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. 2023 May 24:7:100072.
doi: 10.1016/j.obpill.2023.100072. eCollection 2023 Sep.

Weight management treatment modalities in patients with overweight or obesity: A retrospective cohort study of administrative claims data

Hong Kan  1 , Jason P Swindle  2   3 , Jay Bae  1 , Julia P Dunn  1 , Erin K Buysman  4 , Noelle N Gronroos  4 , Lindsay Bengtson  5   3 , Chanadda Chinthammit  1 , Janet Ford  6   7 , Nadia Ahmad  1
Affiliations

Weight management treatment modalities in patients with overweight or obesity: A retrospective cohort study of administrative claims data

Hong Kan et al. Obes Pillars. .

Abstract

Background: The purpose of this study was to describe demographic and clinical characteristics among patients who have medical encounters for weight management treatments and to investigate the association of those characteristics with treatment modality.

Methods: This was a retrospective database study using medical claims, pharmacy claims, and enrollment information from commercial and Medicare Advantage with Part D members in the Optum Research Database from 01/01/2011-2/29/2020. Adult patients with a claim for a weight management treatment from 01/01/2012-2/28/2019 were categorized into cohorts according to the highest intensity intervention received. To examine the association between patient characteristics and treatment modality received, a multinomial logit model was performed.

Results: Cohorts by increasing intensity included lifestyle intervention (LSI, n = 67,679), weight reduction pharmacotherapy (WRRx) with an anti-obesity medication (AOM, n = 6,905), weight reduction procedure (WRP, n = 1,172), and weight reduction surgery (WRS, n = 18,036). Approximately 32.1% and 16.6% of patients who received WRS or WRP had an LSI during the 12-month baseline, and only 0.6% and 0.4% had treatment with long-term AOMs. In a multinomial logit model, patients with type 2 diabetes (not including WRRx cohort), respiratory disorders, cardiovascular risk factors, pain disorders, and mental health conditions had increased odds of treatment with higher intensity intervention versus LSI. Patients who were male, received an intervention more recently (2016-2019), or had a Charlson comorbidity score of 1 (compared to 0) had decreased odds of treatment with higher intensity interventions.

Conclusion: In this study, age, sex, body mass index, obesity-related complications, and Charlson comorbidity score appeared to influence the type of weight management treatment modality received. This study improves understanding of weight management treatment utilization and identifies gaps and opportunities to improve obesity care with the appropriate use of different treatment modalities.

Keywords: Anti-Obesity medications; Lifestyle intervention; Obesity; Overweight; Surgery; Weight reduction.

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Conflict of interest statement

H Kan, J Bae, J Dunn, C Chinthammit, and N Ahmad are employees of Eli Lilly and Company. J Ford was an employee of Eli Lilly and Company at the time the study was conducted and is a current employee of Agios Pharmaceuticals. J Swindle was an employee at Optum at the time the study was conducted and is a current employee of Evidera. E Buysman and N Gronroos are employees of Optum. L Bengtson was an employee of Optum at the time the study was conducted and is a current employee of Boehringer Ingelheim. Optum received funding from 10.13039/100004312Eli Lilly and Company to conduct the study.

Figures

Fig. 1
Fig. 1
Top obesity-related complications 1Includes dyslipidemia and hypertension; 2Includes asthma and sleep apnea; 3Includes osteoarthritis and back pain; 4Includes depression and anxiety; 5Includes atherosclerotic cardiovascular disease, cerebrovascular disease, ischemic heart disease, and peripheral arterial disease; 6Includes hypogonadism, polycystic ovarian syndrome, and female infertility; 7Includes atrial fibrillation/flutter and heart failure; 8Includes rheumatoid arthritis, ankylosing spondylitis, enteropathic arthropathy, and psoriatic arthritis ASCVD, atherosclerotic cardiovascular disease; CKD, chronic kidney disease; LSI, lifestyle intervention; NAFLD, nonalcoholic fatty liver disease; NASH, nonalcoholic steatohepatitis; WRP, weight reduction procedure, WRRx, weight reduction pharmacotherapy; WRS, weight reduction surgery. Fig. 2. Baseline healthcare resource utilization.
Fig. 2
Fig. 2
Healthcare resource utilization 2a. Mean monthly ambulatory visits. 2b. Mean monthly emergency room visit. 2c. Mean monthly inpatient stays. 1Index date was the first claim for the greatest intensity weight management intervention received, LSI, lifestyle intervention; WRP, weight reduction procedure; WRRx, weight reduction pharmacotherapy; WRS, weight reduction surgery.
Fig. 3
Fig. 3
Multinomial logit model of the association between patient characteristics and treatment modality received1, 3a. WRRx versus LSI, 3b. WRP versus LSI, 3c. WRS versus LSI, 1All overall p-values for each variable were significant across the models, with the exception of other cardiac disorders and autoimmune/inflammatory arthritis. ASCVD, atherosclerotic cardiovascular disease; ER, emergency room; T2DM, type 2 diabetes mellitus.
Fig. 3
Fig. 3
Multinomial logit model of the association between patient characteristics and treatment modality received1, 3a. WRRx versus LSI, 3b. WRP versus LSI, 3c. WRS versus LSI, 1All overall p-values for each variable were significant across the models, with the exception of other cardiac disorders and autoimmune/inflammatory arthritis. ASCVD, atherosclerotic cardiovascular disease; ER, emergency room; T2DM, type 2 diabetes mellitus.
Fig. 3
Fig. 3
Multinomial logit model of the association between patient characteristics and treatment modality received1, 3a. WRRx versus LSI, 3b. WRP versus LSI, 3c. WRS versus LSI, 1All overall p-values for each variable were significant across the models, with the exception of other cardiac disorders and autoimmune/inflammatory arthritis. ASCVD, atherosclerotic cardiovascular disease; ER, emergency room; T2DM, type 2 diabetes mellitus.
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