solid line represents the centreline, indicating the mean value of observed counts for ANZASM
  • blue dot represents improvement or a favourable direction
  • orange dot represents an unfavourable pattern
  • grey dot in the SPC chart represents the actual observed value
  • black dot in the funnel plot denotes the sites or hospitals included in the analysis
  • NHS icon (located at top right corner of the SPC chart) summarises the overall performance pattern over the entire period. An orange ( ) indicates potential special cause deterioration (i.e. in response to a special cause) while a blue ( ) indicates potential special cause improvement.

Detailed guidance on the Making Data Count approach can be found on the Making Data Count website.

Figure 6a: Duration to complete ANZASM evaluation process
Figure 6b: Duration to complete regional ASM evaluation process

There were 7,732 cases that had completed the ANZASM evaluation process as of 03 November 2025. Missing data have been excluded from analysis, thus denominators may change.

The public or private admission status for these patients is summarised in Figure 7.

Figure 7: Admission status for ANZASM patients

ANZASM collects data on emergency and elective admissions. This data is summarised in Figure 8.

Figure 8: Emergency versus elective admission status for ANZASM patients

The distribution of audited cases across the public and private health sectors is summarised in Figure 9.

Figure 9: Hospital status for ANZASM patients

Note: Co-location hospitals are those that provide both privately and publicly funded surgical services

The Australian Institute for Health and Welfare (AIHW) released criteria for classifying hospitals into distinct peer categories according to the services they provide. The distribution of ANZASM cases across these hospital types is summarised in Figure 10.

Figure 10: Hospital peer type for ANZASM patients

Note: Hospital peer type with ≤ 5 cases were grouped into ‘Other’: Mixed day procedure hospitals, Mixed subacute and non-acute hospitals, Non-acute psychiatric hospitals, Other acute specialised hospitals, Other womens & childrens hospitals, Private acute group C hospitals, Private acute group D hospitals, Public acute group C hospitals, Public acute group D hospitals, Public rehabilitation hospital, Very small hospitals, Womens hospitals

The geographical location of ANZASM cases has been summarised according to the modified Monash model (MMM) criteria in Figure 11. MMM classifications are based on the Australian Statistical Geography Standard – Remoteness Areas (ASGS-RA) framework.

Figure 11: Geographical location of ANZASM cases according to MMM criteria

There were 7,732 cases that had completed the ANZASM evaluation process as of 03 November 2025. Missing data have been excluded from analysis, thus denominators may change.

The patient demographics for this cohort have been summarised in Table 1.

Patient comorbidities for this cohort have been summarised in Figure 12.

Table 1: Population characteristics for ANZASM cases
Figure 12: Patient comorbidities

Note: Data is not mutually exclusive

An approximate measure of a patient’s physiological reserve is based on the American Society of Anesthesiologists (ASA) Physical Status Classification System. These data are reported in Figure 13.

Figure 13: ASA status for ANZASM patients

Note: ASA grade I = a normal healthy patient, ASA grade II = a patient with mild systemic disease, ASA grade III = a patient with moderate systemic disease, ASA grade IV = a patient with severe systemic disease that is a constant threat to life, ASA grade V = a moribund patient not expected to survive without an operation, ASA grade VI = a patient declared brain-dead whose organs are being removed for donor purposes

The overall perceived surgical risk (as determined by the treating surgeon) are reported in Figure 14. Please note: perceived surgical risk is only reported for those patients where a procedure took place during their admission.

Figure 14: Surgeon-perceived risk of death for ANZASM patients

The top 5 most common surgical diagnoses have been reported in Table 2. A delay in determining the surgical diagnosis was reported in 5.0% (383/7,729) of cases.

Table 2: Most frequent diagnoses reported in ANZASM cases by region

The most commonly reported final causes of death (not to be confused with coroner-determined cause of death) as noted by surgeons is reported in Table 3.

Table 3: Most commonly reported final causes of death in ANZASM cases by region

The proportion of patients that underwent a procedure during admission is reported in Figure 15. Of all audited ANZASM cases, 8,046 operations were performed in 6,123 patients from 01 January 2023 to 31 December 2024. Patients may have multiple operations.

