Validation of obesity‐related diagnosis codes in claims data
Open accessAbstract
Aim: To determine whether body mass index (BMI) can be accurately identified in epidemiological studies using claims databases. Materials and methods: Using the Mass General Brigham Research Patient Data Repository‐Medicare‐linked database, we identified a cohort of patients with a BMI measurement for the periods January 1 to June 31, 2014 or January 1 to June 31, 2016, to capture both the International Classification of Disease (ICD)‐9 and ICD‐10 eras. Patients were divided into two groups, with or without an obesity‐related ICD code in the 6 months before or after the BMI measurement date. We created two binary measures, first for composite overweight, obesity, or severe obesity (BMI ≥25 kg/m 2 ), and second for obesity or severe obesity (BMI ≥30 kg/m 2 ). We calculated accuracy measures (sensitivity, specificity, positive predictive value [PPV] and negative predictive value [NPV]) for each obesity category for the overall cohort, and stratified by type 2 diabetes and ICD‐code era. Results: The cohort included 73 644 patients with a BMI measurement in 2014 or 2016, of whom 16 280 had an obesity‐related ICD code. The specificity of obesity‐related ICD codes (ICD‐9 and ICD‐10) was 99.7% for underweight/normal weight, 97.4% for overweight, 99.7% for obese and 98.9% for severely obese. For binary categories capturing BMI ≥25 kg/m 2 and BMI ≥30 kg/m 2 , specificity was 97.0% and 98.2%, and PPV was 86.9% and 97.3%. Sensitivity was low overall (<40%). Codes for patients with type 2 diabetes and codes in the ICD‐10 era had higher sensitivity, PPV and NPV. Conclusion: Obesity‐related ICD codes can accurately identify patients with obesity in epidemiological studies using claims databases.
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Adherence was measured using the PDC method endorsed by the Pharmacy Quality Alliance and used by CMS in Part C & D Star Ratings.
“Adherence was measured using the proportion of days covered (PDC) method endorsed by the Pharmacy Quality Alliance and used by Centers for Medicare and Medicaid Services in their Part C & D Star Ratings, with 3 differences:”
From Real-world persistence and adherence to glucagon-like peptide-1 receptor agonists among obese commercially insured adults without diabetes. (2024) · cites this paper as [23]
The Materials and Methods passages describe linking Medicare claims to BMI measurements and validating obesity diagnosis codes, not measuring medication adherence. Searches for PDC, the Pharmacy Quality Alliance, CMS Star Ratings, and medication-adherence measurement found no passage addressing the claim. (LLM, conf=0.76)
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- Authors
- Suissa, K., Schneeweiss, S., Lin, K. J., Brill, G., Kim, S. C., & Patorno, E.
- Affiliations
- Brigham and Women's Hospital (US)
- Corresponding author
- Patorno, Elisabetta
- Venue
- Diabetes, Obesity and Metabolism
- Publisher
- Wiley
- Published
- 2021-08-18
- Volume
- 23
- Issue
- 12
- Pages
- 2623-2631
- ISSN
- 1462-8902 (ISSN-L)
- 1463-1326
- PMC
- PMC8578343
- OpenAlex
- W3190247615
- Cited by
- 89
- References
- 23
- Citations by year
- 2026: 33 · 2025: 22 · 2024: 14 · 2023: 10 · 2022: 9 · 2021: 1
- FWCI
- 7.41
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Diabetes Obesity and Metabolism (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (K08AG055670)
- National Institutes of Health (K24‐AR078959)
- Bristol-Myers Squibb
- Boehringer Ingelheim
- Topics
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- obesity, body mass index, ICD-9, ICD-10, diagnosis codes, claims data, code validation, type 2 diabetes, morbid obesity, overweight, sensitivity and specificity
- MeSH terms
- Aged, Diabetes Mellitus, Type 2, Medicare, Humans, Obesity, United States, Body Mass Index, Databases, Factual, International Classification of Diseases
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