Using a Discrete Choice Experiment to Elicit Public Views Regarding Priority Setting of New Pharmaceuticals
Notice bibliographique
Résumé
Background: Many countries (England, Australia) and most recently, Canada, with the initiation of the Common Drug Review process have developed committees to study whether new treatments should be reimbursed within a publicly funded health care system. The mandates of these organizations are to make funding decisions based upon evidence around effectiveness and cost-effectiveness of submitted medications. Despite the stated mandate of these organizations however, it has been noted that some medications associated with a large cost per QALY gain are funded, while others, with more attractive cost per QALY gained remain unfunded. This is not surprising given that the cost per QALY is purely concerned with a particular and limited definition of efficiency. Societies are also concerned with equity, and aspects of benefit other than those captured in the traditional QALY framework. There is little information available about what the public's preferences are with regard to priority setting for new pharmaceuticals. Thus, we conducted a discrete choice experiment (DCE) to elicit the views of the public in Alberta, Canada on what characteristics of new drugs matter in determining which new drugs should be added to the formulary. Methods: A discrete choice experiment was developed to find out the public's preferences for six features of a hypothetical new drug for a generic chronic health condition given a fixed budget. The six features of the new treatments were baseline life expectancy, gain to life expectancy, baseline quality of life (measured in QALYs), gain to quality of life (measured in QALYs), number of patients treated with the new drug, and the age group of the patients. The design accounted for potential interactions between key attributes. The survey was administered by mail, and included 10 choices as part of the DCE as well as questions about demographics, self-assessed health and prescription drug use and insurance coverage . Results: 423 surveys were returned, representing a response rate of 34%. Preliminary results indicate that all else being equal, the public would prefer to give priority to new drugs which treat a group with a higher baseline life expectancy, which provide a greater gain to life expectancy, which treat a group with a lower baseline quality of life, which provide a greater gain to quality of life, which treat more people, and which treat 35-54 year olds (compared to both younger or older patients). These indicate that people do account for characteristics other than just QALYs in determining which new drugs should be added to forumulary. Marginal rates of substitution will be presented using gain to life expectancy as a numeraire, showing how many additional life years would be needed to induce a switch to priorize a drug with less preferred characteristics. Discussion: Our study has shown the feasability of this methodology for eliciting public views for use in priority setting. The implications of this study and how this information may be used in informing decision making within drug evaluation committees will be discussed.
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 | 0,031 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 ».