Quantifying Industry Spending on Promotional Events Using Open Payments Data
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Notice bibliographique
Résumé
Importance: Sponsorship of promotional events for health professionals is a key facet of marketing campaigns for pharmaceuticals and medical devices; however, there appears to be limited transparency regarding the scope and scale of this spending. Objective: To develop a novel method for describing the scope and quantifying the spending by US pharmaceutical and medical companies on industry-sponsored promotional events for particular products. Design and Setting: This was a cross-sectional study using records from the Centers for Medicare & Medicaid's Open Payments database on payments made to prescribing clinicians from January 1 to December 21, 2022. Main Outcomes and Measures: An event-centric approach was used to define sponsored events as groupings of payment records with matching variables. Events were characterized by value (coffee, lunch, dinner, or banquet) and number of attendees (small vs large). To test the method, the number of and total spending for each type of event across professional groups were calculated and used to identify the top 10 products related to dinner events. To validate the method, we extracted all event details advertised on the websites of 4 state-level nurse practitioner associations that regularly hosted industry-sponsored dinner events during 2022 and compared these with events identified in the Open Payments database. Results: A total of 1 154 806 events sponsored by pharmaceutical and medical device companies were identified for 2022. Of these, 1 151 351 (99.7%) had fewer than 20 attendees, and 922 214 (80.0%) were considered to be a lunch ($10-$30 per person). Seven companies sponsored 16 031 dinners for the top 10 products. Of the 227 sponsored in-person dinner events hosted by the 4 state-level nurse practitioner associations, 168 (74.0%) matched events constructed from the Open Payments dataset. Conclusions and Relevance: These findings indicate that an event-centric analysis of Open Payments data is a valid method to understand the scope and quantify spending by pharmaceutical and medical device companies on industry-sponsored promotional events attended by prescribers. Expanding and enforcing the reporting requirements to cover all payments to all registered health professionals would improve the accuracy of estimates of the true extent of all sponsored events and their impact on clinical practice.
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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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 découle