The Australian National Health Survey (NHS), conducted every three years by the Australian Bureau of Statistics (ABS), provides a nationally representative profile of Australians' health and wellbeing. The 2017-18 survey collected self-reported data on health, demographics, and lifestyle factors from both adults and children, offering valuable insights into the nation's health status and behaviors through a comprehensive sampling design.

These are free text responses from Australian healthcare workers captured during a campaign advocating for better work, health and safety standards during the COVID-19 pandemic. They have been redacted in parts to preserve anonymity. These stories accompany a publication by Ananda-Rajah et al in BMJ Leader, 2020.

The Australian Longitudinal Study on Women's Health (ALSWH) is a longitudinal population-based survey, first funded in 1995, which examines the health of over 57,000 Australian women. The Study explores factors that influence health among women who are broadly representative of the entire Australian population. ALSWH goes beyond a narrow perspective that equates women's health with reproductive and sexual health, and takes a comprehensive view of all aspects of health throughout women's lifespan. This cohort, women born 1989-95, were recruited in 2013. The cohort is regularly (to date, either annually, or biennially) surveyed via an online questionnaire covering issues regarding overall physical and emotional health, use of health services, education and employment status, drug and/or alcohol use, diet, exercise, and family situation. A detailed description of the background, aims, themes, methods and progress of the study is given on the project web page https://www.alswh.org.au/about/. This particular dataset refers to Survey 1 of the cohort and is a part of the Core Data Release. Some data in this data release were modified to maintain the confidentiality of ALSWH respondents.

In a survey conducted in Australia in October 2021, over one-fifth of respondents indicated that they felt they had been disrespected or discriminated against while receiving healthcare in Australia in the 12 months leading up to the survey. Over 80 percent of the respondents who identified as Aboriginal and/or Torres Strait Islander responded "yes" to the survey question.

ACT component of the Australian Secondary Students' Alcohol and Drug survey (ASSAD). The data is presented by the ACT Government for the purpose of disseminating information for the benefit of the public. The ACT Government has taken great care to ensure the information in this report is as correct and accurate as possible. While the information is considered to be true and correct at the date of publication, changes in circumstances after the time of publication may impact on the accuracy of the information. Differences in statistical methods and calculations, data updates and guidelines may result in the information contained in this report varying from previously published information.

There is limited research on speech-language pathology (SLP) weekend service provision across Australian healthcare services. Therefore, this study aimed to examine weekend SLP services in Australian healthcare services and explore SLP manager perspectives regarding the provision of these services. A mixedmethods, cross-sectional survey design was employed. SLP managers (or their facility representatives) from Australian healthcare services completed the survey. Quantitative data were analysed using descriptive statistics and qualitative data using qualitative content analysis. Data from 67 participants were analysed. More than half of the participants’ facilities (n = 39, 58.2%) provided a weekend speech pathology service. Most of these facilities were publicly funded (n = 62, 92.5%) and located in metropolitan areas (n = 41, 61.2%). Nearly two-thirds of facilities employed a dedicated speech-language pathologist for weekend service provision (n = 25/38, 65.8%). Service eligibility criteria were highly variable across sites. More than half (n = 37, 52.2%) of participants predicted a future need for increased weekend SLP services to service subacute wards and to enable access to senior clinicians. There is variability in weekend SLP service provision, eligibility criteria, and staffing profiles in healthcare facilities around Australia. Further research is required to understand how to inform optimal service delivery models for equitable client care and determine the value of weekend SLP services.

This dataset presents the footprint of the age-standardised percentage of adults who perform insufficient weekly physical activity. Insufficient physical activity is defined as those aged 18-64 years who did not complete over 150 minutes of physical activity, and at least 5 sessions over a week, and those aged 65+ years who did not complete 30 minutes of activity on at least 5 days in a week. As an indication of the accuracy of estimates, 95% confidence intervals were produced. These were calculated by the Australian Bureau of Statistics (ABS) using standard error estimates of the proportion. The data spans the financial year of 2014-2015 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).

Health risk factors are attributes, characteristics or exposures that increase the likelihood of a person developing a disease or health disorder. Examples of health risk factors include risky alcohol consumption, physical inactivity and high blood pressure. High-quality information on health risk factors is important in providing an evidence base to inform health policy, program and service delivery.

