4343.0 - Survey of Health Care, Australia, 2016 Quality Declaration 
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 20/09/2017  First Issue
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INTRODUCTION

1 This summary publication contains results from the Survey of Health Care (SHC) conducted throughout Australia from April 2016 to June 2016. The SHC was funded by the AIHW, and conducted by the ABS and the AIHW, as part of the broader Coordination of Health Care Study.

2 The Coordination of Health Care Study is a broad collection consisting of two components. The first is the SHC and the second involves integrating data for consenting participants with specific data items from the Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS) data, Repatriation Pharmaceutical Benefits Scheme (RPBS), together with hospitalisation data including visits to emergency departments and admissions to hospital.

SCOPE AND COVERAGE

3 The scope of the SHC was people aged 45 years and over who had at least one GP visit in the 12 months between November 2014 and November 2015. A GP visit means having a claim against any one of a defined set of MBS item numbers. These people were chosen because they are more likely to have complex and chronic conditions, and have experiences with multiple providers including hospitals, specialists, and allied health professionals. See Glossary for MBS item numbers.

4 The scope of SHC was people in all States and Territories. The scope included:

  • people who were registered to receive Medicare benefits at any time prior to November 2015
  • people who live in private and non-private dwellings
  • visitors and diplomats from countries where there is a reciprocal Medicare arrangement
  • people who received services through Aboriginal Medical Services
  • people who were deceased after the sample was selected.

5 The scope excluded:
  • people who were not registered with Medicare
  • people who had only had GP transactions which were not billed through Medicare, (for example through doctors who draw a salary and do not bill to Medicare)
  • people who were in active military service and obtained all their medical services through the military.

6 The sample frame for the SHC was the Medicare Enrolment Database (MEDB). The sample was selected from this frame by the Department of Human Services (DHS) in accordance with a stratification and allocation specified by the ABS.

7 As people were in scope of the SHC if they saw a GP at least once in the 12 months prior to selection (23 November 2015), there may have been people who saw a GP at least once in the 12 months prior to enumeration (April 2016 to June 2016) who were not in scope as they did not visit a GP between November 2014 and November 2015. Similarly, there may have been people who visited a GP in the 12 months prior to selection but did not visit a GP in the 12 months prior to enumeration who were in scope.

SAMPLE DESIGN

8 The SHC sample was designed to support estimates at the Primary Health Network (PHN) area level. A stratified random sample was used where the strata were based on the following variables:
  • age groups (five-year groups from 45 to 79 years of age, then 80 years and over)
  • sex (male and female)
  • PHN area (31 PHNs plus an extra category for unknown PHN)
  • socio-economic category (people were divided into three socio-economic strata ‘low’, ‘medium’ and ‘high’ based on their postcode’s score on the Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD), ‘low’ and ‘high’ being the bottom and top two deciles respectively)
  • number of GP visits in the 12 months prior to selection (number of GP visits was split into users with 1 to 11 visits and users with 12 visits or more).

9 People on the frame were assigned a PHN based on the postcode of their postal address as recorded on the MEDB. A correspondence between postal areas and PHNs was used to do this. As not every postcode is included in the ABS postal area classification, there were around 100,000 people who could not be allocated a PHN. At the sample design stage, these people were allocated to an unknown PHN category.

10 There were 8.8 million people in scope on the MEDB. A total sample of around 124,000 people was selected by sorting within stratum by number of GP visits and then applying a skip using a random start.

11 Also incorporated into the overall sample design was a requirement to oversample people who saw a GP more than 12 times such that the resulting sample consisted of approximately half people who saw a GP 12 or more times and half who saw a GP 1-11 times.

SURVEY RESPONSE

12 There were around 124,000 people selected for this survey. Of these, there were 35,495 responses, giving a response rate of 28.6%. In this survey it is not possible to distinguish between non-response and sample loss. For example, a person may have been selected to participate, but will not have received any survey materials due to an out-of-date address on the MEDB.

13 The following table contains response rates by the State or Territory that the person was selected in. Persons selected in the unknown PHN category have unknown State for selection.

Table 1.1 RESPONSE RATES

NSW
Vic.
Qld
SA
WA
Tas.
NT
ACT
Unknown
Aust.

