Abstract
OBJECTIVE: In this study, we utilized a large-scale clinical database to evaluate the relationship between polypharmacy and adverse outcomes among type 2 diabetes patients in rural Montana to inform strategies that improve adherence, reduce preventable complications, and promote equitable diabetes care in underserved regions. RESEARCH DESIGN AND METHODS: 591 patients from the Big Sky Care Connect Database (BSCC) with type 2 diabetes and medication history were stratified into 3 cohorts based on prescribed number of medications: (1-4 medications, non-polypharmic), (5-9 medications, polypharmic), and (≥10 medications, hyperpolypharmic). Each cohort was examined for Major Adverse Cardiovascular Events (MACE) and Diabetes Complication Severity Index (DCSI). Descriptive statistics, multivariate logistic regressions, linear regression, and Poisson regression analyses were performed. RESULTS: Medication count was associated with male gender (β = -2.1341, p < 0.001). Both medication count (IRR 1.06 per additional medication, p < 0.001) and age (IRR 1.03 per year, p < 0.001) were significant predictors of MACE. Neuropathy and nephropathy prevalence was statistically significant (p < 0.001) across patient cohorts and increased with medication count. CONCLUSIONS: A high prevalence of polypharmacy was observed in type 2 diabetic patients in rural Montana. Polypharmacy was found to be a significant predictor of MACE and increased the odds of nephropathy in this study. While disease severity contributes to higher medication counts, these findings highlight the need for medication review and cross-provider management to minimize adverse outcomes. ARTICLE HIGHLIGHTS: Why did we undertake this study? The study presents the impact of polypharmacy in the management of type 2 diabetes patients in a rural, medically underserved population in Montana What is the specific question(s) we wanted to answer? Does polypharmacy affect patient outcomes in type 2 diabetes? What did we find? Polypharmacy in rural Montana is linked to higher microvascular complication rates. What are the implications of our findings? Medication count is not only a sign of disease burden but is a modifiable risk factor.