Kan Hong, Swindle Jason P, Bae Jay, Dunn Julia P, Buysman Erin K, Gronroos Noelle N, Bengtson Lindsay, Chinthammit Chanadda, Ford Janet, Ahmad Nadia
Eli Lilly, 893 Delaware St, Indianapolis, IN, USA.
Evidera, 500 Totten Pond Rd, Waltham, MA, 02451, USA.
Obes Pillars. 2023 May 24;7:100072. doi: 10.1016/j.obpill.2023.100072. eCollection 2023 Sep.
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.
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.
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.
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.
本研究的目的是描述接受体重管理治疗的患者的人口统计学和临床特征，并调查这些特征与治疗方式之间的关联。
这是一项回顾性数据库研究，使用了2011年1月1日至2020年2月29日Optum研究数据库中商业保险和医疗保险优势计划D部分成员的医疗理赔、药房理赔和参保信息。2012年1月1日至2019年2月28日期间有体重管理治疗理赔的成年患者，根据接受的最高强度干预措施被分为不同队列。为了检验患者特征与接受的治疗方式之间的关联，进行了多项logit模型分析。
按照强度递增的队列包括生活方式干预（LSI，n = 67,679）、使用抗肥胖药物的减重药物治疗（WRRx）（n = 6,905）、减重手术（WRP，n = 1,172）和减重手术（WRS，n = 18,036）。接受WRS或WRP的患者中，约32.1%和16.6%在12个月基线期接受过LSI，只有0.6%和0.4%接受过长期抗肥胖药物治疗。在多项logit模型中，2型糖尿病患者（不包括WRRx队列）、呼吸系统疾病患者、心血管危险因素患者、疼痛性疾病患者和心理健康状况患者接受高强度干预治疗的几率高于LSI。男性患者、近期（2016 - 2019年）接受干预的患者或Charlson合并症评分为1（与评分为0相比）的患者接受高强度干预治疗的几率降低。
在本研究中，年龄、性别、体重指数、肥胖相关并发症和Charlson合并症评分似乎会影响所接受的体重管理治疗方式类型。本研究增进了对体重管理治疗利用情况的理解，并确定了通过适当使用不同治疗方式改善肥胖护理的差距和机会。
