Health‑related classifications have multiple purposes, including the facilitation of data collection and management in the clinical setting, the analysis of data to inform health policy, and the allocation of financial and other resources. This section provides a short description of the classification systems referenced in this report.
The Australian Classification of Health Interventions (ACHI) is the Australian national standard for procedure and intervention coding in Australian hospitals.
The National Centre for Classification in Health (NCCH) developed the ACHI based on the Medicare Benefits Schedule (MBS). The MBS is a fee schedule for Medicare services including general practice consultations, specialist consultations, surgical procedures and other medical services, such as diagnostic investigations and optometric services. The Department of Health (DoH) updates the MBS at least twice each year and these code changes are incorporated into the ACHI or the MBS codes are mapped to existing ACHI codes.
The ACHI classifies procedures and interventions performed in public and private Australian hospitals, day centres and ambulatory settings, as well as allied health interventions, dentistry and imaging. The structure of the ACHI is anatomically based, rather than based on the medical speciality.
To maintain parity with disease classification, ACHI chapters resemble the International Statistical Classification of Diseases and Related Health Problems, 10th revision, Australian Modification (ICD‑10-AM chapters). The ACHI is updated biennially by the National Casemix and Classification Centre (NCCC) in line with the disease section of the ICD‑10‑AM. Use of the codes is guided by the Australian Coding Standards of the ICD‑10‑AM.
Further information on the ACHI is available from the Independent Health and Aged Care Pricing Authority (IHACPA) website.
Primary Health Networks are organisations that connect health services across a specific geographic area (a PHN area), with the boundaries defined by the Australian Government Department of Health. There are 31 PHN areas that cover the whole of Australia. Further information is available on the Department of Health and Aged Care website.
The Australian Statistical Geography Standard (ASGS) was developed by the Australian Bureau of Statistics (ABS) for the collection and dissemination of geographically classified statistics. It is a common framework that enables publication of statistics that are comparable and spatially integrated and is an essential reference for understanding and interpreting the geographical context of Australian statistics.
The ASGS replaces the Australian Standard Geographical Classification (ASGC) and has been utilised for release of data from the 2016 Census of Population and Housing.
Statistical Areas – Statistical Areas are a geographical classification defined by the Australian Bureau of Statistics. They encompass 4 levels, with increasing size and population: Statistical Areas Level 1 (SA1s); Statistical Areas Level 2 (SA2s); Statistical Areas Level 3 (SA3s); and Statistical Areas Level 4 (SA4).
In some data sections, aggregate SA3 data were mapped to PHNs using correspondence files as sourced from Australian Statistical Geography Standard (ASGS): Volume 3 - Non ABS Structures (ABS cat.no. 1270.0.55.003). Population estimates for SA3s as at 30 June were mapped to PHNs using this method.
Where applicable, data from previous collection periods where data were reported with SA3 2011 boundaries were mapped to 2016 to allow for historical comparisons. Correspondence are sourced from Australian Statistical Geography Standard (ASGS): Volume 1 - Main structure and Greater Capital City Statistical Areas (ABS cat.no. 1270.0.55.001).
Australian Statistical Geography Standard (ASGS) is the geographical framework defined by the Australian Bureau of Statistics (ABS) for disseminating geographically classified statistics (ABS 2011, ABS 2016). In this report, the ASGS applies to the data presented by remoteness area. For data from 2017–18 onwards, the ASGS 2016 is used; earlier years use ASGS 2011. ASGS is categorised into Remoteness Areas (RAs). RAs aggregate to states and territories and cover the whole of Australia without gaps or overlaps.
This report uses the ASGS to present data in the following categories:
For further information on this classification system, refer to the ABS website
The ABS Socio-Economic Indexes For Areas Index of Relative Socio-economic Disadvantage (SEIFA IRSD) is used to report Australian socio-economic data (ABS 2014, ABS 2016). SEIFA scores are calculated by taking into account social and economic indicators of advantage and disadvantage, such as education, occupation, employment, income, families, and housing, and are used to summarise the socio-economic conditions of a geographical area (ABS 2014, ABS 2016).
