meps

This repository provides example code for loading and analyzing data from AHRQ's Medical Expenditure Panel Survey (MEPS). More information about the survey and access to public use data files is available on our website

TweetyourMEP

More realistic synthetic medication data.

Code for creating the interactive MEPS summary tables

Python package to retrieve MEPs voting data from Votewatch.eu. Check what your MEPs are doing in a few simple commands.

MEPS Household Component Annual Consolidated Data Files

Reading Spike2 files for electromiography and preprocessing them

Extract Medical Expenditure Panel Survey's Household Consolidated Data Files using Stata

MEPS Two-Year Longitudinal Files

matlab analysis script of the results from my paper on vombined TMS and EMG

Leakage-safe longitudinal asthma risk analytics using Synthea, with an independent MEPS benchmark

Prospective MEPS analysis of next-year medical cost and prescription out-of-pocket burden.

Incremental annual healthcare cost of diagnosed diabetes: survey-weighted two-part model (logistic + Gamma GLM) on MEPS 2023, with recycled predictions and a Rao-Wu bootstrap CI.

MEPS Person Round Plan Public Use Files

Python-based statistical modeling of the MEPS dataset to investigate healthcare access and financial burdens among cancer patients.

Decision-science analysis of 22,431 MEPS records using predictive modeling, patient-burden segmentation, and tested healthcare policy simulations.

Who gets picked for care management when the risk model predicts cost instead of health. Built on AHRQ MEPS survey panels from 2016 to 2023.

Reproducible MEPS Panel 24 study evaluating incremental predictive value beyond three-year historical ED utilization for next-year ED use.

Survey-weighted MEPS 2024 healthcare expenditure, cost concentration, utilization, payment source, and priority review analysis using Python, DuckDB SQL, and Power BI.