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  • Title: Evaluation of Medication Adherence Among Prevalent Users in Hypertension, Dyslipidemia, and Diabetes Using Health Insurance Claims: A Population-Based Cohort Study in Japan.
    Author: Matsumoto M, Harada S, Ikuta H, Iida M, Kato S, Sata M, Shibuki T, Ishibashi Y, Miyagawa N, Hisamatsu M, Hirata A, Kuwabara K, Takeuchi A, Sugiyama D, Suzuki S, Nakamura T, Okamura T, Takebayashi T.
    Journal: Pharmacoepidemiol Drug Saf; 2024 Aug; 33(8):e5855. PubMed ID: 39145400.
    Abstract:
    PURPOSE: Hypertension (HT), dyslipidemia (DL), and diabetes mellitus (DM) are major risk factors for cardiovascular diseases. Despite the wide availability of medications to reduce this risk, poor adherence to medications remains an issue. The aim of this study is to evaluate medication adherence of prevalent users in these disease medications (HT, DL, DM) using claims data. Factors associated with non-adherence were also examined. METHODS: Of 7538 participants of the Tsuruoka Metabolomics Cohort Study, 3693 (HT: 2702, DL: 2112, DM: 661) were identified as prevalent users of these disease medications. Information on lifestyle was collected through a questionnaire. Adherence was assessed by a proportion of days covered (PDC) and participants with PDC ≥0.8 were defined as adherent. Predictors of non-adherence were determined by performing multivariable logistic regression. RESULTS: Medication adherence differed by treatment status. Among those without comorbidities, those with HT-only showed the highest adherence (90.2%), followed by those with DM-only (81.2%) and those with DL-only (80.8%). Factors associated with non-adherence in each medication group were skipping breakfast and poor understanding of medications among those with HT medications, females, having comorbidities, having a history of heart disease, and drinking habit among those with DL medications, and good sleep quality and skipping breakfast among those with DM medications. CONCLUSION: While participants showed high medication adherence, differences were observed across medication groups. The identified predictors of non-adherence could help target those in need of adherence support.
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