Where no operation was performed, treating surgeons specified the reasons. These data are reported in Figure 16.

Urgency of surgical procedures fall into 4 categories: immediate (procedure ≤ 2 hours from admission), emergency (procedure ≤ 24 hours from admission), scheduled emergency (procedure > 24 hours post-admission) or elective surgery. These data are reported in Figure 17.

The consultant and/or fellow presence in theatre for reported procedures is summarised in Figure 18.

Figure 15: Proportion of ANZASM patients undergoing 1 or more surgical procedures
Figure 16: Basis for no operation being undertaken on ANZASM patients

Note: Data is not mutually exclusive

Figure 17: Operative urgency for ANZASM patients
Figure 18a: Consultant presence in theatre for surgical procedures on ANZASM patients
Figure 18b: Fellow presence in theatre for surgical procedures on ANZASM patients

The proportion of ANZASM patients where a postoperative complication was reported is summarised in Figure 19. The proportion of ANZASM patients where a delay was identified in postoperative complications was 6.0% (87/1,461).

The types of postoperative complications reported has been summarised in Figure 20.

Statistical Process Control (SPC) charts can be used to present data over time and allow for determinations to be made as to whether changes in a particular metric represent seasonal variation or are in response to a specific cause.

Pattern

Pattern symbol

Pattern summary

SPC – Astronomical Point

≒

An identified point that exceeds 3 sigma limits from the mean

SPC – Trend (5)

ⓣ

5 consecutively increasing or decreasing points

SPC – Two in Three

⅔

2 out of 3 consecutive points exceeding 2 sigma limits from the mean

SPC – Shift (7)

ⓢ

7 consecutive points above or below the mean

Multiple elements comprise the SPC charts:

  • 2 sigma (2σ) limits are displayed as dotted lines, representing 95% warning limits
  • 3 sigma (3σ) limits are displayed as dashed lines, representing 99.8% control limits
  • dark solid line represents the centreline, indicating the mean value of observed counts for ANZASM
  • blue dot represents improvement or a favourable direction
  • orange dot represents an unfavourable pattern
  • grey dot in the SPC chart represents the actual observed value
  • black dot in the funnel plot denotes the sites or hospitals included in the analysis
  • NHS icon (located at top right corner of the SPC chart) summarises the overall performance pattern over the entire period. An orange ( ) indicates potential special cause deterioration (i.e. in response to a special cause) while a blue ( ) indicates potential special cause improvement.

Detailed guidance on the Making Data Count approach can be found on the Making Data Count website.

Figure 19a: Proportion of patients with a postoperative complication in ANZASM patients

Note:
numerator = number of patients with postoperative complication; denominator = total number of patients underwent surgical procedures (missing data excluded)

Figure 19b: Proportion of patients with a postoperative complication in regional ASM patients

Note:
numerator = number of patients with postoperative complication; denominator = total number of patients underwent surgical procedures (missing data excluded)

Figure 20: Types of postoperative complications reported in ANZASM patients

Note:
One patient can have more than one postoperative complication.
Anastomotic leak consists of the following subtypes: colorectal, gastric, oesophageal, panc/billary and small bowel
Neurological consists of the following subgroups: Cerebral swelling, CSF leak, Neurological deficiency
Haemorrhage consists of Significant post-op bleeding
‘Other’ consists of medical complications or surgical complications not easily captured by the existing categories.

Figure 21 summaries the admission of patients to the CCU. It also reports the proportion of patients that assessors believed should have been admitted.

Figure 21: Admission of ANZASM patients to critical care units

Note:
⋆numerator = number of patients where CCU not used; denominator = total number of patients (missing data excluded);
**numerator = number of patients not used but should have used CCU; denominator = total number of patients who were not admitted to CCU

The proportion of patients where a clinically significant infection was acquired either before or during admission is summarised in Figure 22.

The type of infection is reported in Figure 23.

For those infections acquired during admission, the site of infection is reported in Figure 24.

Figure 22: Presence of clinically significant infections in ANZASM patients
Figure 23: The type of infection acquired by ANZASM patients
Figure 24: ANZASM patients with clinically significant infection acquired during admission

The proportion of patients that were given deep vein thrombosis (DVT) Prophylaxis is reported in Figure 25.

