Head injuries in Australia 2020–21

The aim of this report is to count and describe the number of head injury hospitalisations in Australia from 1 July 2020 to 30 June 2021,inclusive. In all cases, patients had a head injury diagnosis code (as either a principal or additional diagnosis) in their hospitalisation record.

Only a small proportion of all incidents of injury result in admission to a hospital. For each admission, many more people with injuries are treated in an emergency department but not admitted, or visit a general practitioner rather than a hospital. A larger number of minor injuries do not receive any medical treatment. A smaller number of severe injuries that result in death do not include a stay in hospital but are captured in mortality data. Where a hospitalisation for injury resulted in death, the case will be counted both in hospitalisations and deaths data. 

Head injury cases account for a quarter of hospitalised injury cases. The head or neck was the body part most often identified as the main site of injury in all injury hospitalisations in 2020–21 (AIHW 2023), which to some extent probably reflects the serious nature of head and neck injuries. 

This document covers: 

• definitions and classifications used 
• presentation of data in this report 
• analysis methods. 

The data on hospitalised injuries are from the Australian Institute of Health and Welfare’s (AIHW) National Hospital Morbidity Database (NHMD). The NHMD is effectively considered to contain the complete picture of acute injuries that result in hospital admission across Australia. Comprehensive information on the quality of data is available on the AIHW MyHospitals website. 

Admitted patient care data

In the NHMD, records are presented by hospital separations (discharges, transfers, deaths, or changes in care type) by time period. Records from any selected period will include data on patients who were admitted before that period— if they separated during that period. A record is included for each separation, not each patient, so patients who separated more than once in the period will have more than one record. 

Patient days is the number of days between the separation date and date of admission, not including any hospital leave days. Patient day statistics can provide information on hospital activity that, unlike separation statistics, accounts for differences in length of stay.  

It is expected that patient days for patients who separated in 2020–21, but who were admitted before 1 July 2020, will be counterbalanced overall by the patient days for patients in hospital on 30 June 2021 who will separate in future reporting periods. 

Estimated resident populations 

All populations are based on the estimated resident population (ERP) or Indigenous projected population as at 30 June immediately prior to the reporting period (that is, for the reporting period 2020–21, the population at 30 June 2020 is used). The population is used as the denominator for age‑specific and age‑standardised rates.

The ERP as at 30 June 2001 is used as the standardising population throughout the report (ABS 2003).

The COVID-19 pandemic and resulting Australian Government closure of the international border from 20 March 2020 disrupted the usual Australian population trends. The ERP for 30 June 2020, used in this report, reflects this disruption.

All population data are sourced from the Australian Bureau of Statistics (ABS) as follows:

• General populations are from National, state and territory population
• Indigenous populations are from Estimates and Projections, Aboriginal and Torres Strait Islander Australians (ABS 2019)
• Remoteness populations (available on request from ABS)
• Socio-Economic Indexes For Areas (SEIFA) Index of Relative Socio-Economic Disadvantage (IRSD) quintile populations are from AIHW analysis of Census of Population and Housing: Socio-Economic Indexes for Areas (ABS 2018) and Regional population.

This report estimates the number of incidents of head injuries that lead to hospitalisation. This is less than the number of injury-related records in the NHMD. 

Each record in the NHMD refers to a single episode of care in a hospital. Some injury incidents result in more than one episode of care and, hence, more than one record. 

This can occur in 2 main ways: 

• a person is admitted to one hospital, then transferred to another or has a change in care type (for example, from acute to rehabilitation) within the same hospital 
• a person has an episode of care in hospital, is discharged home (or to another place of residence) and is then admitted for further treatment for the same injury, to the same hospital or another. 

