The capacity of the Commonwealth to respond effectively to current and emerging health workforce needs is significantly enhanced by access to appropriate, reliable and up-to-date health workforce data. The national data collections available are described in Box 9.2.
DoHA has reported some concerns with the current data sharing arrangements between the agencies involved in the production and analysis of health labour force surveys, stemming from a change in the contracting arrangements.
Prior to the introduction of the National Registration and Accreditation Scheme (NRAS), DoHA funded the Australian Institute of Health and Welfare (AIHW) to compile and report on data collected through voluntary surveys of health professionals undertaken in conjunction with state/territory registration processes. Following the introduction of NRAS, HWA assumed responsibility for the funding arrangements with AIHW, with data exchange protocols formalised under a Memorandum of Understanding between HWA, AIHW and AHPRA.
This has created some difficulty for DoHA in gaining early access to new data releases, and in undertaking the informal quality assurance and analysis function it had previously engaged in. These appear to be transitional issues that could be managed with the maintenance of communication and relationships between the Department, HWA and AIHW. Note that these issues were also raised earlier in Chapter 3.
Box 9.2: health workforce data collections
National Health Workforce Data Set (NHWDS)
Mandatory registration data are collected under the NRAS when health practitioners apply for initial registration and annual renewal of their registration. Data collected at initial registration includes demographic information such as age, sex, country of birth; and details of health qualification(s) and registration information such as status and type. The Australian Health Practitioner Regulation Agency (AHPRA) publishes summary registration data quarterly on their internet site as well as in its Annual Report.
When health practitioners renew their registration they are also asked to complete a voluntary Workforce Survey. The questionnaire collects information on the employment characteristics, primary work location and work activity of the practitioner. The response rate for these surveys since being undertaken by AHPRA have been high: 85% for the 2011 Medical workforce survey, 86% for the 2011 nursing and midwifery workforce survey and 73% for the 2011 dental workforce survey.
AHPRA, on behalf of the National Boards, submits the de-identified registration and workforce survey data to AIHW at designated times each year following the annual registration renewal process. The AIHW merges the two datasets into a de-identified national data set then undertakes cleansing and adjustment for non-response in preparation for submission to the NHWDS.
Australian Bureau of Statistics (ABS) - Census of Population and Housing
The ABS Census of Population and Housing (Census) data provides information which can be used to establish the size and distribution of the entire health workforce and the number of Aboriginal and Torres Strait Islander people working in the health sector, including the occupations in which they are specifically employed.
The Census is conducted by the ABS every five years in August. The Census data is available in a range of formats from free basic tables accessible online to charged products such as customised flat files and large Unit Record Files requiring organisational micro-data access. Data collected on occupation are coded using the Australian and New Zealand Standard Classification of Occupations (ANZSCO). However to get a more precise estimate of health workforce size, Census data needs to be interrogated down to the six digit ANZSCO code level. This data is not available on line and must be purchased from the ABS. Also, there may need to be consideration of exactly which occupations are categorised as health occupations, rather than for example welfare or community services occupations. This analysis was undertaken by AIHW in 2009 (and for previous Censuses) and published in the Health and Community Services Labour Force, 2006 report. Initial discussions with HWA indicate that they will be undertaking a similar project on 2011 Census data in the future.
Geographical distribution of the health workforce can be analysed in terms of the person’s place of usual residence, place of renumeration and place of work. Geographical information is available based on ABS geographies (ASGS – Mesh block, SA1, SA2, SA3, SA4) and some non-ABS geographies (i.e. LGA, destination zone).
Additionally, information on health sector qualifications is available and may highlight where people with health sector qualifications are not employed, or employed outside of the health sector.
Medicare Benefits Scheme (MBS) Claims data set
MBS data is used to calculate GP workforce statistics by counting providers who rendered services under Medicare. These figures are used in publications such as the Report on Government Services (RoGS) and are published on the DoHA internet site.
The MBS is managed and funded by DoHA and administered by the Department of Human Services (DHS). Through the process of administering the scheme, DHS captures information on Medicare benefits payable for services (items) listed in the MBS provided by practitioners with a Medicare provider number. This data is transmitted to DoHA.
Visa data - Department of Immigration and Citizenship (DIAC)
Visa data is used for information about the overseas supply of health practitioners.
DIAC collects administrative data about the number of permanent and temporary visa grants and visa holders in Australia. There are a number of temporary visa options available for health practitioners.
DIAC visa information is available in the form of statistical publications and temporary entrance statistics tables (annual and quarterly stock data). The Department receives a regular medical workforce report but can also request specific information on an ad hoc basis if necessary.
