Introduction: Heart failure (HF) is a major public health concern, prevalent in millions of people worldwide. The most widely-used HF diagnostic method, echocardiography, incurs a decreased diagnostic accuracy for heart failure disease progression when patients are asymptomatic compared to those who are symptomatic. The purpose of this study is to conduct a cost-effectiveness analysis of heart failure diagnosis comparing echocardiography to a novel myocardial strain assessment (Fast-SENC), which utilizes cardiac-Tagged magnetic resonance imaging. Methods: We develop two models, one from the perspective of payers and one from the perspective of purchasers (hospitals). The payer model is a cost-effectiveness model composed of a 1-year short-Term model and a lifetime horizon model. The hospital/purchaser model is a cost impact model where expected costs are calculated by multiplying cost estimates of each subcomponent by the accompanying probability. Results: The payer model shows lower healthcare costs for Fast-SENC in comparison to ECHO ($24,647 vs. $39,097) and a lifetime savings of 37% when utilizing Fast-SENC. Similarly, the hospital model revealed that the total cost per HF patient visit is $184 for ECHO and $209 for Fast-SENC, which results in hospital contribution margins of $81 and $115, respectively. Conclusions: Fast-SENC is associated with higher quality-Adjusted life years and lower accumulated expected healthcare costs than echocardiogram patients. Fast-SENC also shows a significant short-Term and lifetime cost-savings difference and a higher hospital contribution margin when compared to echocardiography. These results suggest that early discovery of heart failure with methods like Fast-SENC can be cost-effective when followed by the appropriate treatment.
CITATION STYLE
Schneider, J. E., & Stojanovic, I. (2019). Economic evaluation of cardiac magnetic resonance with fast-SENC in the diagnosis and management of early heart failure. Health Economics Review, 9(1). https://doi.org/10.1186/s13561-019-0229-7
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