Clinical Decision Supports in Electronic Health Records to Promote Childhood Obesity-Related Care: Results from a 2015 Survey of Healthcare Providers
Clinical Nutrition Research
; : 255-264, 2019.
Article
in English
| WPRIM (Western Pacific)
| ID: wpr-763502
Responsible library:
WPRO
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.
Full text:
Available
Health context:
Sustainable Health Agenda for the Americas
Health problem:
Goal 6: Information systems for health
Database:
WPRIM (Western Pacific)
Main subject:
Body Mass Index
/
Logistic Models
/
Odds Ratio
/
Health Personnel
/
Decision Support Systems, Clinical
/
Delivery of Health Care
/
Electronic Health Records
/
Pediatric Obesity
Type of study:
Etiology study
/
Prognostic study
/
Risk factors
Aspects:
Social determinants of health
Limits:
Adolescent
/
Humans
Language:
English
Journal:
Clinical Nutrition Research
Year:
2019
Document type:
Article