Motives to Report Adverse Drug Reactions to the National Agency:A Survey Study among Healthcare Professionals and Patients in Croatia, The Netherlands, and the UK

Introduction Healthcare professionals (HCPs) and patients have various motives to report adverse drug reactions (ADRs) to their national agency. These motives may differ between countries. Objective The aim of this study was to assess to what extent motives of HCPs and patients to report ADRs differ between countries. Methods HCPs and patients from Croatia (HR), The Netherlands (NL), and the UK were asked to complete a web-based survey containing questions regarding demographics and ADR reporting. HCPs and patients could select all motives for reporting that applied to them, with a total of 23 and 24 motives, respectively. Descriptive statistics are presented and Chi-square tests were used to test for differences across the countries, with effect sizes calculated using Cramer's V. Results In total, 296 HCPs and 423 patients were included (60% and 32% from Croatia, 19% and 44% from NL, and 21% and 24% from the UK, respectively). For most of the motives to report or not to report an ADR, there were no differences between countries. Most HCPs from all countries would be motivated to report an ADR if there was a strong suspicion of causality (89%), if it concerned a severe/serious ADR (86%), and if it concerned an ADR for a new, recently marketed drug (77%). Most patients from all countries agreed that they would report an ADR if it concerned a severe ADR (96%), if the ADR influenced their daily activities (91%), and if they were worried about their own situation (90%). Differences across the countries (p V &gt;= 0.21) were observed for three and four of the HCP and patient motives, respectively. For HCPs, these differences were seen in motives related to legal obligation (65% HR, 24% NL, 38% UK), black triangle medicines (27% HR, 4% NL, 77% UK), and the reporting of well-known ADRs (53% HR, 85% NL, 69% UK). For patients, these differences were seen in motives related to a linkage between the ADR report and the medical notes (59% HR, 60% NL, 30% UK), complexity and time taken to report (25% HR, 13% NL, 40% UK), medicines purchased on the internet (59% HR, 39% NL, 65% UK), and the reporting of embarrassing ADRs (32% HR, 11% NL, 35% UK). Conclusions HCPs' and patients' motives to report or not to report ADRs to the national agency were mostly similar across the three countries. Such motives can be used in general strategies to promote and increase ADR reporting. The observed differences provide guidance to further fine-tune ADR reporting at a national level.</p

Use of a Patient-Friendly Terms List in the Adverse Drug Reaction Report Form: A Database Study

INTRODUCTION: When reporting adverse drug reactions to pharmacovigilance centres, patients and consumers can describe adverse drug reactions experienced in free-text format. Recently, a patient-friendly adverse drug reaction terms list was introduced in the adverse drug reaction report form in the UK to facilitate this reporting. OBJECTIVE: The objective of this study was to evaluate the actual use of the patient-friendly terms list in the adverse drug reaction report form and its association with the type of adverse drug reactions reported. METHODS: We conducted a database study in which we reviewed the list's use for all reported adverse drug reactions by patients and consumers to the pharmacovigilance centre in the UK via the online report form between August and September 2017. Descriptive statistics were used. In addition, for adverse drug reactions reported more than 20 times, Chi-squared tests were used to test for differences in the number of reports in which the patient-friendly terms list was used and those in which the adverse drug reaction was entered as free text. RESULTS: In total, 888 reports were received. In 185 reports (21%), the patient-friendly terms list was used to enter an adverse drug reaction. In total, the reports contained 3227 adverse drug reactions. Nausea, headache, diarrhoea, dizziness, insomnia, anxiety, depression, fatigue, tiredness, vomiting, appetite lost, joint pain, chest pain, constipation and pain were reported more than 20 times. Five of these adverse drug reactions (i.e. nausea, diarrhoea, dizziness, insomnia and constipation) were reported significantly more often in reports where the adverse drug reactions were selected from the patient-friendly terms list. CONCLUSIONS: Most people chose to describe adverse drug reactions in their own words rather than selecting adverse drug reactions from a patient-friendly terms list. Although the patient-friendly terms list may be a useful feature for some patients or for some adverse drug reactions, it should not replace the option for patients to describe adverse drug reactions in their own words

Recommendations on the Use of Mobile Applications for the Collection and Communication of Pharmaceutical Product Safety Information: Lessons from IMI WEB-RADR

Over a period of 3 years, the European Union's Innovative Medicines Initiative WEB-RADR (Recognising Adverse Drug Reactions; https://web-radr.eu/) project explored the value of two digital tools for pharmacovigilance (PV): mobile applications (apps) for reporting the adverse effects of drugs and social media data for its contribution to safety signalling. The ultimate intent of WEB-RADR was to provide policy, technical and ethical recommendations on how to develop and implement such digital tools to enhance patient safety. Recommendations relating to the use of mobile apps for PV are summarised in this paper. There is a presumption amongst at least some patients and healthcare professionals that information ought to be accessed and reported from any setting, including mobile apps. WEB-RADR has focused on the use of such technology for reporting suspected adverse drug reactions and for broadcasting safety information to its users, i.e. two-way risk communication. Three apps were developed and publicly launched within Europe as part of the WEB-RADR project and subsequently assessed by a range of stakeholders to determine their value as effective tools for improving patient safety; a fourth generic app was later piloted in two African countries. The recommendations from the development and evaluation of the European apps are presented here with supporting considerations, rationales and caveats as well as suggested areas for further research

Recommendations for the Use of Social Media in Pharmacovigilance: Lessons from IMI WEB-RADR

A central problem in e-commerce is determining overlapping communities among individuals or objects in the absence of external identification or tagging. We address this problem by introducing a framework that captures the notion of communities or clusters determined by the relative affinities among their members. To this end we define what we call an affinity system, which is a set of elements, each with a vector characterizing its preference for all other elements in the set. We define a natural notion of (potentially overlapping) communities in an affinity system, in which the members of a given community collectively prefer each other to anyone else outside the community. Thus these communities are endogenously formed in the affinity system and are "self-determined" or "self-certified" by its members. We provide a tight polynomial bound on the number of self-determined communities as a function of the robustness of the community. We present a polynomial-time algorithm for enumerating these communities. Moreover, we obtain a local algorithm with a strong stochastic performance guarantee that can find a community in time nearly linear in the of size the community. Social networks fit particularly naturally within the affinity system framework -- if we can appropriately extract the affinities from the relatively sparse yet rich information from social networks, our analysis then yields a set of efficient algorithms for enumerating self-determined communities in social networks. In the context of social networks we also connect our analysis with results about $(\alpha,\beta)$-clusters introduced by Mishra, Schreiber, Stanton, and Tarjan \cite{msst}. In contrast with the polynomial bound we prove on the number of communities in the affinity system model, we show that there exists a family of networks with superpolynomial number of $(\alpha,\beta)$-clusters.Comment: 22 page