Funk Luke M, Shan Ying, Voils Corrine I, Kloke John, Hanrahan Lawrence P
*William S. Middleton VA Hospital †Department of Surgery, Wisconsin Surgical Outcomes Research Program (WiSOR), University of Wisconsin-Madison, Madison, WI ‡Center for Health Services Research in Primary Care, Veterans Affairs Medical Center §Department of Medicine, Duke University Medical Center, Durham, NC Departments of ∥Biostatistics and Medical Informatics ¶Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI.
Med Care. 2017 Jun;55(6):598-605. doi: 10.1097/MLR.0000000000000693.
Estimating population-level obesity rates is important for informing policy and targeting treatment. The current gold standard for obesity measurement in the United States-the National Health and Nutrition Examination Survey (NHANES)-samples <0.1% of the population and does not target state-level or health system-level measurement.
To assess the feasibility of using body mass index (BMI) data from the electronic health record (EHR) to assess rates of overweight and obesity and compare these rates to national NHANES estimates.
Using outpatient data from 42 clinics, we studied 388,762 patients in a large health system with at least 1 primary care visit in 2011-2012.
We compared crude and adjusted overweight and obesity rates by age category and ethnicity (white, black, Hispanic, Other) between EHR and NHANES participants. Adjusted overweight (BMI≥25) and obesity rates were calculated by a 2-step process. Step 1 accounted for missing BMI data using inverse probability weighting, whereas step 2 included a poststratification correction to adjust the EHR population to a nationally representative sample.
Adjusted rates of obesity (BMI≥30) for EHR patients were 37.3% [95% confidence interval (95% CI), 37.1-37.5] compared with 35.1% (95% CI, 32.3-38.1) for NHANES patients. Among the 16 different obesity class, ethnicity, and sex strata that were compared between EHR and NHANES patients, 14 (87.5%) contained similar obesity estimates (ie, overlapping 95% CIs).
EHRs may be an ideal tool for identifying and targeting patients with obesity for implementation of public health and/or individual level interventions.
估算人群肥胖率对于制定政策和确定治疗目标至关重要。美国目前肥胖测量的金标准——国家健康与营养检查调查（NHANES）——抽样人群不足0.1%，且未针对州级或卫生系统层面的测量。
评估使用电子健康记录（EHR）中的体重指数（BMI）数据评估超重和肥胖率，并将这些率与国家NHANES估计值进行比较的可行性。
利用42家诊所的门诊数据，我们研究了一个大型卫生系统中在2011 - 2012年至少有1次初级保健就诊的388,762名患者。
我们比较了EHR参与者和NHANES参与者按年龄类别和种族（白人、黑人、西班牙裔、其他）划分的粗率和调整后的超重及肥胖率。调整后的超重（BMI≥25）和肥胖率通过两步法计算。第一步使用逆概率加权法处理缺失的BMI数据，而第二步包括后分层校正，以将EHR人群调整为具有全国代表性的样本。
EHR患者的调整后肥胖率（BMI≥30）为37.3% [95%置信区间（95%CI），37.1 - 37.5]，而NHANES患者为35.1%（95%CI，32.3 - 38.1）。在EHR患者和NHANES患者之间比较的16个不同的肥胖类别、种族和性别分层中，14个（87.5%）包含相似的肥胖估计值（即95%CI重叠）。
电子健康记录可能是识别和确定肥胖患者以实施公共卫生和/或个人层面干预措施的理想工具。
