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The Impact of Misclassification of Obesity Coding in Administrative Claims Data on Negative Health Outcomes

*Heather Watson, Exponent, Inc.  
Edmund Lau, Exponent, Inc. 

Keywords: administrative claims data, obesity, misclassification

Administrative claims data are important for the analysis of health outcomes. Obesity is a risk factor that can greatly influence a variety of health outcomes, yet the data validity of obesity in in administrative claims data may not be adequate. A patient’s BMI can be coded generally with ICD-9-CM 278.x or more specifically with V85.x. When comparing obese patient surgery outcomes to normal weight patient outcomes, misclassification of obesity will occur as any claim without an obesity code is assumed to be for a patient of normal weight. However, obese patients may not be coded and are grouped in the normal weight population for analysis. This study investigates the application of multiple statistical methods, such as propensity scores to estimate the probability of coding and random group re-assignment, to examine the bias and influence of misclassification rates on the risk of negative health outcomes (i.e., death, readmission, infection, etc.) within 90 days of hip surgery using Medicare data.