The types of DVT prophylaxis that were used are reported in Figure 26.

The proportion of patients not on DVT prophylaxis and the reasons given are reported in Figure 27.

Figure 25: Proportion of ANZASM patients given DVT prophylaxis
Figure 26: Types of DVT prophylaxis given to ANZASM patients

Note: Data is not mutually exclusive

Figure 27: Basis for ANZASM patients not being given DVT prophylaxis

Note: Data is not mutually exclusive

The occurrence of unplanned returns to theatre are reported in Figures 28.

The occurrence of unplanned admission to critical care units are reported in Figures 29.

The occurrence of unplanned readmission to hospital are reported in Figures 30.

Statistical Process Control (SPC) charts can be used to present data over time and allow for determinations to be made as to whether changes in a particular metric represent seasonal variation or are in response to a specific cause.

Pattern

Pattern symbol

Pattern summary

SPC – Astronomical Point

≒

An identified point that exceeds 3 sigma limits from the mean

SPC – Trend (5)

ⓣ

5 consecutively increasing or decreasing points

SPC – Two in Three

⅔

2 out of 3 consecutive points exceeding 2 sigma limits from the mean

SPC – Shift (7)

ⓢ

7 consecutive points above or below the mean

Multiple elements comprise the SPC charts:

  • 2 sigma (2σ) limits are displayed as dotted lines, representing 95% warning limits
  • 3 sigma (3σ) limits are displayed as dashed lines, representing 99.8% control limits
  • dark solid line represents the centreline, indicating the mean value of observed counts for ANZASM
  • blue dot represents improvement or a favourable direction
  • orange dot represents an unfavourable pattern
  • grey dot in the SPC chart represents the actual observed value
  • black dot in the funnel plot denotes the sites or hospitals included in the analysis
  • NHS icon (located at top right corner of the SPC chart) summarises the overall performance pattern over the entire period. An orange ( ) indicates potential special cause deterioration (i.e. in response to a special cause) while a blue ( ) indicates potential special cause improvement.

Detailed guidance on the Making Data Count approach can be found on the Making Data Count website.

Figure 28a: Unplanned returns to theatre among ANZASM patients

Note:
numerator = cases reporting an unplanned return to theatre; denominator = total cases with at least one operation reported (missing data excluded).

Figure 28b: Unplanned returns to theatre among regional ASM patients

Note:
numerator = cases reporting an unplanned return to theatre; denominator = total cases with at least one operation reported (missing data excluded).

Figure 29a: Unplanned admission to critical care units among ANZASM patients

Note:
numerator = cases in which surgeon reported an unplanned admission to CCU; denominator = total number of patients (missing data excluded)

Figure 29b: Unplanned admission to critical care units among regional ASM patients

Note:
numerator = cases in which surgeon reported an unplanned admission to CCU; denominator = total number of patients (missing data excluded)

Figure 30a: Unplanned readmissions to hospital among ANZASM patients

Note:
numerator = cases in which surgeon reported readmission to hospital; denominator = total number of patients (missing data excluded)

Figure 30b: Unplanned readmissions to hospital among regional ASM patients

Note:
numerator = cases in which surgeon reported readmission to hospital; denominator = total number of patients (missing data excluded)

Patient transfer can occur in order to access services not provided by the initial hospital. These data are reported in Figure 31. The proportion of cases with a delay in transfer are also reported.

The proportion of patients transferred to Principal Referral Hospitals are reported in Figure 32.

The proportion of patients transferred from rural to metropolitan hospitals are reported in Figure 33.

The proportion of patients transferred from private to public hospitals are reported in Figure 34.

Figure 31: Proportion of ANZASM patients transferred during the course of care

Note:
⋆numerator = number of transferred patients ; denominator = total number of patients (missing data excluded)
**numerator = number of transferred patients with delay; denominator = number of transferred patients (missing data excluded)

Figure 32: The proportion of patients transferred to Principal Referral Hospitals
Figure 33: Transfer of ANZASM patients from rural to metropolitan hospitals
Figure 34: Transfer of ANZASM patients from private to public hospitals

ANZASM collects data on those admissions resulting from traumatic injuries (motor vehicle accidents, falls or violence). There were 29.5% (2,150/7,293) of cases reported to ANZASM where the admission was thought to be due to trauma. Figure 35 summarises the types of trauma reported to ANZASM.