Medical Training Review Panel Report
Medical training information is sourced from the annual Medical Training Review Panel (MTRP) Report. It includes information on all trainees in undergraduate, postgraduate and vocational training programs compiled from various data sources including:
- Undergraduate medical students data from the Student Statistics Collection (annual) and the Medical Schools Outcomes Database (MSOD) (longitudinal) supplied by Medical Deans Australia and New Zealand Inc (MDANZ).
- First (internship) and second years of prevocational training data supplied by state and territory health departments.
- Vocational training data (doctors specialist training) provided by each of the specialist medical colleges.
- General practice training (trainee) data provided by General Practice Education and Training Limited (GPET), the Royal Australian College of General Practitioners (RACGP) and the Australian College of Rural and Remote Medicine (ACRRM).
- Assessment and accreditation data provided by the Australian Medical Council (AMC).
Higher Education Statistics Collections
Nursing and midwifery, dental and clinical psychology training data can be sourced from the Higher Education Statistics Collection.
The Higher Education Group of DIICCSRTE, with the cooperation of the ABS, is responsible for the collection and dissemination of statistics relating to the provision of higher education in all Australian universities.
DIICCSRTE collects data from higher education providers to determine support for providers that are eligible for Australian government grants. This data is reported by all higher education providers that have been approved under the Higher Education Support Act 2003.
DIICCSRTE, through its Statistics Unit, disseminates data from the collections through statistical publications, datasets, tabulations, extracts and analyses prepared for clients.
Health Workforce 2025
HWA has provided long-term projections for Australia’s national doctor, nurse and midwife workforce to the year 2025 in the report Health Workforce 2025 – Doctors, Nurses and Midwives. This project included supply and demand data modelling to examine future workforce needs under a range of planning scenarios including immigration levels, productivity, workforce retention and training.
Volumes 1 and 2 of the report broadly deal with doctor and nurse/midwife numbers while Volume 3 examines 27 individual medical specialties. Results (supply, demand, excess/shortfall) are presented under different scenarios by specialty/area of practice and geography (state/territory and Remoteness Area).
In the next phase of HW2025, seven professions have been identified for inclusion in HW2025 – Allied and Other Health Professions (dietitians, psychologists, nursing support and personal care workers, physiotherapists, podiatrists, pharmacists, optometrists). HWA will be undertaking a similar project for Australia’s oral health workforce.
The modelling and projections will be updated and refined on an ongoing basis as advancements occur. This includes inputs as better data and information about assumptions become available as well as innovative analysis techniques to improve modelling and outputs.
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Other issues relating to the adequacy of data collection and analysis were raised during the course of this review. As discussed in Chapter 8, allied health professional groups expressed a sense of grievance that the need for coherent data for their sector had not yet been addressed, particularly with respect to the professions not covered by NRAS. Allied health stakeholders were keen to assert the urgency of remedying the current gap in the interests of coherent planning. The next phase of HWA’s work for HW2025 may go some way towards addressing this. Data quality issues with respect to the Aboriginal and Torres Strait Islander health workforce have also been identified, as noted in Chapter 5.
The analysis of programs undertaken as part of this review has highlighted the difficulty in assessing the impact of individual initiatives towards addressing particular health workforce problems, for example, improving access in rural areas. Improvement in the collection of program-level data, along with better linkages between program-level data and broader health workforce data (for example, MBS billing data or registration data), could provide a more robust evidence base for establishing the success or otherwise of particular programs against the department’s health workforce priorities.
This review has also revealed some challenges in the sharing of data between organisations, which could be impeding some program outcomes. It has been suggested that overly prescriptive interpretations of the Privacy Act 1988 have been used by some organisations to avoid sharing even de-identified participation data that could be of great benefit to inform policy development and program delivery. Improving the understanding of privacy issues could assist the various funded groups to be more collaborative and develop better linkages within programs. Privacy requirements need to be consistently met during program delivery, but options for obtaining informed consent for the release of participant data need to be explored where possible to help analyse the success of what are complex and inter-connected programs and initiatives.
While national health workforce planning has been a focus of cross-jurisdictional attention since 1995 through a number of advisory bodies reporting to the Australian Health Ministers’ Conference (now the Standing Council on Health), the development of HW2025 as an ongoing national health workforce planning tool is a major step forward in establishing the evidence base for making policy and program-level decisions regarding the supply and distribution of the health workforce.
The past history of health workforce planning is littered with examples of expensive errors based on inadequate data or fallacious assumptions. For this reason most stakeholders have welcomed the work of the HWA and would urge continued investment in the data and high level policy aspect of its work. Clearly, however, the statistical and analytical basis of these predictive models will need to continue to be refined if major policy shifts and resource investment decisions are to be based upon them.