Variation in pharmacy prescription refill adherence measures by type of oral antihyperglycaemic drug therapy in seniors in Nova Scotia, Canada
Bibliographic record
Abstract
OBJECTIVE: To examine the association between pharmacy prescription refill adherence by type of oral antihyperglycaemic medications used in seniors in Nova Scotia, Canada. RESEARCH DESIGN AND METHODS: Pharmacy and health care utilization data from April 1993 to March 1996 for Nova Scotia Seniors' Pharmacare beneficiaries treated with 1st and 2nd generation sulphonylureas and biguanides was analysed. Refill adherence was quantified by two proportions: number of days beneficiaries had a medication surplus compared with the total period of observation and gaps in treatment compared with the total period of observation. Analysis examined association of type of oral antihyperglycaemic agent and dosing on refill adherence, after adjustment for age, gender and hospital use. RESULTS: A total of 3358 beneficiaries met the study criteria. The mean refill adherence rate [continuous multiple-interval measure of medication availability (CMA)] was 86 +/- 0.4% SE and continuous measure of medication gaps (CMG) was 16 +/- 0.4% SE. Use of biguanides was associated with lower odds of having a medication surplus. The use of 2nd generation sulphonylureas and biguanides, and use of agents with a dosage frequency of more than one dose per day was associated with medication gaps. CONCLUSIONS: Many beneficiaries taking antihyperglycaemic agents adhered well to prescribed therapy. The proportion of days not covered by medications averaged 16%. Beneficiaries taking medications once a day were more likely to have good refill adherence. Further work is needed to compare prescription refill adherence rates with other adherence measures and clinical outcomes. These methods are useful for establishing baseline adherence, monitoring the success of programmes designed to improve adherence, and determining cost-effectiveness of drug regimens.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".