Assessing the feasibility of using computerized pharmacy refill data to monitor antidepressant treatment on a population basis: a comparison of automated and self-report data.

This article compares self-report and automated data as measures of dose and duration of antidepressant use in order to assess the feasibility of using automated pharmacy data in a disease management context. We used self-report and computerized refill data to identify two treatment failures-premature discontinuation of the medication and sub-optimal dosages-at time points 1 and 4 months after initiation of antidepressant therapy. The sources showed modest agreement regarding identification of current users at 1 month (kappa = .33); agreement was high at 4 months (kappa = .72). Agreement regarding dosage adequacy was also higher later in treatment, with kappas of .52 and .65 at 1 and 4 months, respectively. The two sources showed high agreement on an overall measure of acute phase treatment adequacy (kappa = .80). Data completeness was another outcome, with data on current users and overall treatment adequacy generally available from computerized files, data on dose less so. Automated pharmacy data appear to be a feasible means of monitoring treatment adequacy and quality of care as part of a disease management approach to improving care for populations of patients.