Big Data Analytics of Medical Claims Data for Early Prediction of Drug Resistant Epilepsy

Abstract

We analyzed longitudinal claims data from 1,376,756 patients with epilepsy from 2006 to 2015 to determine whether information in medical and pharmacy claims data can predict, at the time of prescribing the first antiepileptic drug (AED), which patients with epilepsy will become resistant to AEDs. Our models created from large claims data using machine learning methods can accurately predict which patients with epilepsy will become drug resistant at the time of the first AED prescription. In addition, our model predicts drug resistance on average 2.26 years earlier than waiting for 2 AED failures as the standard clinical definition of drug resistance.