Approached sample
38,248
22,892
27,415
7,825
11,161
3,940
3,411
3,843
5,337
124,072
Responding sample size
10,738
6,983
7,755
2,632
3,351
1,384
651
1,305
696
35,495
Response rate (%)
28.1
30.5
28.3
33.6
30.0
35.1
19.1
34.0
13.0
28.6


14 In the survey output, respondents are placed into the geographic regions (e.g. State, PHN) and SEIFA decile that correspond to their reported home postcode.

DATA COLLECTION

15 Data was collected by mail. In order to facilitate maximum response, a four stage mail-out approach was used. The four stages consisted of:
  1. a DHS cover letter, a Primary Approach Letter and a translated paper introducing respondents to the study in 10 languages;
  2. a DHS cover letter, the SHC, a Consent Form for Release of Hospital Data, a Consent Form for Release of Department of Human Services Data, a translation paper, a brochure and a reply paid envelope;
  3. a DHS cover letter, a reminder/thank you postcard and a translation paper. This wave was only despatched to people who had not returned a survey form, or who had not contacted the ABS to refuse participating in the study as of the 26th of April 2016; and
  4. a replication of stage 2, despatched only to those who had not returned a survey form nor made contact with the ABS as of the 26th of April 2016.

16 In each phase of the mail out, a cover letter from the DHS was included, explaining that the DHS had not provided the ABS with any personal details of the selected person.

17 People with low English proficiency, or who had a disability which prevented them from completing the survey on their own, were able to complete the survey over the phone. People with low English proficiency were offered the option of an interpreter from the Translation and Interpreting Service (TIS National) who could facilitate a phone call with the ABS and translate as an ABS officer provided information or collected the participant's data over the phone.

WEIGHTING, BENCHMARKS AND ESTIMATION

Weighting

18 Weighting is the process of adjusting results from a sample survey to infer results for the total 'in scope' population. To do this, a 'weight' is allocated to each enumerated person. The weight is a value which indicates the number of people in the population represented by the sample person.

19 The first step in calculating weights for each unit is to assign an initial weight, which is the inverse of the probability of being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 600, then the person would have an initial weight of 600 (that is, they represent 600 people).

20 The probability of being selected was based on the stratification variables: number of GP visits (1-11 or 12 or more), PHN, ‘low’, ‘medium’ or ‘high’ IRSAD, sex and age group (five-year groups from 45 to 79 years of age, then 80 years and over). Persons in the number of GP visits (12 or more) had a higher chance of selection than those with 1-11 GP visits.

21 In order to determine the stratum of selection, self-reported values were used for PHN, SEIFA, sex and age as the ABS does not have access to any personal information from the frame. While self-reported frequency of GP use was also available, analysis of data for persons who consented to have their MBS data released for the study indicated that this was not a reliable indicator of the frequency of GP use (derived from MBS claims) as was used for sample selection. For this reason, the, the initial weight was calculated in the following ways:
  1. For those who consented to have their MBS data released for the study (around 51% of respondents), the initial weight was calculated using the MBS claims information for the period November 2014 to November 2015 to calculate their frequency of GP use at the time of selection.
  2. For those who did not give their consent, and who provided a self-reported frequency of GP use (around 47% of respondents), a logistic adjusted weight was calculated to determine their frequency of GP use. This logistic weight was calculated by modelling the relationship between MBS claims at the time of the survey and self-reported frequency of GP use within strata for those respondents for whom both pieces of information was available and applying this relationship to those for whom only self-reported was available.
  3. For those who did not give their consent and did not provide a self-reported frequency of GP use (around 2% of respondents), an initial weight was calculated based on the average weight across both frequency categories according to the overall probability of being in that category by stratum.

22 For weighting purposes, the PHN and SEIFA allocated to each record were based on the postcode of the respondent’s reported address, which in some cases differed from the postcode, PHN and SEIFA used in selection.

Benchmarks

23 Weights calibrated against population benchmarks ensure that the survey estimates conform to the distribution of the MEDB population rather than the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories of people/households which may occur due to either the random nature of sampling or non-response.

24 The survey was benchmarked to counts of the in-scope population at November 2015 from the MEDB for PHN (based on postal address postcode) by sex by 10 year age groups to age 75 and over.

Estimation

25 Survey estimates of counts of people are obtained by summing the weights of people with the characteristic of interest.