These scores are categorised into 5 groups, referred to as quintiles, which each represent one-fifth (20%) of the population (ABS 2014, ABS 2016). Quintile 1 is the most disadvantaged group (worst off) and quintile 5 is the least disadvantaged group (best off) (ABS 2014, ABS 2016). A geographical area with a low SEIFA score will likely comprise of a higher proportion of people who are relatively disadvantaged and a lower proportion of people who are relatively advantaged.
More information can be found on the ABS website
The Anatomical Therapeutic Chemical (ATC) Classification System, developed by the World Health Organization (WHO), assigns therapeutic drugs to different groups according to the body organ or system on which they act, as well as their therapeutic and chemical characteristics.
The coding of pharmaceutical products within the Schedule of Pharmaceutical Benefits is based on the ATC Classification System but with some differences as outlined in the relevant data source sections.
For further information on this classification system, refer to the WHO website.
The International Classification of Diseases (ICD), which was developed by the WHO, is the international standard for coding morbidity and mortality statistics. It was designed to promote international comparability in the collection, processing, classification and presentation of these statistics. The ICD is periodically reviewed to reflect changes in clinical and research settings (WHO 2011).
Although the ICD is primarily designed for the classification of diseases and injuries with a formal diagnosis, it also classifies a wide variety of signs, symptoms, abnormal findings, complaints and social circumstances that may stand in place of a diagnosis.
Further information on the ICD is available from the WHO website.
The International Statistical Classification of Diseases and Related Health Problems, 9th revision, Clinical Modification (ICD–9–CM) is based on the ninth revision of the ICD (NCC 1996). The ICD–9–CM was the official system of assigning codes to diagnoses and procedures associated with hospital use in Australia before it was superseded by the ICD–10–AM.
The Australian Modification of ICD–10 (called ICD–10–AM) is used to classify diagnoses in the health sector in Australia. It is used in public and private hospitals, and in community and residential mental health care services. The ICD–10–AM was developed in Australia by the NCCH with the purpose of making ICD–10 more relevant to Australian clinical practice (NCCH 2006).
ABS (Australian Bureau of Statistics) 2011. Australian Statistical Geography Standard (ASGS): Volume 5 – Remoteness Structure, July 2011. ABS cat. No. 1270.0.55.005. Canberra: ABS.
ABS 2014. Socio-Economic Indexes for Areas (SEIFA). Canberra: ABS. Viewed December 2022
ABS 2016. 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 2016. Australian Statistical Geography Standard (ASGS): Volume 5 – Remoteness Structure, July 2016. ABS cat. No. 1270.0.55.005. Canberra: ABS.
ABS 2016. Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016. ABS cat. No. 2033.0.55.001. Canberra: ABS.
NCC (National Coding Centre) 1996. The Australian version of the international statistical classification of diseases and related health problems, 9th revision, clinical modification. Sydney: NCC.
NCCH (National Centre for Classification in Health) 2006. The international statistical classification of diseases and related health problems, 10th revision, Australian modification. Sydney: NCCH.
WHO (World Health Organization) 2010. ATC: International classification of diseases (ICD). Geneva: Viewed December 2015.
This section provides a list of codes used to define mental health-related general practice encounters from the Bettering the Evaluation and Care of Health (BEACH) database (as used in the general practice section) and mental health-related hospital separations from the National Hospital Morbidity Database (as used in the Admitted patients section).
Data from the National Hospital Morbidity Database (NHMD) are the source for the Admitted patients section of this site. The definition of the scope of each section is provided in the section’s introduction or data source. Key elements of these definitions depend on the ICD-10-AM diagnosis codes and the Australian Classification of Health Interventions (ACHI) procedure codes. The codes in-scope are listed below.
