Sports injury hospitalisations in Australia, 2019–20

The data on hospital separations are from the Australian Institute of Health and Welfare’s (AIHW) National Hospital Morbidity Database (NHMD). Comprehensive information on the quality of data is available on MyHospitals. Nearly all injury cases admitted to hospitals in Australia are included in the NHMD data reported.

Sport and physical recreation participation data is from the AusPlay survey. Every year, a sample of 20,000 Australians is asked about their participation in sports and physical recreation. The survey results include estimates of the number of participants in a range of activities.

Admitted patient care data

Records are presented in the NHMD by hospital separations (discharges, transfers, deaths, or changes in care type) in the period 1 July 2019 to 30 June 2020. Data on patients who were admitted on any date before 1 July 2019 are included if they also separated between 1 July 2019 and 30 June 2020. A record is included for each separation, not for each patient, so patients who separated more than once in the year will have more than 1 record in the NHMD.

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

It is expected that patient days for patients who separated in 2019–20, but who were admitted before 1 July 2019, will be counterbalanced overall by the patient days for patients in hospital on 30 June 2020, but who will separate in future reporting periods.

The numbers of separations and patient days can be a less accurate measure of the activity for establishments such as public psychiatric hospitals, and for patients receiving subacute or non-acute care, for which more variable lengths of stay are reported.

ICD-10-AM/ACHI

Diagnosis and external cause data for 2019–20 were reported to the NHMD by all states and territories using the 11th edition of the International statistical classification of diseases and related health problems, 10th revision, Australian modification (ICD-10-AM) (ACCD 2018). Data for 2017–18 and 2018–19 were reported to the NHMD using the 10^th edition of the ICD-10-AM.

Estimated resident populations

Australian populations are based on the estimated resident population (ERP) as at 30 June. A calculated 31 December population is derived through averaging the relevant ERP 30 June populations (that is, for the reporting period 2019–20, the 30 June 2019 and 30 June 2020 files are averaged to generate a 31 December population). The calculated 31 December population is used as the denominator for age‑specific rates in table A20.

The COVID-19 pandemic and resulting Australian Government closure of the international border from 20 March 2020 caused significant disruptions to the usual Australian population trends. The ERP for 30 June 2020, used in this report reflects these disruptions. The rates in table A20 may be greater than previous years due to decreases in the denominator of some sub-populations.

Sport and physical recreation participation data

AusPlay data is collected by Engine on behalf of Sport Australia. Australian residents are randomly selected using their mobile phone number and interviewed via a computer assisted telephone interview (CATI). The target sample size is 20,000 people aged 15 years and over. The survey period for the 2019–20 data is 1 July 2019 to 30 June 2020.

The sample data is projected to population estimates using a common post-stratified weighting (scaling) method. As the survey estimates are based on a sample, rather than the full population, they will have sample error. One measure of the sample error is the relative margin of error (RMOE). Survey estimates with a RMOE between 50% and 100% should be used with caution. Survey estimates with a RMOE greater than 100% are considered too unreliable to use.

AusPlay survey respondents answer questions about their participation in sports and physical recreation in the 12 months prior to interview. A respondent needs only to have participated once in the previous 12 months to be counted as a participant. The survey does not distinguish between organised sports and recreational participation. Thus, for example, a participant in soccer may have played consistently in an organised competition over a six month period, or may have played soccer recreationally at a park with friends: both are treated equally as soccer participants.

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

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

The NHMD does not allow for identifying where multiple separations belong to the same instance of injury. This means there is the potential for over counting injury events if simply counting the number of injury separations. To minimise this issue, the mode of admission is used to create an estimate of cases of injury. 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 also met the case selection criteria for injury cases.

The exception to this is in deriving average length of stay, in which the numerator (patient days) includes days recorded across all applicable separations regardless of admission mode. See length of stay section for more information.

This procedure should largely correct for overestimation of cases due to transfers, but will not correct for overestimation due to re-admissions nor statistical admissions where care type changes.

