Near equality in quality for medication utilization among older adults with diabetes with universal medication insurance in <scp>O</scp>ntario, <scp>C</scp>anada
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: To determine whether demographic, community or health status disparities in cardioprotective medication utilization by diabetes patients exist under a universal drug insurance programme, and whether they narrow or widen during periods of increasing drug utilization. METHODS: We examined all prescriptions filled by all people with diabetes aged ≥65 years in Ontario, Canada in annual cohorts from 1996 (n = 175 345) to 2010 (n = 504 093). We ascertained whether any disparities in use of three classes of cardioprotective medication (statins, all antihypertensives and renin-angiotensin-aldosterone system inhibitors) existed, and whether disparities changed over time. RESULTS: Utilization of all three cardioprotective medication classes increased substantially over time, particularly statins (rate ratio per year: 1.13, 95% confidence interval 1.11-1.15). We found no disparities associated with many of the demographic or community characteristics examined (including sex, income or rural residence). Use of statins was lower in those aged ≥80 compared with younger age groups, although this disparity narrowed during the study. Persistently lower use of antihypertensives by minorities and by recent immigrants may be due to lower quality of care, barriers to access, or other patient or provider factors, which highlights the need for ongoing monitoring for disparities even in populations with universal drug insurance. Differences in medication utilization based on health status characteristics such as previous cardiovascular disease were medically indicated. CONCLUSIONS: Although a universal drug insurance programme was reasonably successful in ensuring few disparities in cardioprotective medication use by older patients with diabetes, disparities persisted for some subpopulations, so additional interventions continue to be needed to ensure equitable care.
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How this classification was reachedexpand
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 | 0.016 | 0.097 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".