Can't escape it: the out‐of‐pocket cost of health care in Australia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To analyse the annual out-of-pocket (OOP) expenditure on health care as directly reported by Australian households grouped into older households (those with a reference person aged ≥ 65 years) and younger households (those with a reference person aged < 65 years). DESIGN: Descriptive analysis of statutory data collected by the Australian Bureau of Statistics. SETTING AND PARTICIPANTS: Probability sample of 9774 households across all states and territories. MAIN OUTCOME MEASURES: OOP expenditure on health care. RESULTS: The mean annual OOP expenditure on health care among the older households was estimated as $3585 ± $686 (9.4% of the total expenditure on all goods and services), and among the younger households, it was $3377 ± $83 (4.7% of the total expenditure on all goods and services). Cost of medicines (mainly non-prescription drugs and to a lesser extent the copayments for Pharmaceutical Benefits Scheme scripts) was the biggest item of expenditure for the older households, and the cost of private health insurance (PHI) was the most expensive item for the younger households. Overall, the OOP expenditure, as reported by the Australian households, was $28.7 ± $1.3 billion compared with $21.2 billion as reported by the Australian Institute of Health and Welfare. Unlike our estimate, the Institute's figure was based on statutory data collections and did not include the cost of PHI premiums. CONCLUSIONS: OOP expenses account for almost a quarter (22%) of the total health care costs in Australia. The mean annual OOP expenditure was slightly higher for the older households compared with the younger households, despite the fact that the older households had significantly lower income and had greater access to health care cards, which were used to defray additional health care costs associated with age.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it