Examination of Weight-Related Coding Practices in Administrative Claims: Implications for Future Analyses


Brady B1, Palmer L2
1Merative, Laurel, MD, USA, 2Merative, Ann Arbor, MI, USA

OBJECTIVES: Although availability of real-world clinical data has been increasing over the last decades, closed system administrative claim databases remain some of the largest and most comprehensive data sources available. This study examined use of different weight-related diagnosis codes from 2016-2022 to assess whether coding practices have evolved with increasing focus on the global obesity epidemic.

METHODS: Annual cohorts of adult patients with continuous eligibility and ≥1 office visit were identified in the Merative MarketScan Commercial and Medicare Database in the 2016, 2018, 2020, and 2022 calendar years. Presence and type (either BMI or weight-class [underweight, normal, overweight, obese] based) of weight-related diagnosis codes were investigated in the annual samples.

RESULTS: Each annual cohort included approximately 9-15 million patients. The proportion of patients with ≥1 weight-related code increased from 20.4% to 29.8% over the study period; patients with ≥1 weight-related code had a mean±SD of 6±9 to 7±11 weight-related diagnosis codes annually. There were limited changes in distributions across weight classes, with >60% with ≥1 obese code, 26-29% with ≥1 overweight code, 10-13% with ≥1 normal weight code, and <3% with ≥1 underweight code annually. Examination of reporting by code type indicated that most patients were coded using either BMI codes or weight-class codes, with only 17.6% to 25.6% of patients with both code types. Distributions of code type varied across weight classes with obese patients more likely than overweight or underweight patients to have both BMI and weight class codes reported (there is no normal weight-class code).

CONCLUSIONS: Despite the lack of direct clinical data, such as body mass index (BMI), administrative claims can be used to identify weight-related outcomes. However, given variability in code availability as well as coding practices across patients, researchers should take care in defining methodology to identify different weight classes.

Conference/Value in Health Info

2024-05, ISPOR 2024, Atlanta, GA, USA

Value in Health, Volume 27, Issue 6, S1 (June 2024)




Clinical Outcomes, Epidemiology & Public Health, Study Approaches

Topic Subcategory

Clinical Outcomes Assessment, Disease Classification & Coding


Diabetes/Endocrine/Metabolic Disorders (including obesity), No Additional Disease & Conditions/Specialized Treatment Areas

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