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Enregistrement W2063531135 · doi:10.1111/jgs.12237

Comment on “Association Between the Part D Coverage Gap and Adverse Health Outcomes”

2013· letter· en· W2063531135 sur OpenAlexaff
Sherif Eltonsy, Cara Tannenbaum, Lucie Blais

Notice bibliographique

RevueJournal of the American Geriatrics Society · 2013
Typeletter
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueHealth Systems, Economic Evaluations, Quality of Life
Établissements canadiensUniversité de Montréal
Organismes subventionnairesnon disponible
Mots-clésDiscontinuationMedicineAdverse effectMediationPsychiatryInternal medicine

Résumé

récupéré en direct d'OpenAlex

To the Editor: We read with great interest the article by Polinski et al.1 which adds important information to the growing body of literature on the effect of the Medicare Part D coverage gap. The study concludes that older adults facing the coverage gap are at greater risk of temporarily discontinuing their medications than persons with full insurance coverage, although the study results show no significant effect of medication discontinuation on the risk of adverse health outcomes. Despite the use of robust adjustment and sensitivity analysis techniques to evaluate the latter association, a number of methodological limitations of the study should be carefully considered. Studying the effect of the coverage gap on adverse health outcomes through medication discontinuation as a mediator requires sound relations between the coverage gap and drug discontinuation on one hand and between drug discontinuation and health outcomes on the other (Figure 1). We believe that the latter association was unlikely to be present in the Polinski et al. study because of the short follow-up period and the absence of a direct link between individuals who discontinued their medications and those who experienced adverse health outcomes. The effect of the coverage gap on health outcomes through drug discontinuation could have been estimated using mediation analysis.2 Mediation analysis in the framework of counterfactuals3-6 can test whether the greater risk of adverse health outcomes caused by the coverage gap is entirely mediated through medication discontinuation and, if not, what proportion of increased risk is directly caused by pathways other than medication discontinuation. The method of causal mediation analysis using propensity scores has been described and applied in previous studies.7, 8 Other study design features may have contributed to masking the effect of the coverage gap on health outcomes. The authors considered the discontinuation of several medication classes that treat several diseases. Among them were medications to treat cardiovascular diseases that can directly affect death rates and cardiovascular outcomes. Cardiovascular drug classes include a range of drugs that vary considerably in pharmacological mechanism and price. It is more likely that an individual will discontinue an expensive medication than a cheaper one. Discontinuation of an expensive medication (e.g., statins) may not lead to short-term adverse health outcomes, whereas skipping doses of less-expensive medications (e.g. diuretics) may be more likely to elicit immediate effects. By measuring discontinuation of any medication, the observed effect on health outcomes may have been attenuated. A more-valid approach would be to examine health outcomes of those who discontinue specific classes of medications—especially those with short-term adverse effects. Furthermore, the exposure period to the coverage gap was brief for most participants. To evaluate the long-term effect of medication discontinuation, exposure should be redefined as a cumulative or continuous measure of the total number of days in the gap over subsequent years. Finally, by conducting subanalyses for disease-specific outcomes, it is not clear whether the study was sufficiently powered to detect significant differences in outcomes over the short coverage gap exposure period. To summarize, the study demonstrates a significant increase in medication discontinuation rates due to the coverage gap, but its effect on short- and long-term health outcomes remains unclear. Methodological aspects such as the ability to link those who discontinued to health outcomes, the study of specific classes of medications that can cause short-term adverse effects if discontinued, and the redefinition of the exposure into a cumulative measure need to be addressed to discern the true clinical effect of the coverage gap. Conflict of Interest: The editor in chief has reviewed the conflict of interest checklist provided by the authors and has determined that the authors have no financial or any other kind of personal conflicts with this paper. Author Contributions: All authors contributed equally in the preparation of manuscript. Sponsor's Role: None.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,012
score de la tête « metaresearch » (Gemma)0,073
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,043
Score d'incertitude au seuil0,063

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0120,073
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,003
Bibliométrie0,0020,002
Études des sciences et des technologies0,0030,004
Communication savante0,0040,005
Science ouverte0,0070,003
Intégrité de la recherche0,0430,048
Charge utile insuffisante (le modèle a refusé de juger)0,0090,008

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.

Tête enseignante Opus0,187
Tête enseignante GPT0,383
Écart entre enseignants0,196 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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