The health care and societal costs of inherited retinal diseases in Australia: a microsimulation modelling study
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To estimate the health care and societal costs of inherited retinal diseases (IRDs) in Australia. DESIGN, SETTING, PARTICIPANTS: Microsimulation modelling study based on primary data - collected in interviews of people with IRDs who had ophthalmic or genetic consultations at the Children's Hospital at Westmead or the Save Sight Institute (both Sydney) during 1 January 2019 - 31 December 2020, and of their carers and spouses - and linked Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Schedule (PBS) data. MAIN OUTCOME MEASURES: Annual and lifetime costs for people with IRDs and for their carers and spouses, grouped by payer (Australian government, state governments, individuals, private health insurance) and type (health care costs; societal costs: social support, National Disability Insurance Scheme (NDIS), income and taxation, costs associated with caring for family members with IRDs); estimated annual national cost of IRDs. RESULTS: Ninety-four people (74 adults, 20 people under 18 years; 55 girls and women [59%]) and 30 carers completed study surveys (participation rate: adults, 66%; children, 66%; carers, 63%). Total estimated lifetime cost was $5.2 million per person with an IRD, of which 87% were societal and 13% health care costs. The three highest cost items were lost income for people with IRDs ($1.4 million), lost income for their carers and spouses ($1.1 million), and social spending by the Australian government (excluding NDIS expenses: $1.0 million). Annual costs were twice as high for people who were legally blind as for those with less impaired vision ($83 910 v $41 357 per person). The estimated total annual cost of IRDs in Australia was $781 million to $1.56 billion. CONCLUSION: As the societal costs associated with IRDs are much larger than the health care costs, both contributors should be considered when assessing the cost-effectiveness of interventions for people with IRDs. The increasing loss of income across life reflects the impact of IRDs on employment and career opportunities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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