The effect of cost on adherence to prescription medications in Canada

Data and variables

We analyzed data from the 2007 Canadian Community Health Survey, a telephone survey of the community-dwelling household population 12 years of age and older.14 From September to December, 2007, respondents were asked a series of questions on prescription drug insurance and cost-related nonadherence. The response rate to this component of the survey was 72.2% and included 10 898 respondents from all 10 provinces. Of these respondents, 9404 (86.3%) agreed to share their data with Statistics Canada’s partner agencies. Our study sample was drawn from these respondents.

Cost-related nonadherence was measured using a combination of responses to three questions on the survey (questions 3–5, Appendix 1, available at www.cmaj.ca/lookup/suppl/doi:10.1503/cmaj.111270/-/DC1). Respondents were first asked whether they had received a prescription in the past year. Those who reported that they had received a prescription were then asked three questions about whether costs led them to do anything to make their prescription last longer, not fill a new prescription or not renew a prescription. If a respondent answered yes to any of these three questions, we considered this to be a report of cost-related nonadherence.

We used the survey to construct a range of variables that are consistent with widely used conceptual frameworks on access to health services.15 These included province of residence, age, sex, household income, level of education, self-assessed health status and number of reported chronic conditions (including arthritis, chronic obstructive pulmonary disease, diabetes, cancer, heart disease, high blood pressure and mood disorders), as well as whether respondents reported having prescription drug coverage that paid all or part of the cost of their medications (question 1, Appendix 1).

Statistical analysis

We developed a logistic regression model to determine what factors were associated with reporting cost-related nonadherence. Because the number of respondents in some provinces was small, we combined provinces with less than 1000 respondents into two regional groups: Saskatchewan and Manitoba were combined, as were New Brunswick, Nova Scotia, Prince Edward Island, and Newfoundland and Labrador (Atlantic provinces). This grouping did not change our results by individual province in any substantive manner. We grouped several other variables into categories, including age (12–34, 35–44, 45–64, and ≥ 65 years), annual household income (< $20 000, $20 000–$39 999, $40 000–$59 999, $60 000–$79 999, ≥ $80 000), highest level of education attained (less than high school, high school, some postsecondary, postsecondary), self-assessed health status (excellent or very good, good, fair or poor), and number of reported chronic conditions (none, one, two or more).

To account for the complex sampling design of the survey, we used Statistics Canada survey weights and calculated all confidence intervals (CIs) using bootstrapping.16 In our descriptive analysis, we included only respondents for whom we had complete data (n = 7917, 84.2%). When calculating rates of cost-related nonadherence and statistical modelling, we further restricted our sample to those who reported having received a prescription in the past year (n = 5732, 72.4%). We also conducted two sensitivity analyses. First, we included respondents for whom income data was missing in our model and used multiple imputation based on chained equations to estimate their incomes.17 Second, we modelled an outcome variable calculated from only the first two cost-related questions on non-adherence (not filling and not renewing a prescription). Both analyses showed results with the same substantive interpretation as those we report here (data not shown). To facilitate interpretation of our regression model, we predicted the probability of cost-related nonadherence for both insured and uninsured members of each income group. We calculated these predictions using the average for all other covariates to make them representative of the entire Canadian population.