Background: Research using the Veterans Health Administration (VA) electronic medical records (EMR) has been limited by a lack of reliable smoking data.
Objective: To evaluate the validity of using VA EMR "Health Factors" data to determine smoking status among veterans with recent military service.
Design: Sensitivity, specificity, area under the receiver-operating curve (AUC), and kappa statistics were used to evaluate concordance between VA EMR smoking status and criterion smoking status.
Participants: Veterans (N = 2025) with service during the wars in Iraq/Afghanistan who participated in the VA Mid-Atlantic Post-Deployment Mental Health (PDMH) Study.
Main Measures: Criterion smoking status was based on self-report during a confidential study visit. VA EMR smoking status was measured by coding health factors data entries (populated during automated clinical reminders) in three ways: based on the most common health factor, the most recent health factor, and the health factor within 12 months of the criterion smoking status data collection date.
Key Results: Concordance with PDMH smoking status (current, former, never) was highest when determined by the most commonly observed VA EMR health factor (κ = 0.69) and was not significantly impacted by psychiatric status. Agreement was higher when smoking status was dichotomized: current vs. not current (κ = 0.73; sensitivity = 0.84; specificity = 0.91; AUC = 0.87); ever vs. never (κ = 0.75; sensitivity = 0.85; specificity = 0.90; AUC = 0.87). There were substantial missing Health Factors data when restricting analyses to a 12-month period from the criterion smoking status date. Current smokers had significantly more Health Factors entries compared to never or former smokers.
Conclusions: The use of computerized tobacco screening data to determine smoking status is valid and feasible. Results indicating that smokers have significantly more health factors entries than non-smokers suggest that caution is warranted when using the EMR to select cases for cohort studies as the risk for selection bias appears high.
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| http://dx.doi.org/10.1007/s11606-017-4144-5 | DOI Listing |
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