title: Validating smoking data from the Veteran's Affairs Health Factors dataset, an electronic data source.
abstract: BACKGROUND
  We assessed smoking data from the Veterans Health Administration (VHA) electronic medical record (EMR) Health Factors dataset.
  
  
  METHODS
  To assess the validity of the EMR Health Factors smoking data, we first created an algorithm to convert text entries into a 3-category smoking variable (never, former, and current). We compared this EMR smoking variable to 2 different sources of patient self-reported smoking survey data: (a) 6,816 HIV-infected and -uninfected participants in the 8-site Veterans Aging Cohort Study (VACS-8) and (b) a subset of 13,689 participants from the national VACS Virtual Cohort (VACS-VC), who also completed the 1999 Large Health Study (LHS) survey. Sensitivity, specificity, and kappa statistics were used to evaluate agreement of EMR Health Factors smoking data with self-report smoking data.
  
  
  RESULTS
  For the EMR Health Factors and VACS-8 comparison of current, former, and never smoking categories, the kappa statistic was .66. For EMR Health Factors and VACS-VC/LHS comparison of smoking, the kappa statistic was .61.
  
  
  CONCLUSIONS
  Based on kappa statistics, agreement between the EMR Health Factors and survey sources is substantial. Identification of current smokers nationally within the VHA can be used in future studies to track smoking status over time, to evaluate smoking interventions, and to adjust for smoking status in research. Our methodology may provide insights for other organizations seeking to use EMR data for accurate determination of smoking status.
authors.affiliation: Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, 7180 Highland Drive (151C-H), Pittsburgh, PA 15206-4900, USA. kathleen.mcginnis3@va.gov
authors.forename: Kathleen A
authors.initials: KA
authors.lastname: McGinnis
authors.forename: Cynthia A
authors.initials: CA
authors.lastname: Brandt
authors.forename: Melissa
authors.initials: M
authors.lastname: Skanderson
authors.forename: Amy C
authors.initials: AC
authors.lastname: Justice
authors.forename: Shahida
authors.initials: S
authors.lastname: Shahrir
authors.forename: Adeel A
authors.initials: AA
authors.lastname: Butt
authors.forename: Sheldon T
authors.initials: ST
authors.lastname: Brown
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Freiberg
authors.forename: Cynthia L
authors.initials: CL
authors.lastname: Gibert
authors.forename: Matthew Bidwell
authors.initials: MB
authors.lastname: Goetz
authors.forename: Joon Woo
authors.initials: JW
authors.lastname: Kim
authors.forename: Margaret A
authors.initials: MA
authors.lastname: Pisani
authors.forename: David
authors.initials: D
authors.lastname: Rimland
authors.forename: Maria C
authors.initials: MC
authors.lastname: Rodriguez-Barradas
authors.forename: Jason J
authors.initials: JJ
authors.lastname: Sico
authors.forename: Hilary A
authors.initials: HA
authors.lastname: Tindle
authors.forename: Kristina
authors.initials: K
authors.lastname: Crothers
mesh_terms: D000328:Adult; D000465:Algorithms; D015331:Cohort Studies; D003625:Data Collection / Q000592:standards*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D057566:Self Report; D012907:Smoking / Q000453:epidemiology*; D014481:United States; D014493:United States Department of Veterans Affairs; D014728:Veterans / Q000706:statistics & numerical data*; D058014:Veterans Health / Q000706:statistics & numerical data*