Electronic healthcare databases for active drug safety surveillance: is there enough leverage?

TLDR

The study aims to estimate how many and which drugs can be monitored for safety using electronic healthcare databases and to show that expanding database size and follow‑up time can increase surveillance leverage. The authors used data from eight European administrative claims and medical record databases in a cohort design to estimate the drug exposure needed for signal detection across relative risks for six adverse events, and simulated how increasing database size would affect surveillance capabilities. Analysis of 19.6 million individuals and 2,289 drugs showed that for a common event like acute myocardial infarction, 531 drugs (23 %) could be studied for a RR of 2, whereas for a rare event like rhabdomyolysis only 19 drugs (1 %) could be examined, indicating that active surveillance is feasible but limited for rare outcomes and infrequently used drugs. © 2012 John Wiley & Sons, Ltd.

Abstract

ABSTRACT 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 19 647 452 individuals (59 594 132 person‐years follow‐up) who used 2289 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.