An electronic health record driven algorithm to identify incident antidepressant medication users.

ABSTRACT:

Objective

We validated an algorithm designed to identify new or prevalent users of antidepressant medications via population-based drug prescription records.

Patients and methods

We obtained population-based drug prescription records for the entire Olmsted County, Minnesota, population from 2011 to 2012 (N=149,629) using the existing electronic medical records linkage infrastructure of the Rochester Epidemiology Project (REP). We selected electronically a random sample of 200 new antidepressant users stratified by age and sex. The algorithm required the exclusion of antidepressant use in the 6 months preceding the date of the first qualifying antidepressant prescription (index date). Medical records were manually reviewed and adjudicated to calculate the positive predictive

SUBMITTER: Bobo WV 

PROVIDER: S-EPMC4147111 | biostudies-literature | 2014 Sep-Oct

REPOSITORIES: biostudies-literature