Secondary Data for Pharmacoepidemiological Research - Making the Best of It!

Abstract

Studies using secondary data such as health care claims data are often faced with methodological challenges due to the time-dependence of key quantities or unmeasured confounding. In the present paper, we discuss approaches to avoid or suitably address various sources of potential bias. In particular, we illustrate the target trial principle, marginal structural models, and instrumental variables with examples from the "GePaRD" database. Finally, we discuss the strengths and limitations of record linkage which can sometimes be used to supply missing information.