Standard-based comprehensive detection of adverse drug reaction signals from nursing statements and laboratory results in electronic health records.

ABSTRACT:

Objective

We propose 2 Medical Dictionary for Regulatory Activities-enabled pharmacovigilance algorithms, MetaLAB and MetaNurse, powered by a per-year meta-analysis technique and improved subject sampling strategy.

Matrials and methods

This study developed 2 novel algorithms, MetaLAB for laboratory abnormalities and MetaNurse for standard nursing statements, as significantly improved versions of our previous electronic health record (EHR)-based pharmacovigilance method, called CLEAR. Adverse drug reaction (ADR) signals from 117 laboratory abnormalities and 1357 standard nursing statements for all precautionary drugs ( n   = 101) were comprehensively detected and validated against SIDER (Side Effect Resource) by MetaLAB and MetaNurse against 11 817 and 76 457 drug-ADR pairs,

SUBMITTER: Lee S 

PROVIDER: S-EPMC7651894 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature