title: Electronic health records and community health surveillance of childhood obesity.
abstract: BACKGROUND
  Childhood obesity remains a public health concern, and tracking local progress may require local surveillance systems. Electronic health record data may provide a cost-effective solution.
  
  
  OBJECTIVE
  To demonstrate the feasibility of estimating childhood obesity rates using de-identified electronic health records for the purpose of public health surveillance and health promotion.
  
  
  METHODS
  Data were extracted from the Public Health Information Exchange (PHINEX) database. PHINEX contains de-identified electronic health records from patients primarily in south central Wisconsin. Data on children and adolescents (aged 2-19 years, 2011-2012, n=93,130) were transformed in a two-step procedure that adjusted for missing data and weighted for a national population distribution. Weighted and adjusted obesity rates were compared to the 2011-2012 National Health and Nutrition Examination Survey (NHANES). Data were analyzed in 2014.
  
  
  RESULTS
  The weighted and adjusted obesity rate was 16.1% (95% CI=15.8, 16.4). Non-Hispanic white children and adolescents (11.8%, 95% CI=11.5, 12.1) had lower obesity rates compared to non-Hispanic black (22.0%, 95% CI=20.7, 23.2) and Hispanic (23.8%, 95% CI=22.4, 25.1) patients. Overall, electronic health record-derived point estimates were comparable to NHANES, revealing disparities from preschool onward.
  
  
  CONCLUSIONS
  Electronic health records that are weighted and adjusted to account for intrinsic bias may create an opportunity for comparing regional disparities with precision. In PHINEX patients, childhood obesity disparities were measurable from a young age, highlighting the need for early intervention for at-risk children. The electronic health record is a cost-effective, promising tool for local obesity prevention efforts.
authors.affiliation: Departments of Population Health Sciences, University of Wisconsin School of Medicine and Public Health.
authors.forename: Tracy L
authors.initials: TL
authors.lastname: Flood
authors.affiliation: Biostatistics and Medical Informatics, University of Wisconsin School of Medicine and Public Health.
authors.forename: Ying-Qi
authors.initials: YQ
authors.lastname: Zhao
authors.affiliation: Department of Nutritional Sciences, University of Wisconsin College of Agricultural and Life Sciences, Madison, Wisconsin.
authors.forename: Emily J
authors.initials: EJ
authors.lastname: Tomayko
authors.affiliation: Family Medicine, University of Wisconsin School of Medicine and Public Health.
authors.forename: Aman
authors.initials: A
authors.lastname: Tandias
authors.affiliation: Pediatrics, University of Wisconsin School of Medicine and Public Health.
authors.forename: Aaron L
authors.initials: AL
authors.lastname: Carrel
authors.affiliation: Family Medicine, University of Wisconsin School of Medicine and Public Health. Electronic address: larry.hanrahan@fammed.wisc.edu.
authors.forename: Lawrence P
authors.initials: LP
authors.lastname: Hanrahan
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D057286:Electronic Health Records; D005240:Feasibility Studies; D005260:Female; D054624:Health Status Disparities; D006801:Humans; D008297:Male; D063766:Pediatric Obesity / Q000453:epidemiology*; D011159:Population Surveillance; D044469:Racial Groups / Q000706:statistics & numerical data; D014922:Wisconsin / Q000453:epidemiology; D055815:Young Adult