The NHMD does not allow for the identification of multiple separations belonging to the same instance of injury. This means there is the potential for overcounting injury events if we are simply counting the number of injury separations. To minimise this, the mode of admission is taken into account. Separations with a mode of admission of transferred from another hospital (1) are excluded from injury case counts. This is because separations of this type (transfers) are likely to have been preceded by another separation that met the case selection criteria. Similarly, separations where the mode of admission is statistical admission – episode type change (2) and the care type is not listed as acute (1, 7.1, 7.2), are also excluded as they are likely to have been preceded by an acute episode of care that met the case selection criteria.

When deriving average length of stay, however the patient days from all applicable separations, regardless of admission mode, are included in the totals for the numerator. See the ‘Length of stay’ section for more information.

This process should largely correct for overestimation of cases due to transfers (both internal and external) but will not correct for overestimation due to re-admissions.

The following criteria were used to estimate numbers of cases of head injury hospitalisations in Australia, by cause of injury. 

Period

Selection was based on the financial year of separation, from 1 July 2020 to 30 June 2021. 

Standard separations

Standard separations were included, that is records were excluded where the care type was newborn with unqualified days only (7.3), organ procurement - posthumous (9), or hospital boarder (10).

Head injury

For the purposes of this report, head injury cases are defined as records meeting either of the criteria below:

1. principal diagnosis in the ICD-10-AM range S00–S09, T00.0, T01.0, T02.0, T03.0, T04.0, T06.0, T15, T16, T20, T26, T33.0, T34.0, T35.2 using ‘Chapter 19 Injury, poisoning and certain other consequences of external causes’. or
2. additional diagnosis in the ICD-10-AM range S00–S09, T00.0, T01.0, T02.0, T03.0, T04.0, T06.0, T15, T16, T20, T26, T33.0, T34.0, T35.2.

This scope excludes injuries due to Complications of surgical and medical care (T80 – T88) and Sequelae of injuries, of poisoning and of other consequences of external causes (T90 – T98).

Records where Care involving use of rehabilitation procedures (Z50) has been coded in any additional diagnosis field are excluded from this analysis, except if the care type for the separation was acute. Nearly all injury separations are thought to be included in the data reported, representing minimal risk of counting error.

External causes 

The external cause classification (Chapter 20 of ICD-10-AM) consists of 3-character category codes in the range of U50–Y98 (including place of occurrence and activity when injured). 

The NHMD is structured so that the first listed external cause for a record relates 
 to the first listed injury diagnosis.  

While multiple external causes may be recorded for a separation, we report only one cause for each injury, referred to as ‘nominal external cause’ in these notes. The following steps are followed to determine the nominal external cause for each injury hospitalisation:

1. The first reported external cause is taken to be the nominal external cause
2. If the nominal external cause, as determined by step 1, is U90.0 (Staphylococcus aureus) or a supplementary factor (Y90–Y98), then the second reported code is taken to be the nominal external cause
3. If the nominal external cause, after steps 1 and 2, relates to complications of medical and surgical care (Y40–Y84), sequelae of external causes of morbidity and mortality (Y85–Y89), or a supplementary factor code (Y90–Y98), then the record is excluded.

A new cause code, Exposure to or contact with allergens (Y37) was introduced in the 11th edition of ICD-10-AM. Aside from Allergy to animals (Y37.6), cases where Y37 is the first reported external cause code are excluded from this report.

The hospitalisations analysed within this report may have had a head injury diagnosis as their principal diagnosis or as an additional diagnosis. Some sections of the report can only include analysis cases with head injury as the principal diagnosis due to the structure of the dataset.

Injury type, body location of injury, and external cause are three variables that have principal and additional codes. The principal diagnosis is mapped to the principal injury type, body location and external cause. However additional injury types, body locations and external causes cannot be linked with other additional diagnoses. For these variables, the report typically only analyses based on principal diagnosis. Consequently, statistics obtained for these variables are likely to be underreporting the true number of relevant hospitalisations.

External cause is treated slightly differently, in that the external cause is analysed for both principal and additional diagnoses. Given the likelihood of the principal external cause code being responsible for causing both principal and additional diagnoses, it was decided that including both types of diagnoses would still be representative of the true causes of head injuries.

