Details
The aim of this project is to demonstrate the feasibility and efficiency of developing and validating of a claims-based health outcome interest (HOI) algorithm using machine learning classification techniques applied to a linked claims-electronic medical records (EMR) database. This project has the potential to improve the electronic phenotype development and validation process for outcomes that can be detected via standardized information in an EMR to accelerate validation of claims-based signatures.
Additional Information
Contributors
Jenna Wong, PhD, MSc; Darren Toh, ScD; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA
Teresa B. Gibson, PhD, MS, MA; IBM Watson Health, Ann Arbor, MI
Michael Nguyen, MD; Center for Drug Evaluation and Research, FDA, Silver Spring, MD
James Williams, MBA; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA
Emma Mollenhauer, BS; David Lewandowski; Timothy Burrell, MD, MBA; Shannon Harrer; IBM Watson Health, Ann Arbor, MI
Sai Dharmarajan, PhD, MS; Wei Hua, PhD, MHS, MS; Rita Ouellet-Hellstrom, PhD, MPH; Elande Baro, PhD, MS; Robert Ball, MD, MPh; Center for Drug Evaluation and Research, FDA, Silver Spring, MD