Journal article
Validation of body mass index (BMI)-related ICD-9-CM and ICD-10-CM administrative diagnosis codes recorded in US claims data
Pharmacoepidemiology and drug safety, Vol.27(10), pp.1092-1100
10/2018
DOI: 10.1002/pds.4617
PMID: 30003617
Abstract
Purpose: To quantify the sensitivity and positive predictive value (PPV) of body mass index (BMI)-related ICD-9-CM and ICD-10-CM diagnosis codes in claims data. Methods: De-identified electronic health record (EHR) and claims data were obtained from the Optum Integrated Claims-Clinical Database for cross-sections of commercial and Medicare Advantage health plan members age ≥ 20 years in 2013, 2014, and 2016. In each calendar year, health plan members' BMI as coded in the insurance claims data (error-prone measure) was compared with their BMI as recorded in the EHR (gold standard) to estimate the sensitivity and PPV of BMI-related ICD-9-CM and ICD-10-CM diagnosis codes. The unit of analysis was the person-year. Results: The study sample included 746 763 distinct health plan members who contributed 1 116 283 eligible person-years (median age 56 years; 57% female; 65% commercially insured and 35% with Medicare Advantage). BMI-related diagnoses were coded for 14.6%. The sensitivity of BMI-related diagnoses codes for the detection of underweight, normal weight, overweight, and obesity was 10.1%, 3.7%, 6.0%, and 25.2%, and the PPV was 49.0% for underweight, 89.6% for normal weight, 73.4% for overweight, and 92.4% for obesity, respectively. The sensitivity of BMI-related diagnosis codes was higher in the ICD-10-CM era relative to the ICD-9-CM era. Conclusions: The PPV of BMI-related diagnosis codes for normal weight, overweight, and obesity was high (>70%) but the sensitivity was low (<30%). BMI-related diagnoses were more likely to be coded in patients with class II or III obesity (BMI ≥35 kg/m2), and in 2016 relative to 2013 or 2014.
Details
- Title: Subtitle
- Validation of body mass index (BMI)-related ICD-9-CM and ICD-10-CM administrative diagnosis codes recorded in US claims data
- Creators
- Eric M. Ammann - Johnson & JohnsonIftekhar Kalsekar - Johnson & JohnsonAndrew Yoo - Johnson & JohnsonStephen S. Johnston
- Resource Type
- Journal article
- Publication Details
- Pharmacoepidemiology and drug safety, Vol.27(10), pp.1092-1100
- DOI
- 10.1002/pds.4617
- PMID
- 30003617
- ISSN
- 1053-8569
- eISSN
- 1099-1557
- Grant note
- DOI: 10.13039/100004331, name: Johnson and Johnson
- Language
- English
- Date published
- 10/2018
- Academic Unit
- Epidemiology
- Record Identifier
- 9984364439202771
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