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.
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.
Authors: Peter M Wahl; Joshua J Gagne; Thomas E Wasser; Debra F Eisenberg; J Keith Rodgers; Gregory W Daniel; Marcus Wilson; Sebastian Schneeweiss; Jeremy A Rassen; Amanda R Patrick; Jerry Avorn; Rhonda L Bohn Journal: Drug Saf Date: 2012-05-01 Impact factor: 5.606
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Authors: Ryen W White; Nicholas P Tatonetti; Nigam H Shah; Russ B Altman; Eric Horvitz Journal: J Am Med Inform Assoc Date: 2013-03-06 Impact factor: 4.497
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Authors: Srinivasan V Iyer; Rave Harpaz; Paea LePendu; Anna Bauer-Mehren; Nigam H Shah Journal: J Am Med Inform Assoc Date: 2013-10-24 Impact factor: 4.497