Liles, Elizabeth G, Irving, Stephanie A, Koppolu, Padma et al. · The Permanente journal · 2024 · DOI
This study looked at how often ME/CFS is diagnosed in a large health care system by checking electronic medical records from 2006 to 2017. Researchers found that while doctors used ME/CFS diagnosis codes for over 500 patients, only about 34% of the cases they reviewed actually matched the real diagnostic criteria for ME/CFS. This shows that relying only on diagnosis codes in medical records can give an inaccurate picture of how many people truly have ME/CFS.
Accurate diagnosis and prevalence estimates of ME/CFS are critical for understanding disease burden, allocating health care resources, and recognizing patient needs. This study highlights that many patients coded with ME/CFS may not actually meet diagnostic criteria, while the reverse problem—undiagnosed cases—may also exist. These findings underscore the importance of clinical expertise and proper diagnostic criteria application rather than reliance on coding alone.
This study does not prove how many people in the general population actually have ME/CFS, as it only examines patients within one health care system who received diagnosis codes. It does not identify undiagnosed ME/CFS cases in the community or explain why diagnostic accuracy was low (whether due to clinician knowledge gaps, documentation practices, or other factors). The study also cannot establish whether the increasing trend in diagnosis codes reflects true increasing incidence or simply improved coding practices.
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
Liles, Elizabeth G, Irving, Stephanie A, Koppolu, Padma, Crane, Bradley, Naleway, Allison L, Brooks, Neon B, et al. (2024). Classification Accuracy and Description of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome in an Integrated Health Care System, 2006-2017.. The Permanente journal. https://doi.org/10.7812/TPP/23.170
BibTeX
@article{mecfsatlas-liles-2024-classification-accuracy,
author = {Liles, Elizabeth G and Irving, Stephanie A and Koppolu, Padma and Crane, Bradley and Naleway, Allison L and Brooks, Neon B and Gee, Julianne and Unger, Elizabeth R and Henninger, Michelle L},
title = {Classification Accuracy and Description of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome in an Integrated Health Care System, 2006-2017.},
journal = {The Permanente journal},
year = {2024},
doi = {10.7812/TPP/23.170},
note = {PubMed: 38980763},
url = {https://www.mecfsatlas.com/evidence/liles-2024-classification-accuracy},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-30. https://www.mecfsatlas.com/evidence/liles-2024-classification-accuracy
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