Self-reported medication use validated through record linkage to national prescribing data

Abstract

Objectives: Researchers need to be confident about the reliability of epidemiologic studies that quantify medication use through self-report. Some evidence suggests that psychiatric medications are systemically under-reported. Modern record linkage enables validation of self-report with national prescribing data as gold standard. Here, we investigated the validity of medication self-report for multiple medication types.

Study design and setting: Participants in the Generation Scotland population-based cohort (N = 10,244) recruited 2009-2011 self-reported regular usage of several commonly prescribed medication classes. This was matched against Scottish NHS prescriptions data using 3- and 6-month fixed time windows. Potential predictors of discordant self-report, including general intelligence and psychological distress, were studied via multivariable logistic regression.

Results: Antidepressants self-report showed very good agreement (κ = 0.85, [95% confidence interval (CI) 0.84-0.87]), comparable to antihypertensives (κ = 0.90 [CI 0.89-0.91]). Self-report of mood stabilizers showed moderate-poor agreement (κ = 0.42 [CI 0.33-0.50]). Relevant past medical history was the strongest predictor of self-report sensitivity, whereas general intelligence was not predictive.

Conclusion: In this large population-based study, we found self-report validity varied among medication classes, with no simple relationship between psychiatric medication and under-reporting. History of indicated illness predicted more accurate self-report, for both psychiatric and nonpsychiatric medications. Although other patient-level factors influenced self-report for some medications, none predicted greater accuracy across all medications studied.

Keywords: Agreement; Indication; Linkage; Medicines; Pharmacoepidemiology; Self-report.