Selection criteria

Reporting on sports injury hospitalisations aims to describe sports injury events that resulted in admission to a hospital. This section describes the criteria used to estimate cases of hospitalised sports injury in Australia.

Period

Selection was based on the financial year of separation, from 1 July 2019 to 30 June 2020.

Injury

Injury separations are defined as records that contained a principal diagnosis in the ICD‑10‑AM range S00–T75 or T79, using ‘Chapter 19 Injury, poisoning and certain other consequences of external causes’.

Records where Care involving use of rehabilitation procedures (Z50) has been coded in any additional diagnosis field are excluded as out of scope for this analysis, except if the care type for the separation was acute.

Records where the care type is newborn with unqualified days only, organ procurement–posthumous or hospital boarder are excluded as out of scope for this analysis.

Sports injury hospitalisations are those with an activity code in the sports activity range (U50–U71 in the ICD-10-AM). For injury hospitalisations where the first recorded activity code is Leisure activity, not elsewhere classified (U72) or While working for income (U73), then the second recorded activity code is considered.

External causes

The external cause classification (Chapter 20 of ICD-10-AM) consists of 3-character categories 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 case of injury. Where the first reported external cause code is U90.0 (Staphylococcus aureus) or a supplementary factor (Y90–Y98), then the second code is reported instead.

For the purposes of this report, cases where the first reported external cause relates to complications of medical and surgical care (Y40–Y84) or sequelae of external causes of morbidity and mortality (Y85–Y89), as well as records with a supplementary factor code (Y90–Y98) which have already passed through the above test, are excluded from the analysis.

Cycling

Cycling can be a sport, a recreation activity, or a mode of transport. For hospitalisations, information is recorded separately about the cause of the injury—which could be a cycling transport accident—and the activity being undertaken at the time of the injury—which could be cycling as a sport, a sport other than cycling, or a non-sport activity.

There were 15,244 cycling-related injury hospitalisations in 2019–20. Of these hospitalisations,

• 7,345 (48.2%) had a recorded activity of cycling as a sport, and the cause of injury was a cycling transport accident,
• 654 (4.3%) had a recorded activity of cycling as a sport, but the cause of injury was not a cycling transport accident,
• 186 (1.2%) had a recorded activity of a sport other than cycling, and the cause of injury was a cycling transport accident,
• 7,059 (46.3%) had a cause of injury of a cycling transport accident, but the activity was non-sport (such as leisure, working, or other specified activity).

Hospitalisations from the first two groups are included in this report as cycling sport injury hospitalisations. Hospitalisations from the third group are included in this report as sport injury hospitalisations and attributed to the recorded sport (which is not cycling). Hospitalisations in the fourth group are not sport injury hospitalisations and thus are not included in this report. 

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

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 regime 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 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 monthly 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 2019–20 NHMD if the date of hospital separation is in the period 1 July 2019 to 30 June 2020. 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 injury cases for the year as a whole, 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 the analysis variable. For each day in June, the average percent of incomplete cases (separated in the following financial year) is then added onto the case numbers to create the scaled-up case numbers. For consistency, the scale up factor is applied to each year, not just the 2019–20 data.

In addition to the scale up factor, the number of admissions for each month has been standardised to a 31-day month to enable comparison of trends over each month.

As a result, the case numbers presented in monthly analysis tables cannot be directly compared to the annual cases reported elsewhere in the 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. In particular, 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.

Change in population rates over time

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‑to‑year variation and other short‑run fluctuations are to be expected, and so small changes in rates over a short period normally do not provide a firm basis for asserting that a trend is present.

For 2019–20 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 sports injury hospitalisations are different to previous years. Also, the pandemic and resulting Australian Government closure of the international border from 20 March 2020 caused significant disruptions to the usual Australian population trends. The ERP for 30 June 2020, used in this report, reflects these disruptions. Because of these issues, the sports hospitalisation rates for 2019–20 should be interpreted with this context in mind.

