Yudkin Joshua S, Allicock Marlyn A, Atem Folefac D, Galeener Carol A, Messiah Sarah E, Barlow Sarah E
The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Dallas, Texas, USA.
Center for Pediatric Population Health, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health, Dallas, Texas, USA.
Popul Health Manag. 2023 Oct 4;26(6):365-77. doi: 10.1089/pop.2023.0120.
Clinical weight management programs face low participation. The authors assessed whether using electronic health record (EHR) data can identify variation in referral, consent, and engagement in a pediatric overweight and obesity (OW/OB) intervention. Using Epic EHR data collected between August 2020 and April 2021, sociodemographic and clinical diagnostic data (ie, [ICD] codes from visit and problem list [PL]) were analyzed to determine their association with referral, consent, and engagement in an OW/OB intervention. Bivariate analyses and multivariable logistic regression modeling were performed, with Bayesian inclusion criterion score used for model selection. Compared with the 581 eligible patients, referred patients were more likely to be boys (60% vs. 54%, respectively; = 0.04) and have a higher %BMI (119% vs. 112%, respectively; < 0.01); consented patients were more likely to have a higher %BMI (120% vs. 112%, respectively; < 0.01) and speak Spanish (71% vs. 59%, respectively; = 0.02); and engaged patients were more likely to have a higher %BMI (117% vs. 112%, respectively; = 0.03) and speak Spanish (78% vs. 59%, respectively; < 0.01). The regression model without either ICD codes or PL diagnoses was the best fit across all outcomes, which were associated with baseline %BMI and health clinic location. Neither visit nor PL diagnoses helped to identify variation in referral, consent, and engagement in a pediatric OW/OB intervention, and their role in understanding participation in such interventions remains unclear. However, additional efforts are needed to refer and engage younger girls with less extreme cases of OW/OB, and to support non-Hispanic families to consent.
临床体重管理项目的参与率较低。作者评估了使用电子健康记录(EHR)数据是否能够识别儿科超重和肥胖(OW/OB)干预中在转诊、同意参与和实际参与方面的差异。利用2020年8月至2021年4月收集的Epic EHR数据,分析了社会人口统计学和临床诊断数据(即就诊时的[国际疾病分类(ICD)]编码和问题列表[PL]),以确定它们与OW/OB干预中转诊、同意参与和实际参与之间的关联。进行了双变量分析和多变量逻辑回归建模,并使用贝叶斯纳入标准评分进行模型选择。与581名符合条件的患者相比,被转诊的患者更有可能是男孩(分别为60%和54%;P = 0.04)且BMI百分比更高(分别为119%和112%;P < 0.01);同意参与的患者更有可能BMI百分比更高(分别为120%和112%;P < 0.01)且说西班牙语(分别为71%和59%;P = 0.02);实际参与的患者更有可能BMI百分比更高(分别为117%和112%;P = 0.03)且说西班牙语(分别为78%和59%;P < 0.01)。在所有结果中,不包含ICD编码或PL诊断的回归模型拟合效果最佳,这些结果与基线BMI百分比和健康诊所位置相关。就诊诊断和PL诊断均无助于识别儿科OW/OB干预中转诊、同意参与和实际参与方面的差异,它们在理解此类干预参与情况中的作用仍不明确。然而,需要做出更多努力来转诊并让患有不太严重OW/OB病例的年轻女孩参与进来,并支持非西班牙裔家庭同意参与。