Reporting, Monitoring, and Handling of Adverse Drug Reactions in Australia: Scoping Review
Notice bibliographique
Résumé
BACKGROUND: Adverse drug reactions (ADRs) are unintended consequences of medication use and may result in hospitalizations or deaths. Timely reporting of ADRs to regulators is essential for drug monitoring, research, and maintaining patient safety, but it has not been standardized in Australia. OBJECTIVE: We sought to explore the ways that ADRs are monitored or reported in Australia. We reviewed how consumers and health care professionals participate in ADR monitoring and reporting. METHODS: The Arksey and O'Malley framework provided a methodology to sort the data according to key themes and issues. Web of Science, Scopus, Embase, PubMed, CINAHL, and Computer & Applied Sciences Complete databases were used to extract articles published from 2010 to 2021. Two reviewers screened the papers for eligibility, extracted key data, and provided descriptive analysis of the data. RESULTS: Seven articles met the inclusion criteria. The Adverse Medicine Events Line (telephone reporting service) was introduced in 2003 to support consumer reporting of ADRs; however, only 10.4% of consumers were aware of ADR reporting schemes. Consumers who experience side effects were more likely to report ADRs to their doctors or pharmacists than to the drug manufacturer. The documentation of ADR reports in hospital electronic health records showed that nurses and pharmacists were significantly less likely than doctors to omit the description of the drug reaction, and pharmacists were significantly more likely to enter the correct classification of the drug reaction than doctors. Review and analysis of all ADR reports submitted to the Therapeutic Goods Administration highlighted a decline in physician contribution from 28% of ADR reporting in 2003 to 4% in 2016; however, within this same time period, hospital and community pharmacists were a major source of ADR reporting (ie, 16%). In 2014, there was an increase in ADR reporting by community pharmacists following the introduction of the GuildLink ADR web-based reporting system; however, a year later, the reporting levels dropped. In 2018, the Therapeutic Goods Administration introduced a black triangle scheme on the packaging of newly approved medicines, to remind and encourage ADR reporting on new medicines, but this was only marginally successful at increasing the quantity of ADR reports. CONCLUSIONS: Despite the existence of national and international guidelines for ADR reporting and management, there is substantial interinstitutional variability in the standards of ADR reporting among individual health care facilities. There is room for increased ADR reporting rates among consumers and health care professionals. A thorough assessment of the barriers and enablers to ADR reporting at the primary health care institutional levels is essential. Interventions to increase ADR reporting, for example, the black triangle scheme (alert or awareness) or GuildLink (digital health), have only had marginal effects and may benefit from further improvement revisions and awareness programs.
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 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 | 0,000 |
| 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 ».