The three fictional examples below show how these inclusion criteria are expressed in this project under different circumstances.

Example 1: Kai’s story

Kai had a fall from a bike. Their friend drove Kai to hospital, where they were admitted with a principal diagnosis of a concussion (S06.00). Kai also had an additional diagnosis of an abrasion of forearm (S50.81).

In this report, deidentified data about Kai’s hospitalisation would be included under the principal diagnosis of head injury. Information about the principal diagnosis would be included in analysis of injury type, body location, and external cause. Pedal cyclist injured in noncollision transport accident (V18) could be used for the external cause code (dependent on individual hospital clinical coders). Kai’s forearm injury is not counted as an additional diagnosis within this report, as it is not a head injury.

Example 2: Brian’s story

Brian was at a swimming hole with some friends, when he dove into a shallow region of water and hurt his neck. An ambulance was called, and Brian was admitted with a principal diagnosis of a traumatic rupture of the cervical intervertebral disc (S13.0). Brian also had an additional diagnosis of an open wound to the scalp (S01.0).

In this report, deidentified data about Brian’s story would be included despite the principal spine injury diagnosis, because of the additional head injury diagnosis. Information about Brian would be excluded from analysis of injury type and body location of injury. Diving or jumping into water striking or hitting bottom (W16.0) could be used for the external cause code (dependent on individual hospital clinical coders). Brian’s spine injury principal diagnosis is not analysed within the report, as it is not a head injury. 

Example 3: Leanne’s story

Leanne was working on scaffolding when she fell from a height. Having sustained multiple injuries, Leanne was transported to hospital by ambulance and was admitted with the principal diagnosis of a fractured parietal bone (S02.0). Leanne also had an additional diagnosis of a fractured mandible (S02.6), and an open wound of the head communicating with a fracture (S01.81).

In this report, deidentified data about Leanne’s hospitalisation would be included under a principal head injury diagnosis. Information about the principal diagnosis would be included in analysis of injury type, body location, and external cause. Fall on and from scaffolding (W12) could be used for the external cause code (dependent on individual hospital clinical coders). While Leanne’s additional diagnoses are head injury diagnoses, these are only included for analysis for total diagnoses counts, and are not counted as cases under the additional diagnoses since the principal diagnosis takes precedence.

Due to rounding, percentages in tables may not add up to 100.0. Percentages and rates reported as 0.0 or 0 usually indicate a zero. 

Body part and injury type are derived from the principal diagnosis of the case. The sum of injuries by body part may not equal the total number of hospitalised injury cases because some injuries are not described in terms of body region.

Head location, body part and injury type analysis are only included where there is a head injury code as the principal diagnosis. 

The patient’s age is calculated at the date of admission. In tables by age group and sex, separations for which age and/or sex were not reported are included in the totals.

Suppression of data

The AIHW operates under a strict privacy policy based on Section 29 of the Australian Institute of Health and Welfare Act 1987 (AIHW Act). Section 29 requires that confidentiality of data relating to persons (living and deceased) and organisations be maintained. The Privacy Act 1988 (Privacy Act) governs confidentiality of information about living individuals. 

The AIHW is committed to reporting that maximises the value of information released for users while being statistically reliable and meeting legislative requirements described in the AIHW Act and the Privacy Act. 

Data (cells) in tables may be suppressed to maintain the privacy or confidentiality of a person or organisation, or because a proportion, rate (numerator or denominator) or other measure is related to a small number of events (and may therefore not be reliable). Data may also be suppressed to avoid attribute disclosure. The abbreviation ‘n.p.’ (not published) has been used in tables to denote these suppressions. In these tables, the suppressed information is included in the totals.

