Clinical Decision Supports in Electronic Health Records to Promote Childhood Obesity-Related Care: Results from a 2015 Survey of Healthcare Providers

利用电子健康记录中的临床决策支持促进儿童肥胖相关护理:2015 年医疗保健提供者调查结果

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Abstract

Obesity-related clinical decision support tools in electronic health records (EHRs) can improve pediatric care, but the degree of adoption of these tools is unknown. DocStyles 2015 survey data from US pediatric healthcare providers (n = 1,156) were analyzed. Multivariable logistic regression identified provider characteristics associated with three EHR functionalities: automatically calculating body mass index (BMI) percentile (AUTO), displaying BMI trajectory (DISPLAY), and flagging abnormal BMIs (FLAG). Most providers had EHRs (88%). Of those with EHRs, 90% reporting having AUTO, 62% DISPLAY, and 54% FLAG functionalities. Only provider age was associated with all three functionalities. Compared to providers aged > 54 years, providers < 40 years had greater odds for: AUTO (adjusted odds ratio [aOR], 3.0; 95% confidence interval [CI], 1.58-5.70), DISPLAY (aOR, 2.07; 95% CI, 1.38-3.12), and FLAG (aOR, 1.67; 95% CI, 1.14-2.44). Future investigations can elucidate causes of lower adoption of EHR functions that display growth trajectories and flag abnormal BMIs.

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