Validity of Hospital Codes for Obesity in Ontario, Canada

Obesity has a significant impact on population health and health care. Administrative databases may be a useful tool to study obesity at a population level. In this work, we aimed to determine the validity of hospital codes for obesity in Ontario, Canada.

Using linked health-care databases (ICES), we conducted a validation study in adults ≥18 years of age who had their height and weight recorded during a hospitalization in southwestern Ontario. We considered a body mass index ≥30 kg/m² as our gold standard definition for obesity. We then examined the validity of 2 International Classification of Diseases---10th revision (ICD-10) coding algorithms for obesity (Algorithm 1, ICD-10 E66.X; and Algorithm 2, ICD-10 E65.X-68.X). As additional analyses, we examined the validity of algorithms in different obesity classes (i.e. obese classes 1, 2 and 3), and in patients with diagnosed diabetes and hypertension.

There were 34,588 patients included in our study (mean age, 62 years; 47% female). Algorithm 1 performed best, with a sensitivity, specificity, positive predictive value and negative predictive value of 8.8%, 99.8%, 95.4% and 65.1%, respectively. The sensitivity of this algorithm was highest in patients with obesity class 3 (27.4%) and in those with diagnosed diabetes.

Hospital codes for obesity have a high positive predictive value and specificity. These codes can be used to build and study cohorts of patients with obesity in administrative database studies. However, given their limited sensitivity, administrative codes provide inaccurate incidence and prevalence estimates.