Developing and Evaluating a Machine-Learning Opioid Prediction & Risk-Stratification E-Platform (DEMONSTRATE)

PI: Wei-Hsuan Jenny Lo-Ciganic, PhD, MS, MSPharm
Funding Source: NIH/NIDA
NCT06810076
July 2021 - April 2026

The proposed study aims to harness advanced natural language processing and longitudinal neural network approaches to build on our previously developed machine-learning prediction algorithms to identify patients at risk for opioid overdose or opioid use disorder. We will develop the prediction tool using all-payer electronic health records (EHR), Medicaid claims, and Medicaid claims linked with EHR data from the One Florida Clinical Research Consortium and translate the risk prediction algorithms into a clinical decision support platform integrated into the EHR system to identify patients at high risk of overdose and opioid use disorder. This innovative and integrated platform will better guide clinical providers and health care systems for improving safety of opioid prescribing in clinical practice, and prevent opioid-associated adverse outcomes.

Read published results from this work

Protocol for a Single-Arm Pilot Clinical Trial: Developing and Evaluating a Machine Learning Opioid Prediction & Risk-Stratification E-Platform (DEMONSTRATE)
Je-Won J. Hong, Debbie L. Wilson, Khoa Nguyen, Walid F. Gellad, Julie Diiulio, Laura Militello, Shunhua Yan, Christopher A. Harle, Danielle Nelson, Eric I. Rosenberg, Siegfried Schmidt, Chung-Chou Ho Chang, Gerald Cochran, Yonghui Wu, Stephanie A. S. Staras, Courtney Kuza, and Wei-Hsuan Lo-Ciganic
Journal of Clinical Medicine, November 30, 2025

Using human factors methods to mitigate bias in artificial intelligence-based clinical decision support
Laura G Militello, MA, Julie Diiulio, MS, Debbie L Wilson, PhD, Khoa A Nguyen, PharmD, Christopher A Harle, PhD, Walid Gellad, MD, MPHWei-Hsuan Lo-Ciganic, PhD
JAMIA, November 21, 2024

Design and development of a machine-learning-driven opioid overdose risk prediction tool integrated in electronic health records in primary care settings
Khoa Nguyen, Debbie L. Wilson, Julie Diiulio, Bradley Hall, Laura Militello, Walid F. Gellad, Christopher A. Harle, Motomori Lewis, Siegfried Schmidt, Eric I. Rosenberg, Danielle Nelson, Xing He, Yonghui Wu, Jiang Bian, Stephanie A. S. Staras, Adam J. Gordon, Jerry Cochran, Courtney Kuza, Seonkyeong Yang, & Weihsuan Lo-Ciganic
Bioelectronic Medicine, October 18, 2024