Chen, Robert, Ho, Joyce C, Lin, Jin-Mann S · BMC medical research methodology · 2020 · DOI
Researchers developed a computer program to automatically read through medical records and extract information about what medications ME/CFS patients are taking and why they're taking them. Instead of having someone manually review thousands of medication entries (which is slow and error-prone), their automated system condensed over 1,200 different medication names into 89 standard categories and organized reasons for use into 65 categories. This tool could help future research studies more quickly analyze medication patterns in ME/CFS patients.
ME/CFS research requires analyzing complex medication data from large patient populations, but manual data extraction is prohibitively time-consuming and error-prone. This automation framework enables researchers to efficiently process medication information at scale, facilitating future investigations into medication use patterns and treatment approaches in ME/CFS. Improved data extraction tools accelerate the pace of clinical research and can support machine learning studies aimed at understanding disease mechanisms and treatment effectiveness.
This study does not evaluate the effectiveness or safety of any medications for ME/CFS, nor does it establish which medications patients should use. It is purely a methodological paper demonstrating data processing techniques—it provides no clinical outcomes data or treatment recommendations. The framework's applicability to other diseases or datasets may vary depending on data quality and formatting differences.
About the PEM badge: “PEM required” means post-exertional malaise was an explicit required diagnostic criterion for participant inclusion in this study — not that PEM was studied, observed, or discussed. Studies using criteria that do not require PEM (e.g. Fukuda, Oxford) are tagged “PEM not required”. How the atlas works →
The first block is for the primary paper and is the citation you should use in research work. The atlas-snapshot line only applies if you are specifically referring to this atlas’s reading of the paper on the date shown.
Primary citation
Chen, Robert, Ho, Joyce C, & Lin, Jin-Mann S (2020). Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples.. BMC medical research methodology. https://doi.org/10.1186/s12874-020-01131-7
BibTeX
@article{mecfsatlas-chen-2020-extracting-medication,
author = {Chen, Robert and Ho, Joyce C and Lin, Jin-Mann S},
title = {Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples.},
journal = {BMC medical research methodology},
year = {2020},
doi = {10.1186/s12874-020-01131-7},
note = {PubMed: 33059588},
url = {https://www.mecfsatlas.com/evidence/chen-2020-extracting-medication},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-30. https://www.mecfsatlas.com/evidence/chen-2020-extracting-medication
Contribute
Private, reviewed by a human. Not a public comment thread.