Electronic health records to support obesity-related patient care: Results from a survey of United States physicians Kayla L. Bronder b, ⁎ , Carrie A. Dooyema a , Stephen J. Onufrak a , Jennifer L. Foltz a,c a Division of Nutrition, Physical Activity, and Obesity, Centers for Disease Control and Prevention, Atlanta, GA, USA b The CDC Experience Applied Epidemiology Fellowship, Scientific Education and Professional Development Program Office, Centers for Disease Control and Prevention, Atlanta, GA, USA c United States Public Health Service Commissioned Corps, Atlanta, GA, USA abstract article info Available online 5 May 2015 Keywords: Electronic health records Obesity Body mass index Objective. Obesity-related electronic health record functions increase the rates of measuring Body Mass Index, diagnosing obesity, and providing obesity services. This study describes the prevalence of obesity-related electronic health record functions in clinical practice and analyzes characteristics associated with increased obesity-related electronic health record sophistication. Methods. Data were analyzed from DocStyles, a web-based panel survey administered to 1507 primary care providers practicing in the United States in June, 2013. Physicians were asked if their electronic health record has specific obesity-related functions. Logistical regression analyses identified characteristics associated with im- proved obesity-related electronic health record sophistication. Results. Of the 88% of providers with an electronic health record, 83% of electronic health records calculate Body Mass Index, 52% calculate pediatric Body Mass Index percentile, and 32% flag patients with abnormal Body Mass Index values. Only 36% provide obesity-related decision support and 17% suggest additional resources for obesity-related care. Characteristics associated with having a more sophisticated electronic health record in- clude age ≤ 45 years old, being a pediatrician or family practitioner, and practicing in a larger, outpatient practice. Conclusions. Few electronic health records optimally supported physician's obesity-related clinical care. The low rates of obesity-related electronic health record functions currently in practice highlight areas to improve the clinical health information technology in primary care practice. More work can be done to develop, implement, and promote the effective utilization of obesity-related electronic health record functions to improve obesity treatment and prevention efforts. Published by Elsevier Inc. Background and significance The number of people affected by obesity in the United States is high, with an obesity prevalence of 34.9% for adults and 16.9% for youth in 2011–2012 (Ogden et al., 2013). National obesity treatment guidelines suggest annual screening for obesity as standard of care for adults (Moyer, 2012) and children aged 2 years and older (Barlow, 2007). However, it is estimated that among adults and children with clinical obe- sity, less than 30% of adults (Ma et al., 2009) and only 18% of obese children were diagnosed as obese during their primary care visit (Patel et al., 2010). Additionally, only 37% of obese adults received any obesity counseling (Ma et al., 2009). Several studies have demonstrated that obesity-related electronic health record (EHR) functions can assist pro- viders in the screening and treatment of both adult (Baer et al., 2013) and childhood obesity (Smith et al., 2013). Obesity-related EHR functions increase the rates of assessing body mass index (BMI), diagnosing obesity, and providing obesity counseling and treatment services (Baer et al., 2013; Adhikari et al., 2012; Bordowitz et al., 2007; Coleman et al., 2012; Keehbauch et al., 2012; Savinon et al., 2012; Ayash et al., 2013). The Health Information Technology for Economic and Clinical Health Act was passed in 2009 to spur adoption and utilization of EHRs in hospitals and outpatient clinics. This legislation includes funding to providers who adopt and use EHRs meeting specific re- quirements, known as Meaningful Use (MU) standards. Obesity screening was included in the MU standards; in order to receive incentive payments, EHRs are required to calculate and display BMI for adults and plot and display growth charts, including BMI, for children 0–20 years (Centers for Medicare and Medicaid Services HHS, 2012). Physicians have responded positively to the incentives with EHR adoption increasing from 17% in 2006 to 78% in 2013 among outpatient providers (Hsiao and Hing, 2012). Objective While obesity-related EHR functions have been shown to help physicians diagnose and treat obesity, little is known about obesity- Preventive Medicine 77 (2015) 41–47 ⁎ Corresponding author at: University of Michigan, 1500 E. Medical Center Drive, D3230 MPB, SPC 5718, Ann Arbor, MI 48109-5718. E-mail address: kaylabronder@gmail.com (K.L. Bronder). http://dx.doi.org/10.1016/j.ypmed.2015.04.018 0091-7435/Published by Elsevier Inc. Contents lists available at ScienceDirect Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed