4329.0 - Characteristics of people using mental health services and prescription medication, 2011
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 28/10/2014 First Issue
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EXPLANATORY NOTES
In addition the data excludes:
These exclusions are discussed further in the Data Quality section. LINKAGE RESULTS At the completion of the linkage process:
METHODOLOGY DATA INTEGRATION: OVERVIEW Statistical data integration involves combining information from different administrative and/or statistical sources to provide new datasets for statistical and research purposes (Endnote 5). Data linking is a key part of statistical data integration and involves the technical process of combining records from different source datasets using variables that are shared between the sources. Data linkage is typically performed on records that represent individual persons, rather than aggregates. Two common methods used to link records are deterministic and probabilistic linkage. Deterministic linkage links person-records on exact matches using a unique identifier (such as a social security number or a created unique identifier such as a linkage key). Probabilistic linkage links person-records on close matches based on the relative likelihood that two records refer to the same person, using a number of linking variables (such as date of birth, sex, geographic area). For further information on data integration see Glossary and the National Statistical Service website – Data Integration. DATA INTEGRATION METHOD The Department of Health provided the ABS with de-identified MBS and de-identified PBS data extracts, while the Department of Human Services extracted and provided the associated de-identified demographic data extract on behalf of the Department of Health. This data was de-identified in that it did not include name, address, Medicare Number or Pharmaceutical Benefits number. ABS then transformed this administrative data from transaction-level to person-level. Data from the 2011 Census, and the transformed MBS and PBS data, were brought together using probabilistic linkage. The variables used to link the MBS and PBS data to the Census were Date of Birth, Sex and Mesh Block. The method involved linking without the use of name and address; this information was destroyed at the end of the 2011 Census processing cycle. The process also placed importance on accuracy and uniqueness. Only records that matched exactly on the linkage variables and were unique matches were retained. In this linkage project, a unique match was defined as instances where a record on the MBS or PBS file had only one matching record on the Census, and that same Census record does not match to any other record on the MBS or PBS file. Before records between datasets are compared, the contents of the linking variables of each dataset need to be as consistent as possible to facilitate comparison. This process is known as standardisation. The standardisation procedure for the Mental Health Services-Census Data Integration project included coding imputed and invalid values on the data to a common missing value. These variables included Date of birth, Age, Sex, Mesh Block, Statistical Area Level 1 (SA1) and Postcode. Table 1 lists the variables used to link in each pass. Each record pair required exact matching of all variables used in the pass in order for a link to be created. Table 1 Linking variables used for each pass
REPRESENTATIVENESS The linkage rates that were achieved for the MBS and PBS datasets were in line with expected results, and were relatively consistent across most sub-populations -- the exceptions were Northern Territory, Remote, Very Remote, and younger adults, which had lower linkage rates. LINKAGE ACCURACY False links can occur during the linkage process because, even when a record pair matches on all linking fields, the records may not actually belong to the same individual. While the methodology is designed to ensure that the majority of links are true some false links will be present within the dataset. UNLINKED RECORDS There are three main reasons why records from the MBS and PBS datasets were not linked to a 2011 Census record: 1. Records belonging to the same individual were present in the MBS or PBS dataset and the 2011 Census but these records failed to be linked because they contained missing or inconsistent information in one or more of the datasets. 2. There was no 2011 Census record corresponding to an MBS or PBS record because the person was not counted in the Census. 3. There were more than one Census records that agreed on the same linkage variables – only unique matches were retained. WEIGHTING Some groups of records were more likely to link, or conversely less likely to link, than other groups of records. This resulted in over representation of some groups and under representation of others. Records are more difficult to link when a person has poorly reported, poorly coded, missing or non-applicable values for linking variables. The non-random distribution of links has the potential to cause bias. To compensate for differences in propensity to link, the data were weighted to represent the original MBS or PBS dataset. Weighting is the process of adjusting a sample to infer results for the relevant population. To do this, a 'weight' is allocated to each sample unit - in this case, persons. The weight can be considered an indication of how many people in the relevant population are represented by each person in the sample. For this project, estimates were created by weighting the linked records to represent the original MBS or PBS dataset, using: Age group, Sex, State/Territory, Remoteness Area, SEIFA, broad groups for services and medication. For a relatively small number of records some of these variables were imputed for weighting purposes. DATA QUALITY All data collections are subject to sampling and non-sampling error. Non-sampling