Abstract
OBJECTIVE: To analyze primary medication nonadherence across several prescription indications and test the predictors of drug nonadherence in an adult primary care population. DESIGN: Retrospective observational study using primary care provider prescriptions linked to pharmacy-based dispensing data from 2012 to 2014. SETTING: Manitoba. PARTICIPANTS: Patients in the Manitoba Primary Care Research Network. MAIN OUTCOME MEASURES: Prevalence of primary medication nonadherence by drug class. Multivariable logistic regression models were used to test the associations of patient demographic and clinical or provider characteristics with primary medication nonadherence. The C statistic was used to assess the models' discriminative performance. RESULTS: A total of 91,660 unique prescriptions were assessed from a cohort of more than 200,000 patients. Primary medication nonadherence ranged from 13.7% (antidepressants) to 30.3% (antihypertensives). In conditions that typically present symptomatically (eg, infections, anxiety) nonadherence ranged from 13.7% to 17.5%. The range was 21.2% to 30.0% for medications related to asymptomatic conditions or those typically detected by screening. The discriminative performance of the models based on patient demographic, clinical, or provider characteristics was weak. CONCLUSION: Primary medication nonadherence is common, occurring more often in asymptomatic conditions. The poor predictability of the models suggests that caution is required when considering characteristic-based interventions or prediction tools to improve primary medication nonadherence.