During the preparation of Mental health services in Australia 1999–00 (AIHW 2002), attention was given to ensuring that, for data on hospital separations from the NHMD, the definition of a ‘mental health-related diagnosis’ included all codes that were either clinically or statistically relevant to mental health. This definition was revised for Mental health services in Australia 2000–01 (AIHW 2003) to increase the accuracy of the data. More specifically, for the analyses of the 2000–01 National Hospital Morbidity data, a diagnosis was considered clinically relevant to mental health if:
A diagnosis was defined as being statistically relevant to mental health if:
This method was developed in consultation with the National Mental Health Working Group Information Strategy Committee (now called the Mental Health Information Strategy Standing Committee) and the Clinical Casemix Committee of Australia.
Certain codes were statistically relevant during 1999–00 but not in 2000–01; these were examined and included if over 50% of total separations over the 2 years included specialised psychiatric care.
For Mental health services in Australia, the same codes used for the analysis of the 2000–01 data have been used to define ‘mental health-related’ hospital separations in the Admitted patients section. However, updates have been made to incorporate changes in codes that have occurred as new editions of ICD-10-AM have been released.
The full list of codes used to define mental health-related hospital separations is shown in the following table.
..
Y
.. not applicable Y code used
The full list of ACHI codes as part of the definition of ambulatory-equivalent mental health-related hospital separations is shown in the following table. If there is no procedure recorded, or only procedure(s) in this list, and other criteria as outlined in Section 5 are met, then the separation will be categorised as ambulatory-equivalent.
ABS (Australian Bureau of Statistics) 2014. Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2011. ABS cat. no. 2033.0. Canberra: ABS.
ABS 2016. Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016 ABS cat. No. 2033.0.55.001. Canberra: ABS
AIHW (Australian Institute of Health and Welfare) 2002. Mental health services in Australia 1999–00. Mental health series no. 3. Cat. no. HSE 19. Canberra: AIHW.
AIHW 2003. Mental health services in Australia 2000–01. Mental health series no. 4. Cat. no. HSE 24. Canberra: AIHW.
WHO (World Health Organization) 2011. Anatomical Therapeutic Chemical (ATC) Classification. Geneva: WHO. Viewed 4 March 2021.
Throughout this site:
Data are reported at regional levels for some of the datasets. To report at this level, data were aggregated to Statistical Area Level (SA2). For years prior to 2017–18, SA2 are reported according to 2011 ASGS. These SA2s were concorded to 2016 ASGS using files published by the Australian Bureau of Statistics, to allow for comparisons across time. Data were then aggregated to SA3 and apportioned to PHN based on correspondence files published by the Australian Bureau of Statistics. Population data reported at SA3 level were mapped to PHNs using the same methodology. All data are mapped to 2017 PHN boundaries.
In this publication, crude rates were calculated using the Australian Bureau of Statistics estimated resident population (ERP) at the midpoint of the data range (for example, rates for 2015–16 data were calculated using the ERP at 31 December 2015, while rates for 2015 calendar year data were calculated using ERP at 30 June 2015).
Data for Victoria were not available for the 2011–12 and 2012–13 reporting periods for the Community mental health care section of Mental health services in Australia. Crude rates for national totals in this section were calculated by subtracting Victorian populations data from the National total. These population data were used in the denominator for calculating national ‘Total’ crude rates for these reporting periods.
Some data sources for the ACT were not available for the 2014–15 and/or 2015–16 reporting periods. Refer to the respective table footnotes for details. Crude rates for national totals in these sections were calculated by subtracting ACT populations data from the National total. These population data were used in the denominator for calculating national ‘Total’ crude rates.
The COVID-19 pandemic and the resulting Australian Government closure of the international border from 20 March 2020, caused significant disruptions to the usual Australian population trends. This report uses Australian Estimated Resident Population (ERP) estimates that reflect these disruptions.