Scale up factor for bimonthly admission data

The NHMD is structured by date of hospital separation (discharge, transfer, death or change in care type). This means, for example, that records are included in the 2020–21 NHMD if the date of hospital separation is in the period 1 July 2020 to 30 June 2021. Therefore, some records will be admitted in one financial year, but not reported until a future financial year, when the hospital separation is complete. This particularly affects records with an admission date in mid to late June. This is not considered an issue when reporting total injury cases for the year, as it is expected that admissions not yet separated at the end of the year are counterbalanced by separations at the start of the year that were admitted in the previous year. However, it presents an issue when comparing hospitalisation cases by month of admission.

Where data are presented in this report by month of admission, a scale-up factor is applied to the data for June to estimate cases that were admitted but not yet separated. The scale-up factor is determined by calculating the average percent completion (separated from hospital in the same financial year as admission) across the previous 9 years of data for cases admitted on each day of June, for each analysis variable. For each day in June, the average percent of incomplete cases (i.e. separated in the following financial year) is then added to the case numbers to create the scaled-up case numbers. For consistency, the scale-up factor is applied to each year, not just the 2020–21 data.

This method ensures that causes and types of injury which average varying lengths of stay (thereby impacting on how many records are still receiving care into the next reporting year) are accounted for in the calculation. Additionally, while the final presentation of data is at the bimonthly level, the scaling is calculated for each day in June, from 1 June to 30 June.   This means that the degree of scaling applied reflects the decreasing completeness of the data approaching 30 June.

The efficacy of scaling up reported admissions by the above method has been tested on 2017–18 and 2018–19 years (where a complete record was available for June admissions) and has found the resulting estimate to closely match the true case numbers.

In addition to the scale up factor, the number of admissions for each bimonthly period has been standardised to a 30-day month to enable comparison of trends over months of unequal days. Each month is split into two periods: 1^st–15^th, and the 16^th – end of month.   The standardisation is applied to the latter period. 

As a result, the numbers presented in monthly analysis tables cannot be directly summed to the annual totals reported elsewhere in the report.

Historic data

Over time, minor changes have been made to the method for counting cases of injury, therefore data presented in previous AIHW reports may not match the data presented in this report. 

Length of stay

Patient days reported during the separations that were omitted to reduce overestimation of incident cases are an integral part of the hospital care provided for these injuries. The patient days in these subsequent admissions are therefore included when calculating average length of stay for causes of injury.

Note that ‘length of stay’, as presented in this report, does not include some patient days potentially attributable to injury. It does not include days for most aspects of injury rehabilitation, which cannot be reliably assigned without information enabling identification of all admitted episodes associated with an injury case.

Rates

Age-standardised rates 

Age‑standardisation of rates enables valid comparison across years and/or jurisdictions without being affected by differences in age distributions. All populations are based on ABS ERP data. Unless noted otherwise, population rates were age-standardised using the direct standardisation method and 5-year age groups, with a highest age group of 85 and over. Cases of injury are reported as a rate per 100,000 population.

Population data for age specific and age-standardised rates by Indigenous status are produced using a slightly different method to other rates.

Head injury hospitalisation rates by Indigenous status were directly age-standardised, using the projected Indigenous population (series B) (ABS 2019). The population for non-Indigenous Australians was derived by subtracting the First Nations population from the general population. Importantly, this will include individuals where Indigenous status is unknown or not reported, and therefore does not represent a strictly non-Indigenous population. See Quality of Indigenous status data below for further detail.

Due to data quality issues, the ERP Indigenous population data are limited to a highest age group of 65 and over. Therefore, standardised rates calculated by Indigenous status are not directly comparable with other standardised rates, which used a highest age group of 85 and over. 

Changes in rates due to changes in underlying population data

The age‑standardised rates (per 100,000 population) presented in this report for the year 2011–12 of time-series tables have been calculated using ‘rebased’ ERPs following the 2016 Census. Therefore, rates reported for 2011–12 in this report should not be compared with earlier reports.

