Abstract
Background:
Primary nonadherence is probably an important contributor to suboptimal disease management, but methodological challenges have limited investigation of it.
Objective:
To estimate the incidence of primary nonadherence in primary care and the drug, patient, and physician characteristics that are associated with nonadherence.
Design:
A prospective cohort of patients and all their incident prescriptions from primary care electronic health records between 2006 and 2009 linked to provincial drug insurer data on all drugs dispensed from community-based pharmacies were assembled.
Setting:
Quebec, Canada.
Patients:
15 961 patients in a primary care network of 131 physicians.
Measurements:
Primary nonadherence was defined as not filling an incident prescription within 9 months. Multivariate alternating logistic regression was used to estimate predictors of nonadherence and account for patient and physician clustering.
Results:
Overall, 31.3% of the 37 506 incident prescriptions written for the 15 961 patients were not filled. Drugs in the upper quartile of cost were least likely to be filled (odds ratio [OR], 1.11 [95% CI, 1.07 to 1.17]), as were skin agents, gastrointestinal drugs, and autonomic drugs, compared with anti-infectives. Reduced odds of nonadherence were associated with increasing patient age (OR per 10 years, 0.89 [CI, 0.85 to 0.92]), elimination of prescription copayments for low-income groups (OR, 0.37 [CI, 0.32 to 0.41]), and a greater proportion of all physician visits with the prescribing physician (OR per 0.5 increase, 0.77 [CI, 0.70 to 0.85]).
Limitation:
Patients' rationale for choosing not to fill their prescriptions could not be measured.
Conclusion:
Primary nonadherence is common and may be reduced by lower drug costs and copayments, as well as increased follow-up care with prescribing physicians for patients with chronic conditions.
Primary Funding Source:
Canadian Institutes of Health Research.
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Author, Article, and Disclosure Information
Authors:
Robyn Tamblyn,
From the Clinical and Health Informatics Research Group, McGill University, Montreal, Quebec, and University of Ottawa and The Ottawa Hospital, Ottawa, Ontario, Canada.
Acknowledgment: The authors thank Dr. Jim Hanley for his thoughtful suggestions about the statistical analysis and its interpretation and Sherry Shi for her assistance in data analysis.
Grant Support: Dr. Eguale was supported by the Canadian Institutes of Health Research Fellowship.
Disclosures: None disclosed. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-1705.
Reproducible Research Statement: Study protocol and data set: Available from Dr. Tamblyn (e-mail, robyn.
Corresponding Author: Robyn Tamblyn, PhD, McGill University, Morrice House, 1140 Pine Avenue West, Montreal, Quebec H3A 1A3, Canada; e-mail, robyn.
Current Author Addresses: Drs. Tamblyn, Eguale, and Huang; Ms. Winslade; and Ms. Doran: McGill University, Morrice House, 1140 Pine Avenue West, Montreal, Quebec H3A 1A3, Canada.
Author Contributions: Conception and design: R. Tamblyn, T. Eguale, A. Huang, N. Winslade.
Analysis and interpretation of the data: R. Tamblyn, T. Eguale, N. Winslade.
Drafting of the article: R. Tamblyn, T. Eguale, P. Doran.
Critical revision of the article for important intellectual content: R. Tamblyn, T. Eguale, A. Huang, P. Doran.
Final approval of the article: R. Tamblyn, T. Eguale, A. Huang, N. Winslade, P. Doran.
Provision of study materials or patients: R. Tamblyn.
Statistical expertise: R. Tamblyn, T. Eguale.
Obtaining of funding: R. Tamblyn.
Administrative, technical, or logistic support: R. Tamblyn, P. Doran.
Collection and assembly of data: R. Tamblyn, T. Eguale, A. Huang.
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