Confidentiality

26 The Census and Statistics Act, 1905 provides the authority for the ABS to collect statistical information, and requires that statistical output shall not be published or disseminated in a manner that is likely to enable the identification of a particular person or organisation. The requirement means that the ABS must take care and make assurances that any statistical information about individual respondents cannot be derived from published data.

27 Perturbation is used in this publication to minimise the risk of identifying individuals in aggregate statistics. 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.

RELIABILITY OF ESTIMATES

28 All sample surveys are subject to error which can be broadly categorised as either:
  • sampling error
  • non-sampling error.

29 Sampling error is the difference between the published estimate, derived from a sample of people, and the value that would have been produced if all people in scope of the survey had been included. For more information refer to the Technical Note.

30 In this publication, estimates with an RSE of 25% to 50% are preceded by an asterisk (e.g. *3.4) to indicate that the estimate has a high level of sampling error relative to the size of the estimate, and should be used with caution. Estimates with an RSE over 50% are indicated by a double asterisk (e.g. **0.6) and are generally considered too unreliable for most purposes.

31 Margins of Error are provided for proportions to assist users in assessing the reliability of these data. The proportion combined with the MoE defines a range which is expected to include the true population value with a given level of confidence. This is known as the confidence interval. This range should be considered by users to inform decisions based on the proportion. Proportions with an MoE of greater than 10 percentage points are preceded by a hash (e.g. #40.1) to indicate the range in which the true population value is expected is relatively wide.

32
Non-sampling error may occur in any collection, whether it is based on a sample or a full count of the population such as a census. Sources of non-sampling error include: non-response; errors in reporting by respondents or recording of answers by interviewers; and errors in coding and processing data. Every effort was made to reduce the non-sampling error by: careful design and testing of the questionnaire; follow-up of respondents; and extensive editing and quality control procedures at all stages of data processing.

33 Non-response bias occurs where non-respondents may have different characteristics from those who did respond. While the collection is subject to non-response bias, it is not possible to reliably quantify this. The magnitude of any bias depends on the rate of non-response and the extent of the differences in characteristics between those people who responded to the survey and those who did not. See Table 1.2 below for a comparison with other ABS collections.

34 This collection was undertaken in a different manner from other ABS household surveys as it was a voluntary, mail-based collection with follow-up by mail. The collection achieved a response rate of 29%.

DATA QUALITY

Comparability with other ABS surveys

35 As this is the first time the SHC has been collected, there is no time series data available.

36 Similar concepts to those in the SHC are found in other ABS surveys, for example the Patient Experience in Australia (cat. no. 4839.0) and the National Health Survey (cat. no. 4364.0.55.001). However, comparison with other ABS surveys should be undertaken with caution. There are several reasons why data from the SHC may not be comparable with other ABS collections:
  • the scope (SHC includes persons who live in non-private dwellings such as hospitals and nursing homes, persons in areas classified as Very Remote, and those in discrete Aboriginal and Torres Strait Islander communities),
  • reference period,
  • question wording,
  • voluntary nature of the collection, and
  • the mode of enumeration.

37 Given the response rate, an investigation was carried out in order to try to understand whether the sample is representative of the in-scope population. While there are some differences between the sample distribution from the Survey of Health Care and other surveys by age, sex, SEIFA and PHN, these have been taken into account by the weighting process. The table below gives a comparison of proportions for a range of other variables from SHC, Patient Experience 2015-16 (PEx) and the National Health Survey 2014-15 (NHS) for the same scope (i.e. over 45 years and at least one GP visit in the previous 12 months). For ‘level of education’ and whether the person ‘had private health insurance’, the proportions were similar across the different sources. For some health related variables, the SHC generally had a higher proportion of people with poorer health. No adjustment to the weighting has been made for this potential bias.

Table 1.2 COMPARISON BETWEEN SHC, PEX AND NHS, PERSONS AGED 45 YEARS AND OVER WHO HAD AT LEAST ONE GP VISIT IN THE PREVIOUS 12 MONTHS(a)

Survey of Health Care,
2016
Patient Experience,
2015-16
National Health Survey,
2014-15

