How does direct-to-consumer advertising (DTCA) affect prescribing? A survey in primary care environments with and without legal DTCA.
Notice bibliographique
Résumé
BACKGROUND: Direct-to-consumer advertising (DTCA) of prescription drugs has increased rapidly in the United States during the last decade, yet little is known about its effects on prescribing decisions in primary care. We compared prescribing decisions in a US setting with legal DTCA and a Canadian setting where DTCA of prescription drugs is illegal, but some cross-border exposure occurs. METHODS: We recruited primary care physicians working in Sacramento, California, and Vancouver, British Columbia, and their group practice partners to participate in the study. On pre- selected days, patients aged 18 years or more completed a questionnaire before seeing their physician. We asked these patients' physicians to complete a brief questionnaire immediately following the selected patient visit. By pairing individual patient and physician responses, we determined how many patients had been exposed to some form of DTCA, the frequency of patients' requests for prescriptions for advertised medicines and the frequency of prescriptions that were stimulated by the patients' requests. We measured physicians' confidence in treatment choice for each new prescription by asking them whether they would prescribe this drug to a patient with the same condition. RESULTS: Seventy-eight physicians (Sacramento n = 38, Vancouver n = 40) and 1431 adult patients (Sacramento n = 683, Vancouver n = 748), or 61% of patients who consulted participating physicians on pre-set days, participated in the survey. Exposure to DTCA was higher in Sacramento, although 87.4% of Vancouver patients had seen prescription drug advertisements. Of the Sacramento patients, 7.2% requested advertised drugs as opposed to 3.3% in Vancouver (odds ratio [OR] 2.2, 95% confidence interval [CI] 1.2-4.1). Patients with higher self- reported exposure to advertising, conditions that were potentially treatable by advertised drugs, and/or greater reliance on advertising requested more advertised medicines. Physicians fulfilled most requests for DTCA drugs (for 72% of patients in Vancouver and 78% in Sacramento); this difference was not statistically significant. Patients who requested DTCA drugs were much more likely to receive 1 or more new prescriptions (for requested drugs or alternatives) than those who did not request DTCA drugs (OR 16.9, 95% CI 7.5-38.2). Physicians judged 50.0% of new prescriptions for requested DTCA drugs to be only "possible" or "unlikely" choices for other similar patients, as compared with 12.4% of new prescriptions not requested by patients (p < 0.001). INTERPRETATION: Our results suggest that more advertising leads to more requests for advertised medicines, and more prescriptions. If DTCA opens a conversation between patients and physicians, that conversation is highly likely to end with a prescription, often despite physician ambivalence about treatment choice.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».