Within the Australian population, arthritis and other musculoskeletal conditions are highly prevalent, associated with significant disability, and generate large costs for the health and welfare systems. It is important to monitor these conditions to describe existing health patterns, populations at risk of illness, current health service use, and future demands on the health and welfare systems.
This report assesses the potential for existing data sources to improve our understanding of arthritis and other musculoskeletal conditions. Although many of the data sources identified were not primarily designed for monitoring these conditions, they do contain relevant data.
A 4-step process is used to assess the utility of different of data sources, including an initial stocktake of data collections, a review of in-scope data collections, an assessment of individual data collections and lastly an overall assessment of data collections collectively. This methodological approach can be used to assess other data sources for different conditions.
This report acknowledges:
- Data are available for:
- risk factors, including some relevant information from longitudinal surveys
- prevalence, with the exception of rarer conditions.
- Data are available but require further development for:
- prevention, treatment and management, particularly to fill substantial gaps in relation to prevention activity and the use and appropriateness of care provided in primary health-care settings
- death and disability, noting additional information is expected in late 2015 from new Australian estimates of burden of disease.
- Data require development for:
- quality of life
- health expenditure.
- Future opportunities for improving data include:
- data linkage to enhance the information that can be gained using existing data
- enhancing the current lack of primary health-care data
- improving consistency and comparability of data from different sources by encouraging development and implementation of information standards
- regular/ongoing collection of data to enable the assessment of change over time.