Out-of-pocket spending on drugs and pharmaceutical products and cost-related prescription non-adherence among Canadians with chronic disease.
Bibliographic record
Abstract
BACKGROUND: Approximately one-third of Canadians' prescription medication costs are paid directly out-of-pocket. This study attempts to determine if out-of-pocket spending greater than 5% of household income on drugs and pharmaceutical products is associated with cost-related prescription non-adherence among people with cardiovascular-related chronic conditions. DATA AND METHODS: The data are from the survey on Barriers to Care for People with Chronic Health Conditions. Three categories of out-of-pocket spending on drugs and pharmaceutical products as a percentage of household income were identified: 0%, more than 0% to less than 5%, and 5% or more. Log-binomial regression was used to investigate associations between category of out-of-pocket spending and cost-related non-adherence. RESULTS: In 2012, about 80% of people aged 40 or older who lived in British Columbia, Alberta, Saskatchewan or Manitoba and had cardiovascular-related chronic conditions reported out-of-pocket spending on drugs and pharmaceutical products; 4.8% reported out-of-pocket spending of at least 5% of their household income. These individuals were significantly older, more often lived in households with incomes less than $30,000, and more often reported multiple morbidities than did people whose out-of-pocket spending on drugs and pharmaceutical products was less than 5% of household income. When the results were adjusted for age and sex, people whose spending amounted to 5% or more of household income were almost three times as likely (prevalence rate ratio = 2.6) to report cost-related prescription non-adherence than were those spending less than 5%. INTERPRETATION: Spending at least 5% of household income on drugs and pharmaceutical products was significantly associated with cost-related prescription non-adherence. Additional data are required to determine if even lower levels of spending put individuals at risk of cost related non-adherence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".