Estimated change in rates over time

Estimated trends in rates of hospitalised injury were reported as annual percentage change.  Due to a break in series between 2016–17 and 2017–18 reporting years (see ‘changes in New South Wales admission practice’ below), the average annual change has been calculated for the six years from 2011–12 to 2016–17, and for the four years from 2017–18 to 2020–21. The percent change to 2020–21 from 2019–20 is also presented.

Population‑based rates of injury tend to have similar values from one year to the next. Exceptions to this can occur (for example, due to a mass‑casualty disaster), but are unusual in Australian injury data. Some year‑on‑year variation and short‑run fluctuations are to be expected, so small changes in a rate over a short period do not provide a firm basis for asserting that a trend is present. 

For 2019–20 and 2020–21 data, the COVID-19 pandemic resulted in lockdowns and social distancing measures from March 2020, which resulted in changed behaviour, and thus the counts of head injury hospitalisations may be different to previous years. Also, the pandemic and resulting Australian Government closure of the international border from 20 March 2020 caused significant disruption to the usual Australian population trends. The ERPs for 30 June 2020 and 30 June 2021, used in this report, reflect this disruption. Because of these issues, head injury hospitalisation rates for 2019–20 and 2020–21 should be interpreted with this in mind.

Geographical classifications 

The ABS’s Australian Geography Standard (ASGS) Remoteness Structure 2016 (ABS 2016a) is a hierarchical classification system of geographical regions and consists of interrelated structures. The ASGS provides a common framework of statistical geography and enables the production of statistics that are comparable and can be spatially integrated.

The structure has seven hierarchical levels listed here from smallest to largest:

• Mesh Blocks
• Statistical Area Level 1 (SA1)
• Statistical Area Level 2 (SA2)
• Statistical Area Level 3 (SA3)
• Statistical Area Level 4 (SA4)
• Greater Capital City Statistical Areas
• State and Territory.

Each level directly aggregates to the level above. For example, SA1s are aggregates of Mesh Blocks, and themselves aggregate to SA2s. At each level, the units collectively cover all of Australia.

Remoteness area of usual residence of the patient

Australia can be divided into several regions, based on their distance from urban centres. This is considered to determine the range and types of services available. In this report, 
 data on geographical location are collected on the area of usual residence of patients in the NHMD. These data are specified in the Admitted patient care National Minimum Data Set (NMDS) as state or territory of residence and SA2. For 2020–21, the area of usual residence was provided by some jurisdictions in the form of a Statistical Area level 1 (SA1). Where SA1 data were available, remoteness areas were allocated by the AIHW based on the SA1 information. If SA1 data were not available, the SA2 data were used to allocate remoteness areas.

Data on the remoteness area of usual residence are defined using the ABS’s ASGS Remoteness Structure 2016 (ABS 2016b). The ASGS Remoteness Structure 2016 categorises geographical areas in Australia into remoteness areas, described at www.abs.gov.au.

Remoteness is an index applicable to any point in Australia, based on road distance from urban centres of 5 categories. The categories are:

• Major cities (for example, Sydney, Geelong, Gold Coast) 
• Inner regional (for example, Hobart, Ballarat, Coffs Harbour) 
• Outer regional (for example, Darwin, Cairns, Coonabarabran)
• Remote (for example, Alice Springs, Broome, Strahan)
• Very remote (for example, Coober Pedy, Longreach, Exmouth)

Socioeconomic groups 

Data on socioeconomic groups are defined using the ABS’s Socio-Economic Indexes for Areas (SEIFA) 2016 (ABS 2018). 

The ABS generated the SEIFA 2016 data using a combination of 2016 Census data such as income, education, health problems/disability, occupation/unemployment, wealth and living conditions, dwellings without motor vehicles, rent paid, mortgage repayments, and dwelling size. Composite scores are averaged across all people living in areas and defined for areas based on the Census collection districts, and are also compiled for higher levels of aggregation. The SEIFA is described in detail at www.abs.gov.au. 

