Improving the Safety of Medicines via Digital Technology: An Assessment of the Scope and Quality of Risk Minimization Websites in the United States and United Kingdom
Notice bibliographique
Résumé
EHealth holds tremendous promise for enhancing drug safety initiatives known as risk minimization programs. Little is known, however, regarding the scope and quality of existing risk minimization websites. Two publicly accessible repositories, REMS@FDA [1] and Electronic Medicines Compendium [2], were reviewed to identify all regulatorily approved risk minimization programs in the United States (US) and United Kingdom (UK) with websites. Website quality was evaluated using the Enlight Quality Assessment tool, a psychometrically validated instrument that addresses seven quality domains. Ninety-three websites were identified: 59 for healthcare professionals (7 UK/52 US), and 34 for patients (5 UK/29 US). The websites functioned chiefly as archives for electronic copies of educational materials; a subset (31/93) had additional features. Mean quality ratings for Usability (mean 4.70, SD 0.59), Visual Design (mean 4.03, SD 0.87) and Content (mean 4.31, SD 0.82) were good. General Subjective Evaluation was fair (mean 3.15, SD 1.21). Mean scores for Therapeutic Alliance and Therapeutic Persuasiveness were poor (mean 2.62, SD 1.47; and mean 2.50, SD 1.48, respectively); those for User Engagement were very poor (mean 2.25, SD 1.03). No differences were found by target audience but several were identified based on region. Risk minimization websites are easy to navigate and well organized. Few, however, incorporate eHealth design elements that facilitate user engagement, build therapeutic alliance and exert therapeutic persuasiveness. Such elements can enhance program uptake and effectiveness. Results highlight opportunities for improving the quality of risk minimization websites and their ability to bridge pharmaceutical and healthcare systems. A risk minimization program is a type of drug safety measure to ensure that a medicine’s benefits outweigh its risks. Electronic versions of these risk minimization programs (websites) offer new ways to reach and educate patients and healthcare professionals. We conducted a study to examine the quality of these websites. We reviewed all approved risk minimization programs in the United States (US) and the United Kingdom (UK) using two publicly available repositories, REMS@FDA and Electronic Medicines Compendium, to identify risk minimization websites. We assessed website quality using the Enlight Quality Assessment tool. We found 93 websites: 59 for healthcare professionals (7 UK/52 US) and 34 for patients (5 UK/29 US). Our analysis showed that the websites were well organized and easy to search. Few, however, used specific electronic design elements that can promote trust in and engagement with the content of the website, and can encourage users to follow the recommended actions for safe and appropriate use of the medicine. In conclusion, there are multiple ways that the design of risk minimization websites could be improved in order to make them more effective as drug safety measures.
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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 | 0,019 | 0,075 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».