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Related Experiment Video

Updated: Feb 24, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

A Treatment Selection Model for Opioid Use Disorder Using Electronic Health Record and ZIP-Level Data.

Leigh Anne Tang^1,2, Kristopher A Kast³, Colin G Walsh³

¹Indiana University, Indianapolis, IN.

AMIA ... Annual Symposium Proceedings. AMIA Symposium

|February 23, 2026

Summary

This summary is machine-generated.

This study created a predictive model to help choose opioid use disorder (OUD) treatments. Electronic health record data alone proved most effective, consistently favoring buprenorphine over methadone.

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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

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Area of Science:

Data Science
Pharmacology
Public Health

Background:

Opioid use disorder (OUD) treatments like buprenorphine and methadone are underutilized.
Specialist-led care decisions impact treatment accessibility.

Purpose of the Study:

Develop a predictive model to guide OUD treatment selection.
Optimize medication choice for improved patient outcomes.

Main Methods:

Constructed generalized linear regression, random forest, gradient boosted machines, and deep learning models.
Utilized electronic health record (EHR) and ZIP-level data with early and late fusion.
Defined treatment response as absence of adverse outcomes during hospitalization and 90 days post-discharge.

Main Results:

EHR-only models outperformed ZIP-only models.
ZIP-level data did not significantly enhance EHR-only model performance.
Models consistently recommended buprenorphine over methadone for OUD treatment.

Conclusions:

Predictive modeling using EHR data shows promise for OUD treatment selection.
Further research needed to incorporate social and external factors into OUD treatment models.