Search

Objective: To evaluate obesity-related costs and body mass index (BMI) as a cost predictor among privately insured employees by industry., Methods: Individuals with/without obesity were identified using the Optum Health Reporting and Insights employer claims database (January, 2010 to March, 2017). Direct/indirect costs were reported per-patient-per-year (PPPY). Multivariate models were used to estimate the association between obesity and high costs (more than or equal to 80th percentile) by industry., Results: Overall (N = 86,221), direct and absenteeism/disability cost differences between class I obesity (BMI 30.0 to 34.9) and reference were $1,775 and $617 PPPY, respectively (P < 0.05). Among employees with obesity (BMI more than or equal to 30), highest total costs were observed in the government/education/religious services, food/entertainment services, and technology industries. Class I obesity increased the odds of high costs (more than or equal to 80th percentile) within each industry (odds ratios vs reference = 1.09-5.17)., Conclusions: Obesity (BMI more than or equal to 30) was associated with high costs among employees of major US industries.

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.