Patient Experiences in Australia: Summary of Findings methodology

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Reference period
2020-21 financial year
Released
17/11/2021

Overview

This publication contains results from the Patient Experience Survey, a topic on the Multipurpose Household Survey (MPHS) conducted throughout Australia from July 2020 to June 2021. The MPHS, undertaken each financial year by the Australian Bureau of Statistics (ABS), is a supplement to the monthly Labour Force Survey (LFS) and is designed to collect statistics for a number of small, self-contained topics.

The survey collected information from people about their experiences with selected aspects of the health system in the 12 months before their interview, including access and barriers to a range of health care services. Respondents were asked about their experiences with health professionals, the frequency of their visits, waiting times, and barriers to accessing care, as well as their self-assessed health status, long-term health conditions and private health insurance.  Labour force characteristics, education, income and other demographics were also collected.

Data collection

Scope

The scope of the survey was restricted to people aged 15 years and over who were usual residents of private dwellings and excludes:

  • members of the Australian permanent defence forces
  • certain diplomatic personnel of overseas governments, customarily excluded from Census and estimated resident population counts
  • overseas residents in Australia
  • members of non-Australian defence forces (and their dependants)
  • persons living in non-private dwellings such as hotels, university residences, boarding schools, hospitals, nursing homes, homes for people with disabilities, and prisons
  • persons resident in the Indigenous Community Strata (ICS).

The scope for MPHS included households residing in urban, rural, remote and very remote parts of Australia, except the ICS.

Coverage

In the LFS, rules are applied which aim to ensure that each person in scope is associated with only one dwelling, and hence has only one chance of selection in the survey. See Labour Force, Australia for more detail.

Sample size

Information was collected from 28,386 fully responding persons. This includes 486 proxy interviews for people aged 15 to 17 years, where permission was not given by a parent or guardian for a personal interview.

Collection method

The survey is one of a number of small, self-contained topics on the MPHS.

Each month, one eighth of the dwellings in the LFS sample were rotated out of the survey and selected for the MPHS. After the LFS had been fully completed for each person in scope and coverage, a usual resident aged 15 years or over was selected at random (based on a computer algorithm) and asked the additional MPHS questions in a personal interview. 

In the MPHS, if the randomly selected person was aged 15 to 17 years, permission was sought from a parent or guardian before conducting the interview. If permission was not given, the parent or guardian was asked the questions on behalf of the 15 to 17 year old (proxy interview).

Data were collected using Computer Assisted Interviewing (CAI), whereby responses were recorded directly onto an electronic questionnaire in a notebook computer, with interviews conducted over the telephone. 

Processing the data

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Classifications

Country of birth

Education

Industry

Socio-economic Indexes for Areas (SEIFA)

Comparing the data

Comparability of Time Series

When comparing data from different cycles of the survey, users are advised to consult the questionnaires (available from the Data downloads section), check whether question wording or sequencing has changed, and consider whether this may have had an impact on the way questions were answered by respondents.

All data items shown in time series tables are comparable between the survey cycles presented. 

Comparability to monthly LFS Statistics

Since the survey is conducted as a supplement to the LFS, data items collected in the LFS are also available in this publication. However, there are some important differences between the two surveys. The scope of the Patient Experience Survey and the LFS differ (refer to the Scope section above). Due to the differences between the samples, data from this survey and the LFS are weighted separately. Differences may therefore be found in the estimates for those data items collected in the LFS and published as part of the Patient Experience Survey.

Comparability with other ABS surveys

Caution should be taken when comparing across ABS surveys and with administrative by-product data that address the access and use of health services. Estimates from the Patient Experience Survey may differ from those obtained from other surveys (such as the National Aboriginal and Torres Strait Islander Health Survey, National Aboriginal and Torres Strait Islander Social Survey, National Health Survey, General Social Survey and Survey of Disability, Ageing and Carers) due to differences in survey mode, methodology and questionnaire design.

Data Release

Datacubes/spreadsheets 

Data Cubes containing all tables for this publication in Excel spreadsheet format are available from the Data downloads section of the main publication. The spreadsheets present tables of estimates and proportions, and their corresponding relative standard errors (RSEs) and/or Margins of Error (MOEs).

As well as the statistics included in this and related publications, the ABS may be able to provide other relevant data on request. Subject to confidentiality and sampling variability constraints, tables can be tailored to individual requirements for a fee. A list of data items from this survey is available from the Data downloads section. All enquiries should be made to the Customer Assistance Service on 1300 135 070, or email client.services@abs.gov.au.

DataLab

Detailed microdata will be available in DataLab for approved users who are required to undertake interactive (real time) complex analysis of microdata in the secure ABS environment. For more details, refer to About DataLab.

Confidentiality

To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves a small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as TableBuilder.

Glossary

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Abbreviations

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