The Impact of Prescription Medication Cost Coverage on Oral Medication Use for Hypertension and Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: No previous study, to the best of our knowledge, has examined both the time trend and impact of not having insurance or prescription medication cost coverage (PMCC) on the usage of type 2 diabetes and hypertension oral medications in Ontario and New Brunswick, Canada.Methods: We used data from the Canadian Community Health Survey (CCHS) from 2007 to 2014 to examine the time trend and impact of PMCC.A multivariable-adjusted logistic regression model was fitted.Results: The pseudo-cohort included 23,215 individuals representing a population of approximately 8.7 million people.Overall, 20.0% of respondents reported absence of PMCC.This proportion increased slightly from 19.6% (95% confidence interval [CI] 95% CI [17.5, 22.5]) to 20.7% (95% CI [16.9, 23.1]).Adjusted odds ratios (OR) showed that uninsured individuals were 23% less likely to use their medications (OR = 0.77, 95% CI [0.657, 0.911]).Conclusion: There was a slight decline in PMCC over time and this decline was associated with reduced use of medications for type 2 diabetes and hypertension. RésuméContexte : Aucune étude, à notre connaissance, n' a examiné à la fois la tendance temporelle et l'impact de l' absence de régime d' assurance ou de couverture du coût des médicaments d' ordonnance (CCMO) sur l' utilisation des médicaments oraux contre le diabète de type 2 et l'hypertension en Ontario et au Nouveau-Brunswick, au Canada.Méthode : Nous avons utilisé les données de l'Enquête sur la santé dans les collectivités canadiennes (ESCC) de 2007 à 2014 pour examiner la tendance temporelle et l'impact de la CCMO.Un modèle de régression logistique ajusté à plusieurs variables a été employé.Résultats : La pseudo-cohorte comprenait 23 215 individus représentant une population d' environ 8,7 millions de personnes.Dans l' ensemble, 20,0 % des répondants ont signalé ne pas avoir de CCMO.Cette proportion a légèrement augmenté, passant de 19,6 % (intervalle de confiance [IC] à 95% [17,5; 22,5]) à 20,7 % (IC à 95% [16,9; 23,1]).Les rapports de cote (RC) corrigés montrent que les personnes non assurées sont moins susceptibles, dans une proportion de 23 %, d' utiliser leurs médicaments (RC = 0,77, IC à 95% [0,657; 0,911]).Conclusion : Il y a eu une légère baisse de la CCMO au fil du temps et cette baisse est associée à une réduction de l' utilisation des médicaments pour le diabète de type 2 et l'hypertension. The Impact of Prescription Medication Cost Coverage on Oral Medication Use for Hypertension and Type 2 Diabetes Mellitus
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".