QUALITY DECLARATION - SUMMARY
For information on the institutional environment of the Australian Bureau of Statistics (ABS), including the legislative obligations of the ABS, financing and governance arrangements, and mechanisms for scrutiny of ABS operations, please see ABS Institutional Environment.
For the 2013–14 iteration, data on Patient Experience were collected as part of the 2013–14 Multipurpose Household Survey (MPHS) which was supplemented by additional sample selected in particular areas using a separate survey called the Health Services Survey (HSS). The additional sample was collected to improve the quality of estimates at the Medicare Local catchment level. Sample from the MPHS and HSS were combined to produce one set of output.
The MPHS is a supplement to the monthly Labour Force Survey (LFS) and is designed to collect annual statistics on a small number of self-contained topics. The HSS is an independent survey, with sample selected within a subset of 31 Medicare Local catchments in 5 states (New South Wales, Victoria, Queensland, South Australia and Western Australia).
Respondents, aged 15 years and over, are asked questions about their experiences with health services in Australia. The type of information collected includes their experiences with general practitioners, dentists, medical specialists and hospitals, as well as their use of pathology and imaging tests. In the MPHS, information is collected from one person selected at random in each selected household. In the HSS, information is collected from up to two people selected at random in each selected household.
The scope of the LFS is restricted to people aged 15 years and over and excludes members of the permanent defence forces; certain diplomatic personnel of overseas governments usually excluded from Census and estimated resident populations; overseas residents in Australia; and members of non-Australian defence forces (and their dependants). Refer to Labour Force, Australia (cat. no. 6202.0) for further information regarding the LFS. In addition, the 2013–14 MPHS excluded people living in Indigenous communities and people living in non-private dwellings such as hotels, university residences, students at boarding schools, patients in hospitals, inmates of prisons and residents of other institutions (e.g. retirement homes, homes for persons with disabilities).
The scope of the HSS matches the scope of the MPHS. The coverage of the HSS was the same as the scope, except that persons living in Indigenous Communities in non-very remote areas and those living in very remote areas were not covered for operational reasons.
The MPHS is collected annually with enumeration undertaken over the financial year period from July 2013 to June 2014. The Patient Experience topic is collected via the MPHS each year, and started in 2009. Generally, data are released approximately five months after the end of MPHS enumeration. Enumeration of the HSS was undertaken from September to December 2013.
The LFS, and consequently the MPHS, is primarily designed to provide estimates for the whole of Australia and, secondly, for each state and territory. Additional sample was collected for 2013–14 via the HSS to improve the quality of estimates at the Medicare Local catchment level.
Two types of error are possible in an estimate based on a sample survey: non-sampling error and sampling error. Non-sampling error arises from inaccuracies in collecting, recording and processing the data. Every effort is made to minimise reporting error by the careful design of questionnaires, intensive training and supervision of interviewers, and efficient data processing procedures. Non-sampling error also arises because information cannot be obtained from all persons selected in the survey.
Sampling error occurs because a sample, rather than the entire population, is surveyed. One measure of the likely difference resulting from not including all dwellings in the survey is given by the standard error (SE). There are about two chances in three that a sample estimate will differ by less than one SE from the figure that would have been obtained if all dwellings had been included in the survey, and about 19 chances in 20 that the difference will be less than two SEs. Measures of the relative standard errors (RSE) of the estimates for this survey are included with this release.
Only estimates (numbers and proportions) with RSEs less than 25% are considered sufficiently reliable for most purposes. Estimates with RSEs between 25% and 50% have been included and are annotated to indicate they are subject to high sample variability and should be used with caution. In addition, estimates with RSEs greater than 50% have also been included and annotated to indicate they are considered too unreliable for general use.
The ABS seeks to maximise consistency and comparability over time by minimising changes to the survey. Sound survey practice, however, requires ongoing development to maintain and improve the integrity of the data. Due to changes in the questionnaire, certain data items from each iteration of the Patient Experience Survey are not comparable year to year. For changes between iterations of the survey please refer to the Data Comparability section of the Explanatory Notes.
Due to differences in collection methods and question wording, health data collected in the Patient Experience Survey may not be comparable with data from other ABS health surveys, such as the National Health Survey or the National Aboriginal and Torres Strait Islander Health Survey.
To aid in the interpretation of the data, detailed information on concepts, definitions, terminology and other technical aspects of the survey can be found in the relevant web pages included with this release.
All tables and associated RSEs are available in Excel spreadsheets which can be accessed from the Downloads tab.
Additional tables may also be available on request. The Downloads tab also includes a document containing a complete list of the data items available. Note that detailed data can be subject to high RSEs and, in some cases, may result in data being confidentialised.