Group-based trajectory modeling to identify longitudinal patterns and predictors of adherence among older adults on concomitant triple therapy (oral antidiabetic, renin-angiotensin-system antagonists, statins)

• DOI: 10.18553/jmcp.2025.31.4.396
• Publication Date: 2025-03-28T15:02:19Z
• Authors: Sai S. Cheruvu; Bilqees Fatima; Susan Abughosh
• Keywords: Concomitant

Diabetes, hypertension, and hyperlipidemia frequently co-occur in older adults, significantly increasing their risk for cardiovascular disease, a leading cause of mortality the United States. Managing these conditions often requires concomitant triple therapy, which includes antihypertensives, oral antidiabetics, statins. Although medication adherence is critical reducing risk, to complex regimens suboptimal populations, further complicating disease management. Medicare's STAR metrics assess medications as measure care quality. Traditional methods, like proportion days covered (PDC), provide single estimates, but fail capture dynamic nature over time. Group-based trajectory modeling (GBTM) offers more comprehensive approach, graphically depicting patterns behavior. This study seeks understand longitudinal predictors concurrent therapy among elderly patients under Managed Care using GBTM. To evaluate (antidiabetic, antihypertensive, lipid-lowering medications) GBTM identify associated with each trajectory. Patients on were identified Texas Medicare Advantage dataset from July 2016 December 2016. included had an overlap 30 second prescription component within identification period, 12-month follow-up after therapy. Monthly was measured PDC during follow-up. defined adherent if they at least 80% (24 out days) all 3 medications. The monthly incorporated into logistic distinct adherence. Two five groups estimated second-order polynomial function Predictors multinomial regression, guided by Anderson Behavioral Model. Of 7,847 included, following 4 trajectories identified: (42.5%), gaps (28.9%), gradual decline (13.4%), rapid (15.3%). Female higher odds being or compared males. Low-income subsidy recipients less likely experience decline. Prior hospitalizations increased likelihood heterogeneous adults factors. Targeted interventions tailored specific are needed improve health outcomes this high-risk population.