The financial burden of accessing care for people with scleroderma in Canada: a patient-oriented, cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Patients with scleroderma require a lifetime of treatment and frequent contacts with rheumatologists and other health care professionals. Although publicly funded health care systems in Canada cover many costs, patients may still face a substantial financial burden in accessing care. The purpose of this study was to quantify out-of-pocket costs borne by people with scleroderma in Canada and compare this burden for those living in large communities and smaller communities. METHODS: We analyzed responses to a Web-based survey of people living in Canada with scleroderma. Respondents reported annual out-of-pocket medical, travel and accommodation and other nonmedical costs (2019 Canadian dollars). We used descriptive statistics to describe travel distance and out-of-pocket costs. We used a 2-part model to estimate the impact on out-of-pocket costs of living in a large urban centre (≥ 100 000 population), compared with smaller urban centres or rural areas (< 100 000 population). We generated combined mean estimates from the 2-part models using predictive margins. RESULTS: The survey included 120 people in Canada with scleroderma. The mean, annual, total out-of-pocket costs were $3357 (standard deviation $5580). Respondents living in smaller urban centres and rural areas reported higher mean total costs ($4148, 95% confidence interval [CI] $3618-$4680) and travel or accommodation costs ($1084, 95% CI $804-$1364) than those in larger urban centres (total costs $2678, 95% CI $2252-$3104; travel or accommodation costs $332, 95% CI $207-$458). INTERPRETATION: Many patients with scleroderma incur considerable out-of-pocket costs, and this burden is exacerbated for those living in smaller urban centres and rural areas. Health care systems and providers should consider ways to alleviate this burden and support equitable access to care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".