Participant rates

Rates of sports injury hospitalisations per participant are calculated using AusPlay participant data as the denominator. The AusPlay sports categories are not an exact match to the sports categories for the hospital data. Table 1 below provides the AusPlay to ICD-10-AM mapping used for this report. 

If not otherwise indicated, data elements were defined according to the definitions in the National health data dictionary, versions 16, 16.1 and 16.2 (AIHW 2012, 2015a, 2015b or METeOR), and summarised in the Glossary.

Data element definitions for the Admitted patient care National Minimum Data Set (NMDS) are also available online at METeOR.

Indigenous status

The term ‘Indigenous Australians’ is used to refer to persons identified as such in Australian hospital separations data. The term ‘non-Indigenous Australians’ is used where NHMD records the Indigenous status is explicitly stated as non-Indigenous.

Quality of Indigenous status data

The AIHW report Indigenous 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 Indigenous 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.

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 2019–20, the area of usual residence was voluntarily 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 ABS.

Remoteness is an index applicable to any point in Australia, based on road distance from urban centres of 5 sizes. The reported areas are defined as follows:

• 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)

Table 1 describes the AusPlay to ICD-10-AM code mapping used for this report.

Adjusting for changes to rehabilitation coding

A change in coding practice for ICD-10-AM, introduced July 2015, Care involving the use of rehabilitation procedures (Z50) has necessitated a change to the standard record inclusion criteria for reports of hospital-admitted injury cases. The change applies to episodes that ended on 1 July 2015, or later.

Due to the change in coding practice, the numbers of separations in 2015–16 with a principal diagnosis in the ICD-10-AM ‘Chapter 19 Injury, poisoning and certain other consequences of external causes’ (S00–T98) range increased (approximately an additional 60,000 records).

In order to minimise the effect of the coding change on the estimation of injury occurrence and trends, a change to the case estimation method established by NISU was required. Records with Z50—either as Principal diagnosis or as Additional diagnosis—are were omitted in data-years both before and after the coding change, up to 2016–17. The change to data prior to 2015–16 amounts to an adjustment of less than 0.1% of records. Where injury trends are presented by Principal diagnosis for years prior to 2015–16, data will not be directly comparable with previous reporting periods. For 2017–18 and 2018–19 data in this report, records with a care type of ‘acute’ and with Z50 as an additional diagnosis were included.

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.

ABS (Australian Bureau of Statistics) 2016a. Australian Statistical Geography Standard (ASGS): Volume 1—Main structure and greater capital city statistical areas, July 2016. ABS cat. no. 1270.0.55.001. Canberra: ABS.

ABS 2016b. Australian Statistical Geography Standard (ASGS): Volume 5—Remoteness structure, July 2016. ABS cat. no. 1270.0.55.005. Canberra: ABS.

ACCD (Australian Consortium for Classification Development) 2018. The international statistical classification of diseases and related health problems, 10th revision, Australian modification (ICD-10-AM), 11th edn. Tabular list of diseases and alphabetic index of diseases. Adelaide: IHPA, Lane Publishing.

AIHW (Australian Institute of Health and Welfare) 2010. Indigenous identification in hospital separations data: quality report. Health services series no. 35. Cat. no. HSE 85. Canberra: AIHW.

AIHW 2012. National Health Data Dictionary. Version 16 Cat. no. HWI 119. Canberra: AIHW.

AIHW 2013. Indigenous identification in hospital separations data: quality report. Cat. no. IHW 90. Canberra: AIHW.

AIHW 2015a. National Health Data Dictionary: version 16.1. National Health Data Dictionary series. Cat. no. HWI 130. Canberra: AIHW.

AIHW 2015b. National Health Data Dictionary: version 16.2. National Health Data Dictionary series. Cat. no. HWI 131. Canberra: AIHW.

Centre for Epidemiology and Evidence (2019). Reporting of hospitalisation-related indicators on HealthStats NSW: Impact of changes to emergency department admissions. Statistical Method No. 8 April 2019. HealthStats NSW. Sydney: NSW Ministry of Health.  Viewed 18 January 2021.