The SEIFA Index of Relative Socio-Economic Disadvantage (IRSD) indicates the collective socioeconomic status (SES) or situation of the people living in an area, with reference to the situation and standards applying in the wider community at a given point in time. A relatively disadvantaged area is likely to have a high proportion of relatively disadvantaged people. However, such an area is also likely to contain people who are not disadvantaged, as well as people who are relatively advantaged. 

The AIHW generated separation rates by SES using the IRSD scores for the statistical area level 2 (SA2) of usual residence of the patient reported for each separation. The ‘1—lowest’ group represents the areas containing the 20% of the national population with the most disadvantage, and the ‘5—highest’ group represents the areas containing the 20% of the national population with the least disadvantage. These SES groups do not necessarily represent 20% of the population in each state or territory. Disaggregation by SES group is based on the area of usual residence of the patient, not the location of the hospital. 

The following labels for each socioeconomic group have been used throughout this report:

Label                                      Socioeconomic area

1—lowest                              Most disadvantaged

2                                              Second-most disadvantaged

3                                              Middle

4                                              Second-least disadvantaged

5—highest                               Least disadvantaged.

Indigenous status

The term ‘First Nations people’ is used to refer to persons identified as such in Australian hospital separations data and population data collections. The term ‘non-Indigenous Australians’ is used where NHMD records the status is explicitly stated as non-Indigenous. ’Other Australians’ refers to people with an Indigenous status of ‘no’ or ‘not recorded’.

When calculating First Nations and non-Indigenous rates, records where Indigenous status is missing or not stated are not included in the analysis. 

Quality of Indigenous status data 

The AIHW report First Nations identification in hospital separations data: quality report (AIHW 2013) presents the latest findings on the quality of Indigenous identification in hospital separations data in Australia, based on studies conducted in public hospitals during 2011. Private hospitals were not included in the assessment. The results of the study indicate that, overall, the quality of First Nations identification in hospital separations data was similar to that achieved in a previous study (AIHW 2010). However, the survey for the 2013 report was performed on larger samples for each jurisdiction/region and is therefore considered more robust than the previous study. An estimated 88% of First Nations patients were correctly identified in Australian public hospital admission records in 2011-12 (AIHW 2013). This under counting of First Nations patients is a known issue across states and territories too with proportions ranging from 58% (confidence interval, 46-69%) in the Australian Capital Territory and 98% (96-99%) in the Northern Territory over the same time period.

Unless otherwise indicated, data elements were defined according to their definitions in the AIHW’s Metadata Online Registry (METEOR), and summarised in the Glossary.

In particular, data element definitions for the Admitted patient care National Minimum Data Set (NMDS) are available online at the METEOR website.

Unless otherwise indicated, data elements were defined according to their definitions in the AIHW’s Metadata Online Registry (METEOR), and summarised in the Glossary.

In particular, data element definitions for the Admitted patient care National Minimum Data Set (NMDS) are available online at the METEOR website.

Diagnosis, intervention and external cause data for 2020–21 was reported to the NHMD by all states and territories using classifications from the 11^th edition of the International statistical classification of diseases and related health problems, 10^th revision, Australian modification (ICD-10-AM) (ACCD 2019a).

In tables and figures, information on diagnoses, external causes, and interventions are presented using the codes and abbreviated descriptions of the ICD-10-AM and the 11^th edition of the Australian classification of health interventions (ACHI). Full descriptions of the categories are available in ICD-10-AM/ACHI publications (ACCD 2019a, ACCD 2019b, ACCD 2019c).

Where data are presented in a time series incorporating previous reporting periods,
these have been coded according to the following editions of ICD‑10‑AM:

• 7^th edition for 2011–12 and 2012–13 hospital data
• 8^th edition for 2013–14 and 2014–15 hospital data
• 9^th edition for 2015–16 and 2016–17 hospital data
• 10^th edition for 2017–18 and 2018–19 hospital data
• 11^th edition for 2019–20 hospital data.

This report simplified the most common ICD-10-AM codes and ACHII chapter procedure types into plain English terms.

