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

Megan R Harrison; Elizabeth A Lundeen; Brook Belay; Alyson B Goodman

doi:10.7762/cnr.2019.8.4.255

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

Clin Nutr Res. 2019 Oct 14;8(4):255-264. doi: 10.7762/cnr.2019.8.4.255. eCollection 2019 Oct.

Authors

Megan R Harrison¹, Elizabeth A Lundeen¹, Brook Belay¹, Alyson B Goodman¹

Affiliation

¹ Division of Nutrition, Physical Activity and Obesity, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.

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.

Keywords: Adolescent; Childhood obesity; Childhood overweight; Decision supports; Electronic health record.