For further information about this dataset, visit the data source: Australian Institute of Health and Welfare - Health Risk Factors in 2014-2015 Data Tables.

Please note:

• AURIN has spatially enabled the original data using the Department of Health - PHN Areas.

• Age-standardisation is a method of removing the influence of age when comparing populations with different age structures - either different populations at the same time or the same population at different times. For this data the Australian estimated resident population of people aged 18 and over as at 30 June 2001 has been used as the standard population.

• Adults are defined as persons aged 18 years and over.

• Values assigned to "n.p." in the original data have been removed from the data.

• Data for PHN107 should be interpreted with caution, as the estimates have a relative standard error of 25% to 50%.

• Data for PHN701 (Northern Territory) should be interpreted with caution as the National Health Survey excluded discrete Aboriginal and Torres Strait Islander communities and very remote areas, which comprise around 28% of the estimated resident population of the Northern Territory living in private dwellings.

This dataset presents the footprint of the percentage of adults who saw three or more health professionals for the same condition in the preceding 12 months. The data spans the years of 2014-2017 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).

The data is sourced from the Australian Bureau of Statistics (ABS) 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. It also includes data from previous Patient Experience Surveys conducted in 2013-14, 2014-15 and 2015-16. The Patient Experience Survey is conducted annually by the ABS and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patient Experience Survey collects data on persons aged 15 years and over, who are referred to as adults for this data collection.

For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Patient experiences in Australia Data Tables.

Please note:

• AURIN has spatially enabled the original data using the Department of Health - PHN Areas.

• Percentages are calculated based on counts that have been randomly adjusted by the ABS to avoid the release of confidential data.

• As an indication of the accuracy of estimates, 95% confidence intervals were produced. These were calculated by the ABS using standard error estimates of the proportion.

• Some of the patient experience measures for 2016-17 have age-standardised rates presented. Age-standardised rates are hypothetical rates that would have been observed if the populations studied had the same age distribution as the standard population.

• Crude rates are provided for all years. They should be used for understanding the patterns of actual service use or level of experience in a particular PHN.

• The Patient Experience Survey excludes persons aged less than 15 years, persons living in non-private dwellings and the Indigenous Community Strata (encompassing discrete Aboriginal and Torres Strait Islander communities).

• Data for Northern Territory should be interpreted with caution as the Patient Experience Survey excluded the Indigenous Community Strata, which comprises around 25% of the estimated resident population of the Northern Territory living in private dwellings.

• NP - Not available for publication. The estimate is considered to be unreliable. Values assigned to NP in the original data have been set to null.

This dataset presents the statistics of prevalence for chronic kidney disease (CKD) distributed by age for the years between 2011-2012. The data is aggregated to 2015 Primary Health Network (PHN) geographic boundaries based on the 2011 Australian Statistical Geography Standard (ASGS). The chronic kidney disease (CKD) datasets were released by the Australian Institute of Health and Welfare (AIHW) to present data on prevalence, treatment (hospitalisations for CKD and dialysis) and deaths. It shows the distribution of the impact of CKD across Australia and visualises rates of CKD and the health and demographic profile for local areas. The data was modelled by the AIHW from the 2011-12 Australian Bureau of Statistics (ABS) Australian Health Survey (AHS): National Health Measures Survey.

A detailed description of the background, aims, themes, methods and progress of the study is given on the project web page https://www.alswh.org.au/about/. The Australian Longitudinal Study on Women's Health - widely known as Women's Health Australia - is a longitudinal population-based survey, which examines the health of over 40,000 Australian women over a 20 year period. It was first funded in 1995. The project was designed to explore factors that influence health among women who are broadly representative of the entire Australian population. The study goes beyond a narrow perspective that equates women's health with reproductive and sexual health, and takes a comprehensive view of all aspects of health throughout women's lifespan. The first wave was conducted in 1996, which was segregated into three groups, the 1973-1978 (Young) cohort, the 1946-1951 (Mid-age) cohort, and the 1921-1926 (Old-age) cohort. Each cohort received a different questionnaire, which varied in the types of questiones asked, but in essence covered issues regarding overall physical and emotional health, use of health services, education and employment status, drug and/or alcohol use, diet, exercise, and family situation. This particular dataset refers to wave five of the 1921-1926 (Old-age) cohort.

