ObjectiveTo investigate the epidemiology of medication errors and error-related adverse events in adults in primary care, ambulatory care and patients’ homes.DesignSystematic review.Data sourceSix ...international databases were searched for publications between 1 January 2006 and 31 December 2015.Data extraction and analysisTwo researchers independently extracted data from eligible studies and assessed the quality of these using established instruments. Synthesis of data was informed by an appreciation of the medicines’ management process and the conceptual framework from the International Classification for Patient Safety.Results60 studies met the inclusion criteria, of which 53 studies focused on medication errors, 3 on error-related adverse events and 4 on risk factors only. The prevalence of prescribing errors was reported in 46 studies: prevalence estimates ranged widely from 2% to 94%. Inappropriate prescribing was the most common type of error reported. Only one study reported the prevalence of monitoring errors, finding that incomplete therapeutic/safety laboratory-test monitoring occurred in 73% of patients. The incidence of preventable adverse drug events (ADEs) was estimated as 15/1000 person-years, the prevalence of drug–drug interaction-related adverse drug reactions as 7% and the prevalence of preventable ADE as 0.4%. A number of patient, healthcare professional and medication-related risk factors were identified, including the number of medications used by the patient, increased patient age, the number of comorbidities, use of anticoagulants, cases where more than one physician was involved in patients’ care and care being provided by family physicians/general practitioners.ConclusionA very wide variation in the medication error and error-related adverse events rates is reported in the studies, this reflecting heterogeneity in the populations studied, study designs employed and outcomes evaluated. This review has identified important limitations and discrepancies in the methodologies used and gaps in the literature on the epidemiology and outcomes of medication errors in community settings.
Cannabidiol (CBD) is ubiquitous in state-based medical cannabis programs and consumer products for complementary health or recreational use. CBD has intrinsic pharmacologic effects and associated ...adverse drug events (ADEs) along with the potential for pharmacokinetic and pharmacodynamic drug-drug interactions (DDIs). Given CBD use among patients with complex conditions and treatment regimens, as well as its expanded consumer use, awareness of potential safety issues with CBD is needed. Prescribing information for federally approved products containing CBD were reviewed. Data on ADEs and DDIs were extracted and summarized. Nearly one-half of CBD users experienced ADEs, which displayed a general dose-response relationship. Common ADEs include transaminase elevations, sedation, sleep disturbances, infection, and anemia. Given CBD effects on common biological targets implicated in drug metabolism (e.g., CYP3A4/2C19) and excretion (e.g., P-glycoprotein), the potential for DDIs with commonly used medication is high. General clinical recommendations of reducing substrate doses, monitoring for ADEs, and finding alternative therapy should be considered, especially in medically complex patients. CBD is implicated as both a victim and perpetrator of DDIs and has its own ADE profile. These effects should be considered in the risk-benefit assessment of CBD therapy and patients and consumers made aware of potential safety issues with CBD use.
Background: One of the FDA-approved treatments for COVID-19 is remdesivir. In this study, we investigated adverse drug events (ADEs) of remdesivir in COVID-19 patients who contacted 13-Aban ...pharmacy's drug and poison information center (DPIC). Methods: In this study, data of patients receiving remdesivir who contacted the 13-Aban pharmacy's DPIC between April 2021 and May 2022 were extracted. For the evaluation of potential ADEs, we reviewed all contacts related to remdesivir recipients. Results: Out of 223 patients enrolled, 108 (48.40%) developed 120 ADEs. Elevated liver transaminase levels (26.67%) were the most common ADE, followed by weakness (7.5%), nausea, and vomiting (7.5%). The causality assessment of ADE using the Naranjo scale revealed that 41.67% were probable and 58.33% were possible. Conclusion: Based on the results of this study, hepatic dysfunction was the most prevalent ADE among remdesivir recipients; thus, in order to ensure safe use of remdesivir, patients should be closely monitored for this ADE.
