Misreporting of coverage and cost-related non-adherence to prescription drugs: an analysis using the Canadian Community Health Survey
Notice bibliographique
Résumé
Background: Canada is the only developed country with universal healthcare but no universal prescription drug coverage. Prescription drug coverage in Canada is often described as a “patchwork” system; eligibility for coverage varies by province and influenced by circumstance. Subsets of the population are eligible for partial or full provincial coverage for their prescription medications through public and/or private coverage. Methods: The extent and factors associated with misreporting of drug insurance and cost-related non-adherence (CRNA) to prescribed medicines were investigated in three study populations: Ontario seniors 65 and over, Quebec seniors 65 and over, and Quebec adults 25-64 using pooled data from the 2015/2016 Canadian Community Health Survey (CCHS). The rationale for these study cohorts was that the vast majority had partial or full coverage for prescription medications from a public and/or private source. The factors associated with CRNA to prescribed medicines were also explored in these three subgroups. Results: There is a degree of misreporting of drug insurance among Ontario seniors (17%), Quebec seniors (18%) and Quebec adults (9%). Quebec adults who declared CRNA to prescribed drugs had twice the odds of misreporting prescription drug coverage (OR 2.1 95% CI 1.3-3.4). Lower-income earners among Ontario seniors (OR 1.8, 95% CI 1.3-2.6), Quebec seniors (OR 1.7 95% CI 1.2-2.6), and Quebec adults (OR 3.4, 95% CI 2.3-5.1) were more likely to misreport coverage. Quebec seniors were more likely to misreport if they had less than a secondary school education (OR 1.4, 95% CI 1.1-1.8). Ontario seniors who were immigrants were more likely to misreport coverage (OR 1.5, 95% CI 1.2-1.8), as were Quebec seniors who were immigrants (OR 2.2, 95% CI 1.4-3.5). Ontario seniors who had a flu shot in the past 12 months (OR 0.7, 95% CI 0.5-9.9) and Quebec adults who had visited a GP in the past 12 months (OR 0.6, 95% CI 0.45,0.77) were less likely to misreport coverage. CRNA to prescribed drugs was reported by Ontario seniors (3.3%), Quebec seniors (2.5%), and Quebec adults (5.3%). Low-income Ontario seniors (OR 2.9, 95% CI 1.5-5.7) and Quebec adults (2.5, 95% CI 1.6-3.8) were more likely to report CRNA to prescribed medicines. Quebec adults with chronic conditions (OR 1.7, 95% CI 1.2-2.4) and those in self-reported poor health (OR 2.4, 95% CI 1.3-4.4) were also more likely to report CRNA to prescribed drugs. Conclusions: There appears to be a socio-economic gradient in misreporting and CRNA among Ontario seniors, Quebec seniors, and Quebec adults. Given most of these subgroups will have coverage, we hypothesize a degree of measurement error among responses. More specifically, respondents who report CRNA to prescribed medicines may reflect measurement error.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,005 | 0,014 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».