Health checks and follow-ups for Aboriginal and Torres Strait Islander people

Counting services and patients

This report presents data using 2 different counting units:

• services – that is, the number of health checks (or follow‑ups, as applicable) provided in the specified period
• patients – that is the number of people who received 1 or more health checks (or follow‑ups, as applicable) in the specified period.

In any given period (for example, 12 months), the number of patients may be smaller than the number of services provided. This occurs when patients have received more than 1 service in that period.

In this report, most figures and explanatory text relate to the number of patients (rather than services). Proportions of the population have been calculated using the number of patients only.

Some proportions are also presented in terms of a pool of relevant patients, for example, the proportion of health check patients who received a follow-up service, or the proportion of health check patients who received at least 2 health checks over a 5-year period.

Patient information in the MBS data set is attached to each service. Patients’ age can be calculated in different ways. There were some differences between the methods used for the analyses presented in this report and the one used for previous editions:

• For counts of patients who received a health check or follow-up: age was calculated from the date of the end of the reference period (reference month or reference year, depending on how data are presented).
  • This method was used to better align with the population structure at the end of the reference period. The population at the end of the reference period was used as the denominator for calculation of proportions of the population.
• For numbers of health checks over 5-years: patients’ age was calculated from the date at the end of the reference period.
  • This method was used to better align with the population structure at the end of the reference period.
• For time between health checks: patients’ age was calculated from the date at the end of the reference year.
  • This method was used for consistency with other outputs.
• For numbers of services: patients’ age was calculated the same way as for numbers of patients.
  • This method was used for simplicity, so that the same individuals would contribute to patient counts and service counts.

Note: Since patients are assigned to only one age group in a given year, it is safe to combine data from multiple age groups if required. Similarly, combining data from multiple regions is generally safe, however rounding errors may compound to give slightly inaccurate sums.

Dates and reference periods

The MBS data set includes information on the date the service was provided, as well as the date that the claim was processed by Medicare. These dates can differ due to a time lag between when a service is provided and when the claim for that service is processed by Medicare.

Most data in this report relate to services provided between 1 January 2013 and 31 December 2023, which were processed on or before 31 March 2024, except for the analysis of ‘time between health checks’, which covers activity back to 1999. Data are reported by date of service as this more accurately reflects when the service was provided. Due to lags between date of service and date of processing, there will be a small proportion of services provided during the reference period that are not captured in these data. For example, if a service was provided on 30 December 2023, but not processed until after 31 March 2024, it will not be included in the data.

Data in this report are presented in a few different ways, in terms of reference period:

• For health check uptake – with the addition of calendar year data (previously, only financial year data were published), it is more conventional to show these periods interspersed in reference to the last month of each period (June for financial years, and December for calendar years). Users may validly refer to the data by calendar year or financial year instead.
• For cumulative health checks (over a 5-year period), data are presented in terms of the 5-year period that they cover, from July to June – for example, ‘July 2018 to June 2023’.
• For ‘time between health checks’ analysis, the reference year refers to financial years. Patients from each financial year are analysed based on their history of health checks back to 1999.
• For counts of follow-up patients and services by age group and sex, data are presented the same way as for health check uptake (by reference month).
• For counts of follow-up patients and services by practitioner type, data are presented for financial years.
• For health checks resulting in a follow-up, data are presented by the calendar year and financial year in which health checks were delivered. Presenting these in reference to June or December would not suitably describe this measure.

Geographic information

Geographic correspondences (sometimes referred to as concordances or mapping files) can be used where the location information in an original data is not available at the geographic level required for analysis and reporting. Geographic correspondences are a mathematical method for reassigning data from one geographic classification (for example, a postcode) to a new geographic classification (for example, remoteness area).

Geographic correspondences enable MBS data summated by postcode to be reported at various other geographic levels. However, there are various limitations associated with the use of postcode data for this purpose. Key issues include that:

• postcodes do not fit neatly into the boundaries of geographic areas typically used for statistical reporting
• defining geographic boundaries for postcodes is an imprecise process – postcodes can also change over time
• people may not keep their postcode information up-to-date with Medicare
• postcodes linked to patient records may belong to PO boxes or another mailing address, making correspondence to geographic areas potentially less accurate.

Due to these issues, various decisions need to be made about how best to allocate the postcode data to geographic regions. There will be some degree of inaccuracy in the resultant estimates, which will affect data in certain areas more than others – see Box 1 later on this page.

For this report, postcodes were re-assigned to 6 different geographies (based on the 2016 Australian Statistical Geography Standard) – Statistical Areas Level 3 (SA3s), Statistical Areas Level 4 (SA4s), Indigenous Regions (IREGs), Primary Health Networks (PHNs), Remoteness Areas, and states and territories. Where postcodes fell across the boundaries of multiple areas (for example, multiple SA4s), data were apportioned based on the population distribution of Indigenous Australians, according to AIHW analysis of ABS population estimates at 30 June 2016. Records with invalid postcode information could not be assigned to sub-national areas.

For patients who had more than one health check or follow-up in a given reference period, postcode information from the last MBS service was used for determining geographic location. When counting health check patients, only health check services were used for this purpose.

For certain geographic levels (PHN, IREG, SA4 and SA3), some of the Tableau figures allow areas to be filtered according to remoteness categories (Major cities, Inner and Outer regional, Remote and Very remote). These categories were assigned for each area based on the proportion of the Aboriginal and/or Torres Strait Islander Census count in 2016, across the 3 remoteness categories.

Measuring time between health checks

To report the time interval between patients’ consecutive health checks (based on date of service), 2 slightly different methods were used to convert the days to months:

For ranges of months (for example, ‘Less than 12 months’, ’12–‍14 months’): the number of fully elapsed calendar months were calculated – where a calendar month has fully elapsed when the day's date returns to or surpasses the same-numbered day in consecutive months.

For example, a patient who received a health check on both 1 January 2022 and 1 January 2023 saw 12 calendar months elapse between health checks, whilst a patient who received a health check on both 1 January 2022 and 31 December 2022 saw only 11 calendar months elapse between health checks.

For mean and median time intervals: days were converted to months based on the average number of days per month {days ÷ (365÷12)}. This allowed for higher precision and accuracy compared with calculating means and medians from the number of fully elapsed months. Estimates were rounded downward to 0.1 of a month.

Comparability with other reports

As described in the Dates and reference periods section, the data in this report are based on the date of service (rather than date of processing), as this more accurately reflects when the service was provided. Data in this report may differ to those published elsewhere based on date of processing, including previous editions of this report. It may also differ to data published elsewhere based on date of service, where the date of processing cut-off is different. In certain cases, data with the same processing cut-off date may also differ slightly if patients’ sex or date of birth are changed on the live patient dataset linked to MBS records. Age and location were also determined in a slightly different way to previous editions of this report (see Counting services and people and Geographic information, presented earlier).

For uptake calculation in this report, the population at the end of the reference period was used as the denominator. In previous editions of this report, the population at the midpoint of each year was used. This method change means age is calculated the same way for patients and the population.

In addition, this report primarily uses population estimates and projections, based on the 2016 Census, when calculating proportions. The proportions presented here may differ to those released in future updates of this report (or in other reports) when revised estimates based on the 2021 Census are used instead.