Abstract
Various decision analytic models exist for evaluating the cost-effectiveness of pharmacological interventions for heart failure (HF). Despite this, studies that explore drivers influencing these modeling approaches remain scarce. Through a systematic review of the literature, the present study sought to identify model drivers that emerge from economic evaluations of HF pharmacological interventions. Among the 72 cost effectiveness papers evaluating HF drug interventions, the most frequently identified, top 5 ranked model drivers impacting the incremental cost-effectiveness ratio (ICER) were cost of treatment and utility, identified in 10% of studies, respectively. Other drivers that emerged as top 5 ranked drivers in > 5% of studies included treatment effect on mortality (or cardiovascular mortality), duration of treatment, and baseline cardiovascular mortality. Model drivers reported at the top of tornado diagrams were treatment effect on mortality or on cardiovascular mortality. Collectively, these observations highlight the key importance of treatment effect in driving cost-effectiveness models for HF.