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Purpose: In drug safety, there is a lack of guidance on how prioritization of safety issues should be performed. The aim of this literature review is to provide an overview of criteria used for signal prioritization and of the associated decision support frameworks., Methods: A search strategy was constructed to identify relevant articles in Medline/Embase databases from the period from 1 January 1995 to 31 August 2015. The prioritization criteria were extracted and classified in relevant categories., Results: From an initial set of 63 articles, 11 were retained for full review. The articles mentioned 48 criteria used in the prioritization process, with a median of six criteria per study [range: 1-16]. More than half of the criteria (63%), referred to strength of evidence while 19% related to public health impact, 14% to general public and media attention and 4% to novelty of the drug event association. Fifteen criteria were tested for predictive value with 11 showing positive results, most of them from the strength of evidence category. Six decision-making frameworks are presented, which incorporate criteria from various categories. Five of these frameworks were tested against expert decisions or by other means, but only in one database each and for a limited set of products., Conclusions: There is a wide range of prioritization criteria described in the literature; however, few of them demonstrated predictive value. Many criteria with predictive value were related to strength of evidence category and to novelty. There were few attempts at integrating different criteria in decision support frameworks. Five of the frameworks were tested for validity and showed usefulness, while at least three are already in use for prioritization. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Purpose: To provide estimates of the number and types of drugs that can be monitored for safety surveillance using electronic healthcare databases., Methods: Using data from eight European databases (administrative claims, medical records) and in the context of a cohort study, we determined the amount of drug exposure required for signal detection across varying magnitudes of relative risk (RR). We provide estimates of the number and types of drugs that can be monitored as a function of actual use, minimal detectable RR, and empirically derived incidence rates for the following adverse events: (i) acute myocardial infarction; (ii) acute renal failure; (iii) anaphylactic shock; (iv) bullous eruptions; (v) rhabdomyolysis; and (vi) upper gastrointestinal bleeding. We performed data simulation to see how expansion of database size would influence the capabilities of such system., Results: Data from 1,947,452 individuals (59,594,132 person-years follow-up) who used 2,289 drugs in the EU-ADR network show that for a frequent event such as acute myocardial infarction, there are 531 drugs (23% of total) for which an association with RR = 2, if present, can be investigated. For a rare event such as rhabdomyolysis, there are 19 drugs (1%) for which an association of same magnitude can be investigated., Conclusion: Active surveillance using healthcare data-based networks for signal detection is feasible, although the leverage to do so may be low for infrequently used drugs and for rare outcomes. Extending database network size to include data from heterogeneous populations and increasing follow-up time are warranted to maximize leverage of these surveillance systems., (Copyright © 2012 John Wiley & Sons, Ltd.)

Purpose: In this proof-of-concept paper we describe the framework, process, and preliminary results of combining data from European electronic healthcare record (EHR) databases for large-scale monitoring of drug safety., Methods: Aggregated demographic, clinical, and prescription data from eight databases in four countries (Denmark, Italy, Netherlands, the UK) were pooled using a distributed network approach by generation of common input data followed by local aggregation through custom-built software, Jerboa(©). Comparison of incidence rates of upper gastrointestinal bleeding (UGIB) and nonsteroidal anti-inflammatory drug (NSAID) utilization patterns were used to evaluate data harmonization and quality across databases. The known association of NSAIDs and UGIB was employed to demonstrate sensitivity of the system by comparing incidence rate ratios (IRRs) of UGIB during NSAID use to UGIB during all other person-time., Results: The study population for this analysis comprised 19,647,445 individuals corresponding to 59,929,690 person-years of follow-up. 39,967 incident cases of UGIB were identified during the study period. Crude incidence rates varied between 38.8 and 109.5/100,000 person-years, depending on country and type of database, while age-standardized rates ranged from 25.1 to 65.4/100,000 person-years. NSAID use patterns were similar for databases within the same country but heterogeneous among different countries. A statistically significant age- and gender-adjusted association between use of any NSAID and increased risk for UGIB was confirmed in all databases, IRR from 2.0 (95%CI:1.7-2.2) to 4.3 (95%CI: 4.1-4.5)., Conclusions: Combining data from EHR databases of different countries to identify drug-adverse event associations is feasible and can set the stage for changing and enlarging the scale for drug safety monitoring., (Copyright © 2010 John Wiley & Sons, Ltd.)