The National Drug Strategy Household Survey (NDSHS) is a national survey providing cross sectional data on alcohol and other drug use in Australia. The survey also provides estimates of licit and illicit drug use. The survey also measures community attitudes to drug use, and awareness of and community support for various drug-related policies.

This dataset presents the footprint of the crude percentage of adults who have high blood pressure. High blood pressure (or hypertension), is defined as including any of the following; systolic blood pressure greater than or equal to 140 mmHg, or; diastolic blood pressure greater than or equal to 90 mmHg, or; receiving medication for high blood pressure. As an indication of the accuracy of estimates, 95% confidence intervals were produced. These were calculated by the Australian Bureau of Statistics (ABS) using standard error estimates of the proportion. The data spans the financial year of 2014-2015 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).

Health risk factors are attributes, characteristics or exposures that increase the likelihood of a person developing a disease or health disorder. Examples of health risk factors include risky alcohol consumption, physical inactivity and high blood pressure. High-quality information on health risk factors is important in providing an evidence base to inform health policy, program and service delivery.

For further information about this dataset, visit the data source: Australian Institute of Health and Welfare - Health Risk Factors in 2014-2015 Data Tables.

Please note:

• AURIN has spatially enabled the original data using the Department of Health - PHN Areas.

• The health risks factors reported are known to vary with age and the different PHN area populations are known to have a range of age structures. As such, comparisons of results between the PHN areas should be made with caution because the crude rates presented do not account for these age differences.

• Adults are defined as persons aged 18 years and over.

• Values assigned to "n.p." in the original data have been removed from the data.

• Data for PHN701 (Northern Territory) should be interpreted with caution as the National Health Survey excluded discrete Aboriginal and Torres Strait Islander communities and very remote areas, which comprise around 28% of the estimated resident population of the Northern Territory living in private dwellings.

This statistic displays the Australian results of a survey on global views on healthcare in 2018. According to data provided by Ipsos, about 64 percent of respondents from Australia agreed with the statement that they get all the medical care they need.

7 percent of Australian respondents answer our survey on "Fitness and health service online purchases" with "Fitness, yoga, and training". The survey was conducted in 2024, among 2,029 consumers. Looking to gain valuable insights about consumers of health and fitness services worldwide? Check out our

This dataset presents the footprint of the percentage of adults who reported excellent, very good or good health. The data spans the years of 2013-2017 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS). The data is sourced from the Australian Bureau of Statistics (ABS) 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. It also includes data from previous Patient Experience Surveys conducted in 2013-14, 2014-15 and 2015-16. The Patient Experience Survey is conducted annually by the ABS and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patient Experience Survey collects data on persons aged 15 years and over, who are referred to as adults for this data collection. For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Patient experiences in Australia Data Tables. Please note: AURIN has spatially enabled the original data using the Department of Health - PHN Areas. Percentages are calculated based on counts that have been randomly adjusted by the ABS to avoid the release of confidential data.

This dataset presents the footprint of the percentage of patients with costs, the total out-of-pocket cost per patient at the 25th, 50th, 75th and 90th percentile and various statistics for all patients. The data spans the financial year of 2016-2017 and is aggregated to Statistical Area Level 3 (SA3) geographic areas from the 2016 Australian Statistical Geography Standard (ASGS). The data is sourced from the Medicare Benefits Schedule (MBS) claims data, which are administered by the Australian Government Department of Health. The claims data are derived from administrative information on services that qualify for a Medicare benefit under the Health Insurance Act 1973 and for which a claim has been processed by the Department of Human Services. Data are reported for claims processed between 1 July 2016 and 30 June 2017. The data also contains the results from the ABS 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. The Patient Experience Survey is conducted annually by the Australian Bureau of Statistics (ABS) and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patients' spending on Medicare Services data accompanies the Patients' out-of-pocket spending on Medicare services 2016-17 Report. For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Patients' out-of-pocket spending on Medicare services Data Tables.

Estimate of self-assessed health as fair or poor health from the Australian Health Survey, from 2011 to 2013, by SA2. SA2 data for this indicator are derived from Population Health Area (PHA) data. PHAs are comprised of one or more whole SA2s. A full listing of SA2s and what percentage of their corresponding PHA has been allocated to them can be found at the following link: http://publichealth.gov.au/AURIN/phidu_PHA_to_SA2_concordance.xls

Abstract

Economy of Papua New Guinea had been in a state of recession since the mid-1990s. The fiscal situation had been compromised by large deficits. Pertinent questions about how effectively social spending was translating into the actual delivery of services had been raised.