error may occur in any data collection. Possible sources of non-sampling error include errors in reporting or recording of information, occasional errors in coding and processing data, and errors introduced by the linkage process (discussed above). A small number of geographies (State and Remoteness Area) were imputed, and a very small number of unusual records were removed prior to linkage. MBS DATA The Department of Human Services collects data on the activity of all persons making claims through the Medicare Benefits Scheme and provides this information to the Department of Health. Information collected includes the type of service provided (MBS item number) and the benefit paid by Medicare for the service. The item numbers and benefits paid by Medicare are based on the Medicare Benefits Schedule (MBS) which is a listing of the Medicare services subsidised by the Australian Government. MBS data includes Medicare-subsidised mental health-related services provided by psychiatrists, general practitioners (GPs), psychologists and other allied health professionals—including mental health nurses, occupational therapists, some social workers, and Aboriginal health workers. These services are defined in the Medicare Benefits Schedule (MBS) (See Appendix A). Medicare data covers services that are provided out-of-hospital (e.g. in doctors' consulting rooms) as well as in-hospital services provided to private patients whether they are treated in a private or public hospital. The figures do not include services provided to public patients in public hospitals or services that qualify for a benefit under the Department of Veterans Affairs National Treatment Account. The States and Territories are the custodians of public hospital data (Endnote 6). For further information (Endnote 7). PBS DATA The Department of Human Services provides data on prescriptions funded through the Pharmaceutical Benefits Scheme (PBS) to the Department of Health. The PBS lists all of the medicines available to be dispensed to patients at a Government-subsidised price. The Government is advised by the Pharmaceutical Benefits Advisory Committee (PBAC) regarding which drugs should be listed on the PBS Scheme. PBS data include subsidised prescription medication from the following groups: Antipsychotics, Anxiolytics, Hypnotics and Sedatives, Antidepressants, Psychostimulants, agents used for ADHD and Nootopics (See Appendix B). The data refer only to prescriptions scripted by registered medical practitioners who are approved to work within the PBS and to paid services processed from claims presented by approved pharmacists who comply with certain conditions. They exclude adjustments made against pharmacists’ claims, any manually paid claims or any benefits paid as a result of retrospective entitlement or refund of patient contributions (Endnote 8). The PBS data exclude non-subsidised medications, such as private and over-the-counter medications. Under co-payment prescriptions (where the patient co-payment covers the total costs of the prescribed medication) data are available from mid-2012; and therefore not available for 2011 (Endnote 8). Data does not include the Repatriation Pharmaceutical Benefits Scheme (RPBS) which is subsidised by the Department of Veterans’ Affairs (Endnote 9). For further information (Endnote 8). CENSUS The 2011 Census measured the number and key characteristics of people who were in Australia on Census night 9 August 2011. For information about the 2011 Census please refer to Census 2011 Reference and Information and Census Data Quality on the ABS website. GEOGRAPHY The mesh block information used in the linkage process may not be aligned between the MBS and PBS files, and the Census, for a range of reasons, including:
Medicare claims data used in this dataset are based on the mesh block of the enrolment address of the patient. As clients may receive services in locations other than where they live, these data do not necessarily reflect the location in which services were received (Endnote 10). The data therefore reflects geographic information about the patient, rather than where they received each service – for example, the data does not show GP services by state, but rather the GP services provided to patients in each state. REMOTE AREAS People living in Remote and Very Remote areas of Australia are underrepresented in the data. This may be for a number of reasons including:
The Census also undercounts the number of people living in some areas of Australia more than others. In 2011, the Northern Territory recorded the highest net undercount rate of all states and territories (6.9%) and showed the largest difference in the net undercount rate between its greater capital city and rest of state region (3.7% and 10.9% respectively) (Endnote 13). ACKNOWLEDGEMENT The ABS acknowledges the continuing support provided by the National Mental Health Commission and the Department of Health for this project. The provision of data by the Department of Health and the Department of Human Services, as well as the funding from the National Mental Health Commission was essential to enable this important work to be undertaken. The enhancement of mental health statistics through data linkage by the ABS would not be possible without their cooperation and support. The ABS also acknowledges the importance of the information provided freely by individuals in the course of the 2011 Census. Census information provided by individuals to the ABS is treated in the strictest confidence as is required by the Census and Statistics Act (1905). MBS and PBS information provided by the Department of Health and the Department of Human Services to the ABS is treated in the strictest confidence as is required by the National Health Act (1953), and the Health Insurance Act (1973). Document Selection These documents will be presented in a new window.
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