Australian Institute of Health and Welfare (2022) Principal diagnosis data cubes, AIHW, Australian Government, accessed 31 January 2023.
Australian Institute of Health and Welfare. (2022). Principal diagnosis data cubes. Retrieved from https://www.aihw.gov.au/reports/hospitals/principal-diagnosis-data-cubes
Principal diagnosis data cubes. Australian Institute of Health and Welfare, 08 July 2022, https://www.aihw.gov.au/reports/hospitals/principal-diagnosis-data-cubes
Australian Institute of Health and Welfare. Principal diagnosis data cubes [Internet]. Canberra: Australian Institute of Health and Welfare, 2022 [cited 2023 Jan. 31]. Available from: https://www.aihw.gov.au/reports/hospitals/principal-diagnosis-data-cubes
Australian Institute of Health and Welfare (AIHW) 2022, Principal diagnosis data cubes, viewed 31 January 2023, https://www.aihw.gov.au/reports/hospitals/principal-diagnosis-data-cubes
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The data cubes can be used to explore a range of clinical data related to hospital separations. This document will provide some tips on how to utilise the data cubes generally and how to deal with the different formats in which the cubes are provided.
From the 2015-16 financial year, hospitals data cubes have been made available in excel format. Prior to 2015-16 hospitals data cubes are available in the SAS cubes software. The guide for extraction of information from these cubes depends on the format in which they are available.
The excel data cube workbooks consist of two sheets:
Variables in the ROWS list can be removed to disaggregate at higher levels.
Variable such as age group, sex and/or same-day flag can be dragged to the COLUMNS list to disaggregate by these variables.
The cubes contain information on the number of separations and number of patient days. Once the cube has been aggregated/disaggregated to the desired level, average length of stay can be calculated as number of patient days/number of separations.
These data cubes will open in a new window. Data will be displayed at the most aggregated level.
Clicking on the plus (+) symbols against each row will expand that item into its relevant sub categories, within the current view.
Clicking the arrow symbols beside the plus will expand the category and also limit the view to just that expanded area of interest.
Right clicking on category headings such as ICD Diagnosis Chapter will bring up a menu where you can click ‘Expand All’, which will expand every item in that list. If you also do this with the subchapter and other headings you can expand out the entire data cube and display all of the available information.
In the default view, the cube will just present the number of hospital separations by year but you can also add other breakdowns such as by Age group, sex, and patient days or average length of stay..
To add an extra breakdown, right click on one of the numbers in the cube and choose ‘Assign data’.
Then choose which variables to add to rows or columns of the cube.
The current view of the data cube can easily be exported to Excel by choosing ‘Export…’ from the ‘File’ menu, and then saving the zipped file to your computer. When extracting the zip archive you will need to extract all files in the archive before opening the downloaded Excel document.
To do this, first see the notes about Expanding the categories and sub categories first and using Expand All. Then once you have the full view of the cube, export the data as per the step above.
Note that the use of the different ICD editions in the data cubes over time means that data across years may not be exactly comparable.
Within the cubes, users can view the diagnoses by working down from the broad chapter level in the ICD classifications to more specific categories (i.e. principal diagnosis code), as illustrated below:
Users of the data cubes are likely to require some familiarity with ICD-9-CM and ICD-10-AM and can also refer to the Australian Hospital Statistics publications. Users will generally need to know what chapter the information they are looking for is in, to work down to more specific levels of detail. More information about the breakdowns and categories used within the data cube are given below.
Principal diagnoses are classified according to either the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) or the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM). The use of the different classifications (ICD-9-CM and ICD-10-AM) in the data cubes means that data from 1998–99 onwards may not be exactly comparable with the earlier data (1993-94 to 1997-98).
In addition, there are some differences in the coding between ICD-10-AM editions and these will be reflected in the cube. Readers should refer to further information below for information on how to access the full classification and for detailed information on the differences between ICD-9-CM, ICD-10-AM and the different editions of ICD-10-AM.
The following is a list of the ICD disease chapters used in the data cube and the code ranges covered by each:
Certain infectious and parasitic diseases
Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism
Endocrine, nutritional and metabolic diseases
Mental and behavioural disorders
Diseases of the nervous system
Diseases of the eye and adnexa
Diseases of the ear and mastoid process
Diseases of the circulatory system
Diseases of the respiratory system
Diseases of the digestive system
Diseases of the skin and subcutaneous tissue
Diseases of the musculoskeletal system and connective tissue
Diseases of the genitourinary system
Pregnancy, childbirth and the puerperium
Certain conditions originating in the perinatal period
Congenital malformations, deformations and chromosomal abnormalities
Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified
Injury, poisoning and certain other consequences of external causes
External Causes of Morbidity and Mortality
Factors influencing health status and contact with health services
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