The table of simplified plain English ICD-10-AM codes is shown in Table 1.

The table of simplified plain English ACHII chapter procedure types is shown in Table 2.

Drowning and submersion

The cases included are those involving unintentional drowning and submersion. Note that this does not include unintentional drowning and submersion injuries due to water transportation, other transportation crashes, or acts of nature such as storms and floods—unless the first-mentioned external-cause code is one of those listed above. Cases of ‘the bends’ due to deep diving and rapid ascents are covered in the Electricity and air pressure cause category. A discussion of terms such as ‘drowning’ and ‘submersion’ can be found in WHO (2014).

Submersion: Brief submersion (or immersion) in water or other non-toxic liquid is usually harmless. However, injuries can occur while a person is submerged, particularly following 
 a fall or dive into water. A submerged person may experience respiratory impairment 
 (see ‘drowning’, below). 

Drowning: Prolonged submersion (or brief submersion in some circumstances—for example, if a person is unconscious when entering the water), puts a person at immediate risk of death by drowning. The drowning process typically involves breath-holding; attempted inhalation triggering spasm of the larynx; depletion of oxygen and build-up of carbon dioxide; loss of consciousness; and, eventually, inhalation of water into the lungs. 

Sometimes the process is interrupted before death (for example, by rescue), in which case the person may survive with harm, such as brain damage due to lack of oxygen. That situation was previously referred to as ‘near-drowning’ and is now called ‘drowning with a non-fatal outcome’, the term currently recommended by the WHO.

Choking and suffocation

This category covers the ICD-10-AM code group ‘Other accidental threats to breathing (W75–W84)’, as well as W44 (Foreign body entering into or through eye or natural orifice) where a principal diagnosis indicates a likelihood that the hospital separation was principally due to a threat to breathing. 

The external cause classification of foreign bodies with and without obstruction (or ‘choking’) is determined by the documentation within the clinical record and the hierarchy and essential modifiers of the ICD-10-AM classification.

If the documentation within the clinical record does not explicitly state ‘asphyxia’, ‘obstruction’ or ‘suffocation’ in relation to the foreign body, W44 must be assigned as the default code as indicated by the Alphabetic Index structure. A code from W80, W79 or W78 may only be assigned where there is clear documentation of the terms ‘asphyxia, obstruction, suffocation’ with a causal link to the foreign body.

For the purposes of this report, any case where the principal diagnosis is a foreign body in the mid-lower respiratory tract is considered a threat to breathing.  Cases with a principal diagnosis of T17.2 – T17.8 (foreign body in pharynx, larynx, trachea, bronchus, or other and multiple parts of the respiratory tract), and an external cause of W44 are reported under the ‘Choking and suffocation’ category. In previous AIHW reports, these cases were reported under the ‘Contact with objects’ external cause category.

It is likely that some cases with a foreign body in the mouth or oesophagus (T18.0 & T18.1) and a code of W44 may also pose an accidental threat to breathing, however the majority will not.  Therefore, these have been excluded from re-categorisation and remain in the ‘Contact with objects’ external cause group.

Contact with objects

The technical description of this category is ‘Exposure to inanimate mechanical forces’. 

A change in coding of Contact with knife, sword or dagger (W26) occurred between the 8th and 9th editions of ICD-10-AM and it was renamed Contact with other sharp object(s) (W26) and Contact with knife, sword or dagger became a subcategory (W26.0). The subcategories in W26 now include:

• Contact with knife, sword or dagger (W26.0)
• Contact with other sharp object(s), not elsewhere classified (W26.8) (including Edge of stiff paper and Tin can lid)
• Contact with unspecified sharp object(s) (W26.9).

In addition, the specific exclusion of ‘Knife, sword or dagger’ in Foreign body or object entering through skin (W45) is removed.

