Economic evaluations of health technologies in Dutch healthcare decision-making: a qualitative study of the current and potential use, barriers, and facilitators
Notice bibliographique
Résumé
BACKGROUND: The use of economic evaluations in healthcare decision-making can potentially help decision-makers in allocating scarce resources as efficiently as possible. Over a decade ago, the use of such studies was found to be limited in Dutch healthcare decision-making, but their current use is unknown. Therefore, this study aimed to provide insight into the current and potential use of economic evaluations in Dutch healthcare decision-making and to identify barriers and facilitators to the use of such studies. METHODS: Interviews containing semi-structured and structured questions were conducted among Dutch healthcare decision-makers. Participants were purposefully selected and special efforts were made to include decision-makers working at the macro- (national), meso- (local/regional), and micro-level (patient setting). During the interviews, a topic list was used that was based on the research questions and a literature search, and was developed in consultation with the Dutch National Healthcare Institute. Responses to the semi-structured questions were analyzed using a constant comparative approach. As for the structured questions, participants' definitions of various economic evaluation concepts were scored as either being "correct" or "incorrect" by two researchers, and summary statistics were prepared. RESULTS: Sixteen healthcare decision-makers were interviewed and two health economists. Decision-makers' knowledge of economic evaluations was only modest, and their current use appeared to be limited. Nonetheless, decision-makers recognized the importance of economic evaluations and saw several opportunities for extending their use at the macro- and meso-level, but not at the micro-level. The disparity between the limited use and recognition of the importance of economic evaluations is likely due to the many barriers decision-makers experience preventing their use (e.g. lack of resources, lack of formal willingness-to-pay threshold). Possible facilitators for extending the use of economic evaluations include, amongst others, educating decision-makers and the general population about economic evaluations and presenting economic evaluation results in a clearer and more understandable way. CONCLUSIONS: This study demonstrated that the current use and impact of economic evaluations in Dutch healthcare decision-making is limited at best. Therefore, strategies are needed to overcome the barriers that currently prevent economic evaluations from being used extensively.
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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 | 0,050 | 0,083 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,008 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,002 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».