Using aggregated, de-identified electronic health record data for multivariate pharmacosurveillance: a case study of azathioprine.

ABSTRACT:

Objective

To demonstrate the use of aggregated and de-identified electronic health record (EHR) data for multivariate post-marketing pharmacosurveillance in a case study of azathioprine (AZA).

Methods

Using aggregated, standardized, normalized, and de-identified, population-level data from the Explore platform (Explorys, Inc.) we searched over 10 million individuals, of which 14,580 were prescribed AZA based on RxNorm drug orders. Based on logical observation identifiers names and codes (LOINC) and vital sign data, we examined the following side effects: anemia, cell lysis, fever, hepatotoxicity, hypertension, nephrotoxicity, neutropenia, and neutrophilia. Patients prescribed AZA were compared to patients prescribed one of 11 other anti-rheumatologic drugs to determine the r

SUBMITTER: Patel VN 

PROVIDER: S-EPMC4002671 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature