Clinical Decision Supports in Electronic Health Records to Promote Childhood Obesity-Related Care: Results from a 2015 Survey of Healthcare Providers
- Author:
Megan R HARRISON
1
;
Elizabeth A LUNDEEN
;
Brook BELAY
;
Alyson B GOODMAN
Author Information
- Publication Type:Original Article
- Keywords: Childhood obesity; Childhood overweight; Adolescent; Electronic health record; Decision supports
- MeSH: Adolescent; Body Mass Index; Decision Support Systems, Clinical; Delivery of Health Care; Electronic Health Records; Health Personnel; Humans; Logistic Models; Odds Ratio; Pediatric Obesity
- From:Clinical Nutrition Research 2019;8(4):255-264
- CountryRepublic of Korea
- Language:English
- 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.
