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|Predicting early dementia using Medicare claims||2.73 MB|
Administrative data provides a wealth of information that can be used to monitor dementia in Australia. Currently, a diagnosis of dementia can be identified in hospital admitted patient care, mortality, aged care and Pharmaceutical Benefits Scheme (PBS) data. However, these sources tend to be best at identifying people with later stages of dementia, as disease progression leads to more frequent contact with various parts of the health and aged care systems.
Primary and secondary care data provide the best opportunity to identify people living in the community who are in the early stages of dementia. However, the lack of explicit identification of a dementia diagnosis in primary and secondary care data is currently a key data gap for dementia monitoring in Australia. There are, however, several Medicare-subsidised services that are commonly accessed by practitioners and their patients in the course of diagnosing dementia in its earlier stages. These include services such as the practitioner appointments themselves, diagnostic imaging and pathology, and team care arrangements.
This feasibility study aims to test whether, at a given point in time, the presence of dementia can be identified from Medicare Benefits Schedule (MBS) item claims that reflect the steps taken by medical practitioners in the diagnosis of dementia. This analysis was undertaken on the National Integrated Health Services Information Analysis Asset (NIHSI-AA), which links together the MBS, PBS, hospitals and aged care data needed to identify a cohort of people with early dementia. Two techniques were tested for identifying early dementia: a decision tree and logistic regression analysis.