JSM 2015 Online Program

Online Program Home
My Program

Abstract Details

Activity Number: 666
Type: Invited
Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
Sponsor: WNAR
Abstract #314244
Title: Perils and Solutions for Comparative Effectiveness Research in Massive Observational Databases
Author(s): Marc A. Suchard*
Companies: UCLA
Keywords: Big Data ; Observational healthcare ; Statistical computing ; Pharmacoepidemiology ; Regularized regression ; R package

Massive longitudinal healthcare databases enable development of surveillance solutions to identify and evaluate drug risk at unprecedented scale. Recent comparative drug safety analyses using administrative claims data continue to rely on unadjusted incidence rate ratios. We develop a large-scale regularized regression framework to control for drug exposure-assignment and estimate adjusted incidence rate ratios at scale. Our framework uses advancing computing technology for Big Data to fit statistical models involving 1,000,000s of patients. In our framework, we include all clinical information available about patients up to their time of indication diagnosis and treatment exposure, such as all possible drug prescriptions, medical conditions, procedures and other demographics. The number of covariates stands in the 10,000s, regularization helps us avoid overfitting and algorithmic optimization provides estimates in real-time. We apply our method to examine incidence rates of in-patient gastrointestinal bleeding among atrial fibrillation patients taking dabigatran or warfarin in a database that covers over 227M patient-years.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program

For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home