Informativité des déclarations de pharmacovigilance en médecine générale en France

Humbert, Xavier; Jacquot, Julien; Alexandre, Joachim; Sassier, Marion; Robin, Ninon; Pageot, Cécile; Kheloufi, Farid; Joyau, C.; Coquerel, Antoine; Durrieu, Geneviève; Fédrizzi, Sophie

doi:10.3917/spub.194.0561

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…In addition, our analysis revealed a positive association between reports marked as serious and well-documented Malaysian reports ( Figure 2 B), consistent with previous studies from France [ 25 , 26 ], China [ 14 , 24 ], and South Korea [ 18 ] that highlighted higher completeness for serious reports. Previous research has also indicated that Malaysian HCPs prioritize reporting serious AEs [ 71 ].…”

Section: Discussionsupporting

confidence: 91%

Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST

Choo,

Sartori,

Lee

et al. 2024

JMIR Med Inform

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Background The completeness of adverse event (AE) reports, crucial for assessing putative causal relationships, is measured using the vigiGrade completeness score in VigiBase, the World Health Organization global database of reported potential AEs. Malaysian reports have surpassed the global average score (approximately 0.44), achieving a 5-year average of 0.79 (SD 0.23) as of 2019 and approaching the benchmark for well-documented reports (0.80). However, the contributing factors to this relatively high report completeness score remain unexplored. Objective This study aims to explore the main drivers influencing the completeness of Malaysian AE reports in VigiBase over a 15-year period using vigiGrade. A secondary objective was to understand the strategic measures taken by the Malaysian authorities leading to enhanced report completeness across different time frames. Methods We analyzed 132,738 Malaysian reports (2005-2019) recorded in VigiBase up to February 2021 split into historical International Drug Information System (INTDIS; n=63,943, 48.17% in 2005-2016) and newer E2B (n=68,795, 51.83% in 2015-2019) format subsets. For machine learning analyses, we performed a 2-stage feature selection followed by a random forest classifier to identify the top features predicting well-documented reports. We subsequently applied tree Shapley additive explanations to examine the magnitude, prevalence, and direction of feature effects. In addition, we conducted time-series analyses to evaluate chronological trends and potential influences of key interventions on reporting quality. Results Among the analyzed reports, 42.84% (56,877/132,738) were well documented, with an increase of 65.37% (53,929/82,497) since 2015. Over two-thirds (46,186/68,795, 67.14%) of the Malaysian E2B reports were well documented compared to INTDIS reports at 16.72% (10,691/63,943). For INTDIS reports, higher pharmacovigilance center staffing was the primary feature positively associated with being well documented. In recent E2B reports, the top positive features included reaction abated upon drug dechallenge, reaction onset or drug use duration of <1 week, dosing interval of <1 day, reports from public specialist hospitals, reports by pharmacists, and reaction duration between 1 and 6 days. In contrast, reports from product registration holders and other health care professionals and reactions involving product substitution issues negatively affected the quality of E2B reports. Multifaceted strategies and interventions comprising policy changes, continuity of education, and human resource development laid the groundwork for AE reporting in Malaysia, whereas advancements in technological infrastructure, pharmacovigilance databases, and reporting tools concurred with increases in both the quantity and quality of AE reports. Conclusions Through interpretable machine learning and time-series analyses, this study identified key features that positively or negatively influence the completeness of Malaysian AE reports and unveiled how Malaysia has developed its pharmacovigilance capacity via multifaceted strategies and interventions. These findings will guide future work in enhancing pharmacovigilance and public health.

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Section: Discussionsupporting

confidence: 91%

Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST

Choo,

Sartori,

Lee

et al. 2024

JMIR Med Inform

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“…The risk is even greater in vulnerable populations such as the pediatric population [ 11 ]. In children, the pharmacokinetics and pharmacodynamics of drugs differ from those in adults and expose them to an increased risk of developing potentially serious adverse effects (e.g., Reye’s syndrome with aspirin or acute renal failure with ibuprofen in case of dehydration) [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Pediatric pharmaceutical interventions in self-medication: a descriptive study in community pharmacies

Bedhomme,

Vaillant-Roussel,

Vorilhon

et al. 2023

BMC Prim. Care

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Background The practice of self-medication is common but not without risk, especially for vulnerable populations such as the pediatric population. Community pharmacists have an important role of vigilance in dispensing drugs available without a medical prescription, with the possibility of carrying out a Pharmaceutical Intervention (PI) if necessary. The aim of our study was to characterize the Pediatric Pharmaceutical Interventions (PPIs) in self-medication carried out during a spontaneous request for a drug at the community pharmacy. Methods We conducted a descriptive study in 139 pharmacies in the Auvergne-Rhône-Alpes region (France). Data were collected from students under the supervision of internship masters in the pharmacy, using the validated GIPAMED (GrId for PhArmaceutical Self-MEDication interventions) notification grid, the first week of each month, from February to May for five years (2017 to 2021). Collected data were entered on a secure university platform. Results Of the 3,552 PIs collected, 8,3% (n = 286) were PPIs. Of these PPIs, 35% (n = 100) was generated by requests for optional prescription drugs contraindicated by the pathophysiological condition, 28.3% for drugs requiring a prescription and 20.6% for over the counter drugs not indicated by the symptomatology. Finally, 10% of requests required a referral for a medical consultation. Four Anatomical Therapeutic Chemical (ATC) classes accounted for more than 90% of the requests: respiratory system (39.5%), alimentary tract and metabolism (19.2%), nervous system (11.5%), and musculoskeletal system (10.8%). The most common drugs generating PPIs were: ibuprofen, oxomemazine and combination camphor/essential oils, mainly due to age-related or weight-related contraindication. Paracetamol also generated PPIs frequently, mainly due to problems with drug compliance and more precise infra-therapeutic doses. When these PPIs were dispensed, the pharmacist’s proposed solutions were accepted in 94.8% (n = 271) of the cases. Conclusions The community pharmacist has an important role in providing information about medicines and their correct use to patients. Our research shows that this attention benefits vulnerable populations, such as children, even for drugs that are widely used (e.g. paracetamol and non-steroidal anti-inflammatory drugs) or active substances for which there are age-related or weight-related contraindications (e.g. antitussives, camphor combinations).

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Are clinical data from spontaneous pharmacovigilance reports transmitted via the Ministry of Health's web portal sufficient to generate a signal without further documentation?

Grandvuillemin,

Jeannot,

Valnet-Rabier

et al. 2024

Therapies

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Informativité des déclarations de pharmacovigilance en médecine générale en France

Cited by 5 publications

References 19 publications

Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST

Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST

Pediatric pharmaceutical interventions in self-medication: a descriptive study in community pharmacies

Are clinical data from spontaneous pharmacovigilance reports transmitted via the Ministry of Health's web portal sufficient to generate a signal without further documentation?

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