Financial toxicity experienced by rural Australian families with chronic kidney disease
Bibliographic record
Abstract
AIM: Chronic kidney disease (CKD) and its treatment places a financial burden on healthcare systems and households worldwide, yet little is known of its financial impact, on those who reside in rural settings. We aimed to quantify the financial impacts and out-of-pocket expenditure experienced by adult rural patients with CKD in Australia. METHODS: A web based structured survey was completed between November 2020 and January 2021. English speaking participants over 18 years of age, diagnosed with CKD stages 3-5, those receiving dialysis or with a kidney transplant, who lived in a rural location in Australia. RESULTS: In total 77 (69% completion rate) participated. The mean out of pocket expenses were 5056 AUD annually (excluding private health insurance costs), 78% of households experienced financial hardship with 54% classified as experiencing financial catastrophe (out-of-pocket expenditure greater than 10% of household income). Mean distances to access health services for all rural and remote classifications was greater than 50 kilometres for specialist nephrology services and greater than 300 kilometres for transplanting centres. Relocation for a period greater than 3 months to access care was experienced by 24% of participants. CONCLUSION: Rural households experience considerable financial hardship due to out-of-pocket costs in accessing treatment for CKD and other health-related care, raising concerns about equity in Australia, a high-income country with universal healthcare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".