The Public Expenditure and Service Delivery Survey (PESD) was conducted in February-August 2002 to study resources flow in education and health sectors. The PESD was launched by the World Bank as part of the Bank's analytical work on poverty in Papua New Guinea, in close cooperation with the country's government and the Australian Agency for International Development.

The main focus of the project was on expenditure in education. The health facility survey was not intended to be a full service delivery survey in order to keep the field operations and costs within manageable limits. It was added as a rider to the school survey. Health facilities that could be reached within 20 minutes from the sample schools were covered. Against a sample of 214 schools, the survey covered 117 health facilities. A short instrument collected information on how often the facilities were open, the presence of staff, and the availability of key medicines.

The PESD education sector survey covered 214 schools in 19 districts across 8 provinces (out of 20), with two provinces selected in each of the four main regions.

Geographic coverage

Regions: Gulf, National Capital District (NCD), Enga, Eastern Highlands, West Sepik (Sandaun), Morobe, West New Britain and East New Britain.

Analysis unit

• Health facilities

Kind of data

Sample survey data [ssd]

Sampling procedure

Health facilities that could be reached within 20 minutes from the sample schools were covered. Against a sample of 214 schools, 117 health facilities were selected.

Below is the discription of how the schools sample was selected:

1) Following regions were covered: Gulf, National Capital District (NCD), Enga, Eastern Highlands, West Sepik (Sandaun), Morobe, West New Britain, East New Britain. These provinces cover a wide spectrum both in terms of poverty levels and educational development. They range from the relatively rich (NCD and Gulf with headcounts of 19 and 28%) to the poor Sandaun (headcount of over 60%), from the well-educated (NCD and East New Britain with adult literacy rates of 84 and 74%) to poorly-educated (Enga and Eastern Highlands with adult literacy rates of 26 and 38%), from those with high primary enrolment (NCD and ENB) to those with low enrolment (Enga, Gulf and Sandaun), from those with high grade 1-8 retention rates (NCD with 79%) to those with low retention rates (Eastern Highlands and Sandaun with just above 20%).

2) Three districts were randomly selected within provinces with probability proportional to the number of schools in the district. In two of the provinces, Gulf and West New Britain, that only had two districts, both were selected. Ten schools were then selected randomly within each district. In NCD, which does not have districts but is organized by wards/census enumeration areas, 30 schools were randomly selected.

3) The original sample included 220 schools. Many of the schools in the original sample could not be covered for a variety of reasons. In these cases, replacement schools (randomly selected from the same district) were used. A special effort was made to ensure coverage of remote schools. In particular, some sites were revisited later to cover schools that could not be surveyed during the first attempt due to logistical difficulties. The final sample included 214 schools.

4) The PESD schools were further classified by the level of poverty and remoteness. The level of poverty was measured by the estimated poverty rate for the LLG where the school was located, and the remoteness index was based on a composite measure of distance and travel time from the school to a range of facilities. The PESD sample of schools was well distributed across the remoteness and poverty spectrum.

Mode of data collection

Face-to-face [f2f]

This dataset presents the statistics of prevalence for chronic kidney disease (CKD) distributed by sex for the years between 2011-2012. The data is aggregated to 2015 Primary Health Network (PHN) geographic boundaries based on the 2011 Australian Statistical Geography Standard (ASGS). The chronic kidney disease (CKD) datasets were released by the Australian Institute of Health and Welfare (AIHW) to present data on prevalence, treatment (hospitalisations for CKD and dialysis) and deaths. It shows the distribution of the impact of CKD across Australia and visualises rates of CKD and the health and demographic profile for local areas. The data was modelled by the AIHW from the 2011-12 Australian Bureau of Statistics (ABS) Australian Health Survey (AHS): National Health Measures Survey.

South Australian Monitoring and Surveillance System (SAMSS) is a population health survey that monitors trends in health risk factors and chronic disease. Data is collected every month for about 600 adults and children using the CATI (Computer-Assisted Telephone Interviewing) system.

Data in tables published in Target, Trends at a glance [TAG] and Indicator reports will be made available, not the individual person level records in SAMSS.