% Percent

Proportion who reported having a long-term health condition(b)
75.1
72.6
..
Proportion who have excellent or very good self-assessed health status
46.8
48.4
47.0
Proportion who have private health insurance
64.8
61.2
60.9
Proportion who have bachelor degree or above
23.7
21.4
21.8
Proportion who have visited an emergency department in the 12 months prior to survey enumeration
18.3
15.1
12.5
Proportion who have been admitted to hospital in the 12 months prior to survey enumeration
21.8
16.9
16.9
Proportion who report 12 or more visits to a GP in the 12 months prior to survey enumeration
15.0
14.0
15.7
Proportion who saw a specialist in the 12 months prior to survey enumeration
54.6
49.6
51.1
Proportion who speak a language other than English at home(c)
9.1
..
10.7
Proportion with two or more persons in their household
80.6
80.2
79.6


Cells in this table have been randomly adjusted to avoid the release of confidential data.
(a) There are differences in the scope of the SHC and the PEx and NHS collections which must be considered when interpreting comparisons in this table. In particular, the SHC includes persons who live in non-private dwellings such as hospitals and nursing homes which are excluded from PEx and NHS. In addition, the NHS excludes persons in areas classified as Very Remote, and both PEx and NHS exclude those in discrete Aboriginal and Torres Strait Islander communities.
NHS and PEx data in this table are restricted to persons aged 45 years and over and who reported having at least one GP visit in the 12 months. SHC data are restricted to persons aged 45 years and over and who reported having at least one GP visit in the 12 months prior to being selected.
More detailed information about the methodology for these two collections can be found in the NHS Explanatory Notes (cat. no. 4364.0.55.001) and PEx Explanatory Notes (cat. no. 4839.0).
(b) There were differences in the methods used to collect long term health conditions between the collections. Both PEx and SHC used a tick box question, PEx with eight and SHC with 14 options. The NHS uses a much more extensive set of questions and is not comparable.
(c) Language other than English spoken at home is not collected in PEx.

Interpretation of results

38 There were a number of issues unique to this collection which may affect the interpretation of the results. These include:
  • This survey was a self-administered paper questionnaire, while other ABS household surveys use interviewer administered computer assisted face to face or telephone interviews. While every effort was made to ensure the questions would be universally understood and sequencing was straightforward, respondents did not have the benefit of interviewers to clarify key terms or the systems to ensure the respondent was correctly sequenced through the form.
  • Due to the age of respondents and possible health limitations, the survey may have been completed on behalf of the respondent by a family member or another person.
  • Questions used in this collection sometimes differed from ABS standard module questions and therefore the resulting data is not necessarily comparable with other ABS household surveys.

Editing of survey data

39 With the mode of delivery being a paper form survey, there was some input editing required. Below are some examples.
  • In some cases respondents incorrectly sequenced themselves past applicable questions or answered questions not applicable to them. Universal edits have been applied to the data to correct these sequencing issues.
  • For questions with free text boxes, in some cases, depending on the clarity of the text, some answers did not scan correctly. For example, the number 5 could scan as the letter S, or the number 9 could scan as the number 4. This required manually reviewing forms where this was known to be an issue in order to correct it.
  • Some respondents answered in such a way that one of their responses contradicted another. Edits were applied to reduce contradictory responses.
  • Most data items include a 'Not stated' category. This is to capture scenarios where the respondent was in the applicable population for that data item, but did not answer the question and there was not enough information to impute their answer to that question. The data items 'Whether has a usual GP' and 'Whether has a usual GP or usual place of care' do not have 'Not stated' categories. If data for these items was missing it was imputed based on answers to other relevant questions.

CLASSIFICATIONS

40 Geographic classifications were applied to the survey data based on the respondent’s reported home postcode, using correspondences between the geography of interest and ABS Postal Area geography.

41 Standard ABS Geographies were classified according to the Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2011 (cat. no. 1270.0.55.001).

42 Remoteness areas are classified according to the Australian Statistical Geography Standard (ASGS): Volume 5 - Remoteness Structure, July 2011 (cat. no. 1270.0.055.005).

43 Primary Health Networks (PHNs) are a classification developed by the Department of Health, see Primary Health Networks in the Glossary. The correspondence between PHN and ABS Postal Area geography was used to relate a person’s postcode as listed on the MEDB to a PHN.

44 Where a postcode crossed a PHN boundary the entire postcode was allocated to the PHN with largest proportion of people living in it. There was a slight exception where a postcode crossed a state boundary; in this case individuals were manually coded to the state they reported as their address.