In the year July 2020 to June 2021, the overall population growth was much smaller than the years prior and in particular, there was a relative large decline in the population of Victoria. ABS reporting indicated these were primarily due to net-negative international migration (National, state and territory population, June 2021, Australian Bureau of Statistics) .
Please be aware that this change in the usual population trends may complicate your interpretation of statistics calculated from these ERPs. For example, rates and proportions may be greater than in previous years due to decreases in the denominator 9Population size) of some sub-populations.
In this publication, some population rates are adjusted (standardised) for age to facilitate comparisons between populations that have different age structures, for example, between Indigenous Australians and non-Indigenous Australians. This publication uses direct standardisation in which age-specific rates are applied to a standard population (the ERP as at 30 June 2001 unless otherwise specified). This effectively removes the influence of age structure on the calculated rate that is described as the age-standardised rate. The method used for this calculation comprises 3 steps:
In some instances in this publication where the numbers in particular 5-year age groups are very small (less than 5), neighbouring age groups have been combined to enable the calculation of a meaningful crude rate.
Data for Victoria were not available for the 2011–12 and 2012–13 reporting period for the community mental health care section of Mental health services in Australia. Age-standardised rates for this section were calculated with Victorian population data excluded from the national total.
Some data for the ACT were not available for the 2014–15 and/or 2015–16 reporting periods. Refer to the respective table footnotes for details. Age-standardised rates for these sections were calculated excluding ACT population data.
In this publication, the average annual rates of change or growth rates have been calculated as geometric rates:
Average rate of change = ((Pn/Po)^(1/n) -1) x 100
where: Pn= value in the later time period Po= value in the earlier time period n = number of years between the 2 time periods.
Average annual rates of change are not calculated where data are incomplete.
A confidence interval is a range of values that is used to describe the uncertainty around an estimate, usually from a sample survey. Generally speaking, confidence intervals describe how different the estimate could have been if the underlying conditions stayed the same but variability in sampling (i.e. selecting a different sample from the population) had led to a different set of data. Confidence intervals are calculated with a stated probability (commonly 95%); this means that there is a 95% chance that the confidence interval includes the true value.
The National Mental Health Establishments Database collects information on direct and indirect recurrent expenditure. Direct recurrent expenditure comprises salaries and wages and selected non-salary expenditure, and is collected at the individual mental health service unit level. Indirect recurrent expenditure is additional expenditure associated with the provision of mental health services not incurred or reported at the individual service unit level. Indirect expenditure is reported at 3 overarching levels above the individual service unit level:
Some of these indirect expenditure items can be directly linked to the provision of services by the service units. Specifically, at the organisational and regional levels the expenditure on the following items is directly related to individual mental health service units and thus has been apportioned to units in the organisation or region reporting the indirect funds:
The apportioning of indirect expenditure is calculated on the total direct funds for the service, as a proportion of the total for all service units in the organisation or region. The total allocation or apportioning of funds is reported in the indirect expenditure rows in Table EXP.1.
The remaining indirect expenditure categories of education and training, research, mental health promotion, service development costs associated with the start up of new services and costs associated with the establishment and operation of jurisdictional Mental Health Act review bodies are not apportioned to mental health service units. State/territory level expenditure is also not apportioned to mental health service units. The total for these residual categories is reported in the row 'Other indirect expenditure' in Table EXP.1. Note that grants to non-government-organisations are not regarded as indirect expenditure.
Expenditure aggregates in this report are expressed in current prices and/or constant prices. The transformation of current prices to constant prices is termed 'deflation', using price indexes or 'deflators'. There are a variety of deflators that can be used to translate current prices into constant prices. The deflators that were used by AIHW for the various items in the Expenditure on mental health services section are outlined in the table below. For further information on the methodology used to calculate deflators, refer to Health expenditure Australia 2018–19 (AIHW 2020).
AIHW (Australian Institute of Health and Welfare) 2020. Health expenditure Australia 2018–19. Cat. no. HWE 80. Canberra: AIHW.
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