Opioid Cost Prediction Using PBM and SDOH: County-Level Machine Learning Framework, United States 2013–2023

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Authors: s, mohit
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Abstract

This repository contains all data, code, and model artifacts for the study "Development and Feasibility Evaluation of a County-Level Machine-Learning Framework for Opioid Cost Surveillance Using Medicare Part D and Social Determinants of Health Data, United States, 2013–2023." It includes feature-engineered panel data (approximately 3,100 U.S. counties, 2013–2023), Random Forest model code, SHAP analysis scripts, counterfactual simulation outputs, and a README with full replication instructions. All data sources are publicly available from CMS, County Health Rankings, and the U.S. Census Bureau. Version 4 updated April 2026.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 May 2026
Document type
Dataset