Socio-economic Indexes for Areas (SEIFA)

45
The survey uses the 2011 Socio-economic Indexes for Areas (SEIFA).

46 SEIFA is a suite of four summary measures that have been created from 2011 Census information. Each index summarises a different aspect of the socio-economic conditions of people living in an area. The indexes provide more general measures of socio-economic status than is given by measures such as income or unemployment alone.

47
For each index, every geographic area in Australia is given a SEIFA number which shows how disadvantaged that area is compared with other areas in Australia.

48
The Survey of Health Care publication uses the Index of Relative Socio-Economic Advantage and Disadvantage, derived from Census variables related to advantage and disadvantage such as high and low household income, lower educational attainment, unemployment, jobs in relatively skilled or unskilled occupations and dwellings without motor vehicles.

49
SEIFA uses a broad definition of relative socio-economic disadvantage in terms of people's access to material and social resources, and their ability to participate in society. While SEIFA represents an average of all people living in an area, it does not represent the individual situation of each person. Larger areas are more likely to have greater diversity of people and households.

50
For more detail, see the following:
PRODUCTS AND SERVICES

Data Cubes

51 Data Cubes containing all tables in Excel spreadsheet format can be found on the ABS website (from the Downloads tab). The spreadsheets present tables of estimates and proportions, and their corresponding relative standard errors (RSEs) and margin of error (MoE).

Customised data requests

52 Special tabulations of the data are available on request. Subject to confidentiality and sampling variability constraints, tabulations can be produced from the survey incorporating data items, populations and geographic areas (including state and territory level data), tailored to individual requirements. These are provided in electronic form. A list of data items from the 2016 Survey of Health Care is available from the Downloads tab.

53 For further information about these and related statistics, contact the National Information and Referral Service on 1300 135 070, or email client.services@abs.gov.au. The ABS Privacy Policy outlines how the ABS will handle any personal information that you provide to us.

ACKNOWLEDGEMENTS

54 ABS surveys draw extensively on information provided by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated and without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.

55 The survey and study were funded by the AIHW, and conducted by the ABS. This publication was jointly prepared and released by the ABS and the AIHW.

56 The ABS and AIHW also acknowledge and thank the DHS for its assistance in the sample selection and postage process of the study.

57 The SHC used variations of questions sourced from other national and international non-ABS surveys. The ABS and AIHW would like to acknowledge the following organisations:
  • Harvard Medical School, Boston
  • Department of Health & Human Services, Victoria
  • The Commonwealth Fund, New York
  • Statistics Canada, Ottawa

58 Specific questions in the SHC that were based on questions from these source organisations are listed in the table below:

Table 1.3 SOURCE ORGANISATIONS AND SOURCE QUESTIONS USED IN SURVEY OF HEALTH CARE SOURCE ORGANISATION

Source QuestionSurvey of Health Care question

Harvard Medical School Public Health Survey In the last 12 months, did your usual GP or others in your usual place of care ask you about things in your work or life that affect your health?
Yes, always
Yes, usually
Yes, sometimes
No, never
In the last 12 months, did your usual GP or others in your usual place of care ask you about things in your work or life that affect your health?
Yes, always
Yes, usually
Yes, sometimes
No, never

Victorian Patient Satisfaction MonitorWere arrangements made by the hospital for any services you needed when you left hospital?
Yes, definitely
Yes, to some extent
No
I didn't need any services
Were arrangements made by the hospital for any services you needed when you left hospital?
Yes
No
I didn't need any services

The Commonwealth Fund After the last time you went to a specialist doctor, did your usual GP or others in your usual place of care seem informed about your specialist care?
Yes
No
Don't know
GP or others in my usual place of care didn’t know until I told them
I didn’t go to my usual GP or go to my usual place of care after my specialist doctor visit
I don’t have a usual GP or usual place of care
After the last time you went to a specialist doctor, did your usual GP or others in your usual place of care seem informed about your specialist care?
Yes
No
Don't know
GP or others in my usual place of care didn’t know until I told them
I didn’t go to my usual GP or go to my usual place of care after my specialist doctor visit
I don’t have a usual GP or usual place of care

Statistics CanadaHow often did your GP explain your test results in a way that you could understand?
Always
Usually
Sometimes
Never
I have not had a follow-up appointment yet
I was never told the results of the tests
In the last 12 months, how often did your usual GP or others in your usual place of care explain your test results (such as blood tests, x-rays or scans) in a way that you could understand?
Always
Usually
Sometimes
Never
I did not have any tests