Figure 35: Proportions of trauma cases due to incidents, falls or violence as reported to ANZASM

Note: Unknown refers to other traumatic events not listed

Patient falls in health care facilities are considered a sentinel event. The location of patient falls is reported in Figure 36.

Figure 36: Location of patient falls among trauma cases, as reported to ANZASM

The types of trauma related accidents are reported in Figure 37.

Figure 37: Types of trauma related accidents among trauma cases, as reported to ANZASM

The types of violence resulting in trauma admissions are reported in Figure 38.

Figure 38: Types of violence among trauma cases, as reported to ANZASM

The surgical care provided to patients is evaluated by independent assessors. Assessors indicate whether key aspects of overall patient management could have been improved in Figure 39.

Figure 39: Areas for patient management improvement

Assessors note any clinical management issues (CMIs) that they have identified, including the type of CMI, whether it contributed to the patient outcome and whether it was considered preventable. These data are reported in Table 4.

When reviewing cases, assessors are asked to identify any CMIs that occurred during the course of care. CMIs are categorised as:

  • an area of consideration, where the clinician believes an area of care could have been improved or different but recognises that there may be an area of debate.
  • an area of concern, where the clinician believes that areas of care should have been better.
  • an adverse event, where an unintended injury caused by medical management, rather than by the disease process, is sufficiently serious to lead to prolonged hospitalisation or to temporary or permanent impairment or disability of the patient at the time of discharge, or which contributes to or causes death.
Table 4: Characteristics of CMIs in ANZASM patients as reported by assessors

The most commonly identified CMIs as reported to ANZASM are summarised in Figure 40.

Figure 40a: Most frequently reported CMIs in ANZASM patients
Figure 40b: Most frequently reported CMIs in regional ASM patients

Funnel plots may be used to identify potential outliers in a population for performance against particular metrics: this is achieved by comparison of individual performance against the average for the target population. The Australian Framework for National Clinical Quality Registries 2024 (produced by the Australian Commission on Safety and Quality in Health Care) recommends an ‘alert and alarm system’ for detection and management of potential outliers. Individual performance more than 2 standard deviations from the target warrants an ‘alert’ status, while more than 3 standard deviations from the target warrants an ‘alarm’ status. The proportions of CMIs that were considered potentially preventable have been depicted in Figure 41.

A timeline for the occurrence of potentially preventable CMIs has been reported in Figure 42.

Figure 41: Potentially preventable CMIs, by state

Statistical Process Control (SPC) charts can be used to present data over time and allow for determinations to be made as to whether changes in a particular metric represent seasonal variation or are in response to a specific cause.

Pattern

Pattern symbol

Pattern summary

SPC – Astronomical Point

≒

An identified point that exceeds 3 sigma limits from the mean

SPC – Trend (5)

ⓣ

5 consecutively increasing or decreasing points

SPC – Two in Three

⅔

2 out of 3 consecutive points exceeding 2 sigma limits from the mean

SPC – Shift (7)

ⓢ

7 consecutive points above or below the mean

Multiple elements comprise the SPC charts:

  • 2 sigma (2σ) limits are displayed as dotted lines, representing 95% warning limits
  • 3 sigma (3σ) limits are displayed as dashed lines, representing 99.8% control limits
  • dark solid line represents the centreline, indicating the mean value of observed counts for ANZASM
  • blue dot represents improvement or a favourable direction
  • orange dot represents an unfavourable pattern
  • grey dot in the SPC chart represents the actual observed value
  • black dot in the funnel plot denotes the sites or hospitals included in the analysis
  • NHS icon (located at top right corner of the SPC chart) summarises the overall performance pattern over the entire period. An orange ( ) indicates potential special cause deterioration (i.e. in response to a special cause) while a blue ( ) indicates potential special cause improvement.

Detailed guidance on the Making Data Count approach can be found on the Making Data Count website.

Figure 42a: Occurrence of potentially preventable CMIs in ANZASM patients
Figure 42b: Occurrence of potentially preventable CMIs in regional ASM patients