Ascertainment of ‘Intentional self‑harm’

According to inclusion notes in ICD‑10‑AM, hospitalisations for injury should be assigned codes in the range X60–X84 if they were purposely self‑inflicted poisoning or injury, suicide, or attempted suicide (ACCD 2019c). Determining whether an injury is due to intentional self‑harm is not always straightforward. Cases may appear to result from intentional self‑harm, but the available information may be inconclusive and therefore preclude them being coded as intentional. In this situation, the case can be coded to an ‘undetermined intent’ category—for example, Falling, jumping or pushed from a high place, undetermined intent (Y30) or Crashing of motor vehicle, undetermined intent (Y32). 

Some patients may choose not to disclose that their injuries resulted from intentional self‑harm. Some may be unable to do so due to the nature of the injuries. For others, their motives may be ambiguous. 

In very young children, confirming that an injury was due to intentional self‑harm can be difficult and may involve a parent or caregiver’s perception of the intent. Ability to form an intention to inflict self‑harm, and to understand the implications of doing so, requires a degree of maturation that is absent in infancy and early childhood. 

It is not possible to differentiate between acts of self‑injury and acts of self‑harm with suicidal intent within the NHMD, but it is likely that a proportion of cases of intentional self‑harm are self‑injurious in nature rather than suicidal in intent. 

Due to the particular uncertainties around the intent of children, cases of intentional self‑harm are presented in aggregate for ages up to and including 14, and suicide statistics are not presented for children aged under 10.

Ascertainment of injury due to assault

As with injury due to intentional self-harm, cases of injury due to intentional assault may be difficult to identify. Feelings of shame or embarrassment may underlie reticence to report either of these forms of intentional injury. In addition, most injuries due to interpersonal violence have potential legal implications. Pressures or incentives to not reveal assault may be particularly likely in circumstances such as injury of a child or other dependent person by a caregiver, or injury of one spouse by the other. Cases recognised as possibly being due to assault—but where doubt remains—may therefore be coded as Undetermined intent.

Perpetrator codes are used in ICD‑10‑AM when a code from the ICD‑10‑AM category Assault (X85–Y09) is present. A coding standard (ACCD 2019c) provides guidance to clinical coders in assigning codes identifying the perpetrator of assault, abuse, or neglect. The coding rules operate on a hierarchical basis, with coders required to code the closest relationship between the perpetrator and the victim. The 10 subcategories of perpetrator consist of the following:

• spouse or domestic partner
• parent
• other family member
• carer
• acquaintance or friend
• official authorities
• person unknown to the victim
• multiple persons unknown to the victim
• other specified person
• unspecified person.

Injuries inflicted through legal interventions and operations of war (Y35 – Y36) are included under the assault category but do not form part of the perpetrator analysis.

Missing or not reported causes

Some injury cases do not include an external cause, or the only cause code provided is invalid for the scope of this report (i.e., supplementary factor codes). These cases are included in this report as ‘not reported’ and are counted towards to the total injury cases.

Changes in New South Wales admission practice

The emergency department admission policy was changed for New South Wales (NSW) hospitals in 2017–18. Episodes of care delivered entirely within a designated emergency department or urgent care centre are no longer categorised as an admission regardless of the amount of time spent in the hospital. This narrowing of the categorisation has had the effect of reducing the number of admissions recorded in NSW from the 2017–18 financial year. For NSW, the effect was a significant decrease (3.7%) in all public hospital admissions in 2017–18 compared to 2016–17. The impact of the change was felt disproportionately among hospitalisations for injury and poisoning. According to NSW Health, the number of hospitalisations for injury and poisoning in NSW decreased by 7.6% between 2016–17 and 2017–18, compared to a usual yearly increase of 2.8% (Centre for Epidemiology and Evidence 2019). 

The change in NSW’s emergency department admission policy may have had different effects on case numbers within different external cause categories. This is because different types of injury have a different likelihood of requiring prolonged care in an emergency department, but without an admission to a hospital ward. 

Due to the size of the contribution of NSW data to the national total, Australian data from 2017–18 should therefore not be compared with data from previous years.

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