BACKGROUND: Poor medication adherence is a predictor of poor health outcomes, especially in populations with chronic diseases. Although several self-reported measures of medication adherence exist, the scope of each is limited. OBJECTIVE: To identify barriers to medication adherence in order to facilitate effective delivery of telephone-based medication therapy management (MTM) services to beneficiaries of contracted Medicare Part D plans. METHODS: This study used a cross-sectional telephone-based questionnaire designed to elicit reasons for low medication adherence. Patients were eligible to participate if they were identified as nonadherent for an antilipidemic, antihypertensive, or antidiabetic agent. Nonadherence was defined as less than 80% of proportion of days covered (PDC). The questionnaire included 17 items pertaining to medication use and 3 demographic items. Data were collected between September 2012 and February 2013. Data analyses included descriptive statistics and Rasch analyses. RESULTS: A total of 124 patients participated in the telephone survey. Of those completing the survey, the majority were patients (97.6%); only 3 surveys (2.4%) were completed by caregivers. The sample population had a mean age of 69.8 years (SD = 9.9), and more than half of participants (60.4%) were female. Nineteen percent of respondents received their medications by mail. Medication nonadherence generated alerts mostly associated with antilipidemic agents (n = 50, 40.3%), followed by antihypertensive drugs (n = 36, 29.0%), and antidiabetic medications (n = 23, 18.5%). The response categories for medication belief items were collapsed from 4 to 3 categories to achieve acceptable Rasch model fit (to fit the model and approximate interval level data). Ten percent of participants reported having medications prescribed either that they did not get or that they obtained but did not use. Almost 30% of patients reported having medications prescribed that they started using but stopped. However, only 4% of patients reporting adherence issues were related to the alert triggering for chronic medications; 96% of reports were linked to unrelated medications that did not generate an alert. The most common reason cited for medication nonadherence was experiencing side effects. CONCLUSIONS: Most participants reported positive beliefs about medications and did not report adherence issues related to those triggering alerts. MTM programs offer potential solutions to a number of barriers to medication adherence and a unique opportunity to raise awareness about the importance of medication adherence among members.
BACKGROUND: Poor medication adherence is a predictor of poor health outcomes, especially in populations with chronic diseases. Although several self-reported measures of medication adherence exist, the scope of each is limited. OBJECTIVE: To identify barriers to medication adherence in order to facilitate effective delivery of telephone-based medication therapy management (MTM) services to beneficiaries of contracted Medicare Part D plans. METHODS: This study used a cross-sectional telephone-based questionnaire designed to elicit reasons for low medication adherence. Patients were eligible to participate if they were identified as nonadherent for an antilipidemic, antihypertensive, or antidiabetic agent. Nonadherence was defined as less than 80% of proportion of days covered (PDC). The questionnaire included 17 items pertaining to medication use and 3 demographic items. Data were collected between September 2012 and February 2013. Data analyses included descriptive statistics and Rasch analyses. RESULTS: A total of 124 patients participated in the telephone survey. Of those completing the survey, the majority were patients (97.6%); only 3 surveys (2.4%) were completed by caregivers. The sample population had a mean age of 69.8 years (SD = 9.9), and more than half of participants (60.4%) were female. Nineteen percent of respondents received their medications by mail. Medication nonadherence generated alerts mostly associated with antilipidemic agents (n = 50, 40.3%), followed by antihypertensive drugs (n = 36, 29.0%), and antidiabetic medications (n = 23, 18.5%). The response categories for medication belief items were collapsed from 4 to 3 categories to achieve acceptable Rasch model fit (to fit the model and approximate interval level data). Ten percent of participants reported having medications prescribed either that they did not get or that they obtained but did not use. Almost 30% of patients reported having medications prescribed that they started using but stopped. However, only 4% of patients reporting adherence issues were related to the alert triggering for chronic medications; 96% of reports were linked to unrelated medications that did not generate an alert. The most common reason cited for medication nonadherence was experiencing side effects. CONCLUSIONS: Most participants reported positive beliefs about medications and did not report adherence issues related to those triggering alerts. MTM programs offer potential solutions to a number of barriers to medication adherence and a unique opportunity to raise awareness about the importance of medication adherence among members.