Alternative Methods for Defining Osteoarthritis and the Impact on Estimating Prevalence in a US Population-Based Survey
- PMID: 26315529
- PMCID: PMC4769961
- DOI: 10.1002/acr.22721
Alternative Methods for Defining Osteoarthritis and the Impact on Estimating Prevalence in a US Population-Based Survey
Abstract
Objective: Provide a contemporary estimate of osteoarthritis (OA) by comparing the accuracy and prevalence of alternative definitions of OA.
Methods: The Medical Expenditure Panel Survey (MEPS) household component (HC) records respondent-reported medical conditions as open-ended responses; professional coders translate these responses into International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes for the medical conditions files. Using these codes and other data from the MEPS-HC medical conditions files, we constructed 3 case definitions of OA and assessed them against medical provider diagnoses of ICD-9-CM 715 (osteoarthrosis and allied disorders) in a MEPS subsample. The 3 definitions were 1) strict = ICD-9-CM 715; 2) expanded = ICD-9-CM 715, 716 (other and unspecified arthropathies) OR 719 (other and unspecified disorders of joint); and 3) probable = strict OR expanded + respondent-reported prior diagnosis of OA or other arthritis excluding rheumatoid arthritis.
Results: Sensitivity and specificity of the 3 definitions, respectively, were 34.6% and 97.5% for strict, 73.8% and 90.5% for expanded, and 62.9% and 93.5% for probable.
Conclusion: The strict definition for OA (ICD-9-CM 715) excludes many individuals with OA. The probable definition of OA has the optimal combination of sensitivity and specificity relative to the 2 other MEPS-based definitions and yields a national annual estimate of 30.8 million adults with OA (13.4% of US adult population) for 2008-2011.
© 2016, American College of Rheumatology.
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Comment in
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Defining the Burden of Osteoarthritis in Population-Based Surveys.Arthritis Care Res (Hoboken). 2016 May;68(5):571-3. doi: 10.1002/acr.22716. Arthritis Care Res (Hoboken). 2016. PMID: 26314807 No abstract available.
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