Background: Digital reporting of adverse events remains the most important tool to improve pharmacovigilance information related to drugs introduced in the market with good efficacy and limited ...safety knowledge perceived from clinical trials.Aim of the Study: The study aimed to identify the knowledge and awareness of digital reporting of adverse drug events among healthcare professionals working at a tertiary care hospital in India.Materials and Methods: A cross-sectional descriptive questionnaire-based study was conducted with Physicians, Pharmacists, Technicians and Nurses. The questionnaire comprised items regarding awareness of pharmacovigilance and digital reporting of ADRs and perception and attitudes of healthcare professionals in digital reporting of adverse drug events. Descriptive statistics were used to analyse the data.Results: Healthcare professionals received 200 questionnaires in total, and 200 participants responded, yielding a 100% response rate among which 108 were male and 92 were female. 98 doctors, 32 pharmacists, 11 technicians, and 59 nurses comprised the group of healthcare professionals. 72% of healthcare professionals were familiar with the phrase "pharmacovigilance." Nearly 73% of healthcare professionals did not know the method of digital reporting of ADR and their nearby pharmacovigilance centers. In addition, 88% agreed that ADRs need to be reported digitally because it is easy and convenient and 92% agreed that it is their professional responsibility.Conclusion: Our study shows that awareness of pharmaco-vigilance and digital ADR reporting among healthcare professionals is relatively low.
Identification of unintended drug effects, specifically drug repurposing opportunities and adverse drug events, maximizes the benefit of a drug and protects the health of patients. However, current ...observational research methods are subject to several biases. These include confounding by indication, reverse causality and missing data. We propose that Mendelian randomization (MR) offers a novel approach for the prediction of unintended drug effects. In particular, we advocate the synthesis of evidence from this method and other approaches, in the spirit of triangulation, to improve causal inferences concerning drug effects. MR addresses some of the limitations associated with the existing methods in this field. Furthermore, it can be applied either before or after approval of the drug, and could therefore prevent the potentially harmful exposure of patients in clinical trials and beyond. The potential of MR as a pharmacovigilance and drug repurposing tool is yet to be realized, and could both help prevent adverse drug events and identify novel indications for existing drugs in the future.
OBJECTIVES:The objective of this systematic review and meta-analysis was to assess the effects of including critical care pharmacists in multidisciplinary ICU teams on clinical outcomes including ...mortality, ICU length of stay, and adverse drug events.
DATA SOURCES:PubMed, EMBASE, and references from previous relevant systematic studies.
STUDY SELECTION:We included randomized controlled trials and nonrandomized studies that reported clinical outcomes such as mortality, ICU length of stay, and adverse drug events in groups with and without critical care pharmacist interventions.
DATA EXTRACTION:We extracted study details, patient characteristics, and clinical outcomes.
DATA SYNTHESIS:From the 4,725 articles identified as potentially eligible, 14 were included in the analysis. Intervention of critical care pharmacists as part of the multidisciplinary ICU team care was significantly associated with the reduced likelihood of mortality (odds ratio, 0.78; 95% CI, 0.73–0.83; p < 0.00001) compared with no intervention. The mean difference in ICU length of stay was –1.33 days (95% CI, –1.75 to –0.90 d; p < 0.00001) for mixed ICUs. The reduction of adverse drug event prevalence was also significantly associated with multidisciplinary team care involving pharmacist intervention (odds ratio for preventable and nonpreventable adverse drug events, 0.26; 95% CI, 0.15–0.44; p < 0.00001 and odds ratio, 0.47; 95% CI, 0.28–0.77; p = 0.003, respectively).
CONCLUSIONS:Including critical care pharmacists in the multidisciplinary ICU team improved patient outcomes including mortality, ICU length of stay in mixed ICUs, and preventable/nonpreventable adverse drug events.
Aims
We aimed to investigate the efficacy and effectiveness of pharmacist‐led interventions to reduce adverse drug events (ADEs) in older people living in residential aged care facilities (RACFs).
...Methods
We systematically searched MEDLINE via PubMed, Embase, Cochrane Central Register of Controlled Trials and PsycINFO from their inceptions to July 2020. We investigated experimental study designs that employed a control group, or quasi‐experimental studies conducted in RACFs.
Results
We screened 3826 records and included 23 studies. We found seven single‐component and 16 multicomponent pharmacist‐led interventions to reduce ADEs in older people living in RACFs. The most frequent single‐component pharmacist‐led intervention was medication review. Medication review and education provision to healthcare professionals were the most common components in many pharmacist‐led multicomponent interventions. Thirteen studies (56%) showed no effect, whereas ten studies (43%) reported significant reductions in ADEs following pharmacist‐led interventions either as a sole intervention or as a part of a multi‐component intervention. Many interventions focused on reducing the incidence of falls (39%).
