Validation of obesity-related diagnosis codes in claims data
DIABETES OBESITY & METABOLISM(2021)
摘要
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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关键词
database research, observational study
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