A method for controlling complex confounding effects in the detection of adverse drug reactions using electronic health records.

ABSTRACT:

Objective

Electronic health records (EHRs) contain information to detect adverse drug reactions (ADRs), as they contain comprehensive clinical information. A major challenge of using comprehensive information involves confounding. We propose a novel data-driven method to identify ADR signals accurately by adjusting for confounders.

Materials and methods

We focused on two serious ADRs, rhabdomyolysis and pancreatitis, and used information in 264,155 unique patient records. We identified an ADR using established criteria, selected potential confounders, and then used penalized logistic regressions to estimate confounder-adjusted ADR associations. A reference standard was created to evaluate and compare the precision of the proposed method and four others.

Results

Precis

SUBMITTER: Li Y 

PROVIDER: S-EPMC3932454 | biostudies-literature | 2014 Mar-Apr

REPOSITORIES: biostudies-literature