Conclusions
This systematic review suggests that pharmacist‐led interventions have the potential to reduce the incidence of ADEs in older people living in RACFs. Medication review and educational programmes, particularly academic detailing, either as a single component or as part of multicomponent interventions were the most common approaches to reducing drug‐related harm in older people living in RACFs. The lack of a positive association between interventions and ADE in many studies suggests that targeted and tailored pharmacist‐led interventions are required to reduce ADEs in older people in RACFs.
Ipilimumab 3 mg/kg was the first agent to demonstrate improved survival in previously treated patients with metastatic melanoma in a phase 3 trial (MDX010-20). Ipilimumab produced a characteristic ...spectrum of immune-related adverse events (irAEs) of special interest, consistent with its immune-based mechanism of action.
In MDX010-20, 676 previously treated patients were randomized 3:1:1 to receive ipilimumab 3 mg/kg plus the glycoprotein 100 melanoma antigen vaccine (gp100), ipilimumab 3 mg/kg + placebo, or gp100 vaccine + placebo. For the current report, the authors conducted a detailed analysis of the time to onset and resolution of irAEs associated with ipilimumab therapy.
Grade 2 through 5 irAEs generally developed during the induction phase of treatment (0-12 weeks). Most, including grade 3/4 irAEs, were reversible when managed with treatment guidelines using vigilant monitoring and corticosteroids. The median time to resolution (to grade 1 or 0 or to the grade at baseline) of irAEs that had an onset during the induction phase was approximately 6 weeks for grade 2 through 4 irAEs and 8 weeks for grade 3 and 4 irAEs. Across the entire study duration, most grade 2 through 4 irAEs resolved within 12 weeks.
Most ipilimumab-associated irAEs, including grade 3/4 symptoms, developed within 12 weeks of initial dosing and resolved within 12 weeks of onset. IrAEs were well characterized in their evolution and could be managed using published algorithms.
Adverse Drug Event (ADE) extraction is one of the core tasks in digital pharmacovigilance, especially when applied to informal texts. This task has been addressed by the Natural Language Processing ...community using large pre-trained language models, such as BERT. Despite the great number of Transformer-based architectures used in the literature, it is unclear which of them has better performances and why. Therefore, in this paper we perform an extensive evaluation and analysis of 19 Transformer-based models for ADE extraction on informal texts. We compare the performance of all the considered models on two datasets with increasing levels of informality (forums posts and tweets). We also combine the purely Transformer-based models with two commonly-used additional processing layers (CRF and LSTM), and analyze their effect on the models performance. Furthermore, we use a well-established feature importance technique (SHAP) to correlate the performance of the models with a set of features that describe them: model category (AutoEncoding, AutoRegressive, Text-to-Text), pre-training domain, training from scratch, and model size in number of parameters. At the end of our analyses, we identify a list of take-home messages that can be derived from the experimental data.
Abstract
Objective
This article presents our approaches to extraction of medications and associated adverse drug events (ADEs) from clinical documents, which is the second track of the 2018 National ...NLP Clinical Challenges (n2c2) shared task.
Materials and Methods
The clinical corpus used in this study was from the MIMIC-III database and the organizers annotated 303 documents for training and 202 for testing. Our system consists of 2 components: a named entity recognition (NER) and a relation classification (RC) component. For each component, we implemented deep learning-based approaches (eg, BI-LSTM-CRF) and compared them with traditional machine learning approaches, namely, conditional random fields for NER and support vector machines for RC, respectively. In addition, we developed a deep learning-based joint model that recognizes ADEs and their relations to medications in 1 step using a sequence labeling approach. To further improve the performance, we also investigated different ensemble approaches to generating optimal performance by combining outputs from multiple approaches.
Results
Our best-performing systems achieved F1 scores of 93.45% for NER, 96.30% for RC, and 89.05% for end-to-end evaluation, which ranked #2, #1, and #1 among all participants, respectively. Additional evaluations show that the deep learning-based approaches did outperform traditional machine learning algorithms in both NER and RC. The joint model that simultaneously recognizes ADEs and their relations to medications also achieved the best performance on RC, indicating its promise for relation extraction.
Conclusion
In this study, we developed deep learning approaches for extracting medications and their attributes such as ADEs, and demonstrated its superior performance compared with traditional machine learning algorithms, indicating its uses in broader NER and RC tasks in the medical domain.
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