Comprehensive Medication Management and Medication Adherence for Chronic Conditions

BACKGROUND: The beneficial clinical effects of medication adherence have been consistently reported across most chronic diseases. Medication nonadherence carries significant economic and clinical burden. Medication therapy management (MTM) services aim to optimize pharmacotherapy and improve medication adherence. OBJECTIVE: To evaluate the impact of exposure to face-to-face comprehensive medication management (CMM) services on medication adherence across 4 classes of chronic disease medications: oral diabetes medications, statins, angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs), and beta-blockers. METHODS: Pharmacy claims of continuously enrolled employees of a large Midwest integrated health system were retrieved for the period 2007-2011. Retrospective analysis was used to compare medication adherence measured using proportion of days covered (PDC) in employees who received CMM with employees who did not (control group). The pharmacy MTM program used the Patient-Centered Primary Care Collaborative standard of care. The CMM group’s index date was the date of the first CMM visit; the non-CMM group’s index date was randomly chosen from all therapeutic class-specific prescription claims dates. For each therapeutic class, patients with at least 1 prescription fill in both the measurement period (365 days post-index) and the baseline period (365 days pre-index) were included. The primary outcome measure was the PDC. RESULTS: The CMM group had consistently higher and statistically significant PDC levels across all the therapeutic classes in the measurement period (P < 0.05) when looking at the unadjusted comparison. In the multivariate models, CMM exposure was associated with higher PDC; the difference between groups was statistically significant in all therapeutic classes except for oral diabetes medications (oral diabetes medications: 0.0403, 95% confidence limits [CL] = -0.0050, 0.0850; statins: 0.0769, 95% CL = 0.0480, 0.1050; ACEIs/ARBs: 0.1083; 95% CL = 0.0710, 0.1450; and beta-blockers: 0.0484; 95% CL = 0.0060, 0.0910). Logistic regression showed that the CMM group had an increased probability of meeting the 80% PDC cut-point for statins (3.36, 95% CL = 0.048, 0.105); ACEIs/ARBs (3.57, 95% CL = 2.35, 5.42); and beta-blockers (2.56, 95% CL = 1.57, 4.18). CONCLUSIONS: Exposure to face-to-face CMM services resulted in improvement of medication adherence. CMM is a powerful practice model that should be encouraged by insurers and health plan administrators to increase rates of medication adherence.