Confronting "confounding by health system use" in Medicare Part D: comparative effectiveness of propensity score approaches to confounding adjustment

Abstract

Purpose: Under Medicare Part D, patient characteristics influence plan choice, which in turn influences Part D coverage gap entry. We compared predefined propensity score (PS) and high-dimensional propensity score (hdPS) approaches to address such "confounding by health system use" in assessing whether coverage gap entry is associated with cardiovascular events or death.

Methods: We followed 243,079 Medicare patients aged 65+ years with linked prescription, medical, and plan-specific data in 2005-2007. Patients reached the coverage gap and were followed until an event or year's end. Exposed patients were responsible for drug costs in the gap; unexposed patients (patients with non-Part D drug insurance and Part D patients receiving a low-income subsidy) received financial assistance. Exposed patients were 1:1 PS-matched or hdPS-matched to unexposed patients. The PS model included 52 predefined covariates; the hdPS model added 400 empirically identified covariates. Hazard ratios for death and any of five cardiovascular outcomes were compared. In sensitivity analyses, we explored residual confounding using only low-income subsidy patients in the unexposed group.

Results: In unadjusted analyses, exposed patients had no greater hazard of death (HR = 1.00; 95%CI, 0.84-1.20) or other outcomes. PS-matched (HR = 1.29; 0.99-1.66) and hdPS-matched (HR = 1.11; 0.86-1.42) analyses showed elevated but non-significant hazards of death. In sensitivity analyses, the PS analysis showed a protective effect (HR = 0.78; 0.61-0.98), whereas the hdPS analysis (HR = 1.06; 0.82-1.37) confirmed the main hdPS findings.

Conclusion: Although the PS-matched analysis suggested elevated but non-significant hazards of death among patients with no financial assistance during the gap, the hdPS analysis produced lower estimates that were stable across sensitivity analyses.