1. Positive predictive value between medical-chart body-mass-index category and obesity versus codes in a claims-data warehouse.
- Author
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Caplan EO, Kamble PS, Harvey RA, Smolarz BG, Renda A, Bouchard JR, and Huang JC
- Subjects
- Adult, Aged, Aged, 80 and over, Body Weight, Data Warehousing, Female, Humans, Male, Medical Records, Medicare Part C, Middle Aged, Retrospective Studies, United States, Body Mass Index, Obesity epidemiology, Overweight epidemiology
- Abstract
Objective: To evaluate the positive predictive value of claims-based V85 codes for identifying individuals with varying degrees of BMI relative to their measured BMI obtained from medical record abstraction., Methods: This was a retrospective validation study utilizing administrative claims and medical chart data from 1 January 2009 to 31 August 2015. Randomly selected samples of patients enrolled in a Medicare Advantage Prescription Drug (MAPD) or commercial health plan and with a V85 claim were identified. The claims-based BMI category (underweight, normal weight, overweight, obese class I-III) was determined via corresponding V85 codes and compared to the BMI category derived from chart abstracted height, weight and/or BMI. The positive predictive values (PPVs) of the claims-based BMI categories were calculated with the corresponding 95% confidence intervals (CIs)., Results: The overall PPVs (95% CIs) in the MAPD and commercial samples were 90.3% (86.3%-94.4%) and 91.1% (87.3%-94.9%), respectively. In each BMI category, the PPVs (95% CIs) for the MAPD and commercial samples, respectively, were: underweight, 71.0% (55.0%-87.0%) and 75.9% (60.3%-91.4%); normal, 93.8% (85.4%-100%) and 87.8% (77.8%-97.8%); overweight, 97.4% (92.5%-100%) and 93.5% (84.9%-100%); obese class I, 96.9 (90.9%-100%) and 97.2% (91.9%-100%); obese class II, 97.0% (91.1%-100%) and 93.0% (85.4%-100%); and obese class III, 85.0% (73.3%-96.1%) and 97.1% (91.4%-100%)., Conclusions: BMI categories derived from administrative claims, when available, can be used successfully particularly in the context of obesity research.
- Published
- 2018
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