Aims: The purpose of this study is to assess the economic cost differences and the associated treatment resource changes between the developing coronary artery disease (CAD) diagnostic tool fast strain-encoded cardiac imaging (Fast-SENC) and the current commonly used stress test single-photon emission computed tomography (SPECT).
Materials and methods: A "payer perspective" model was created first, consisting of long-term and short-term components that used a hypothetical cohort of patients of average age (60.8 years) presenting with chest pain and suspected CAD to assess cost-impact. A cost impact model was then built that assessed likely savings from a "hospital perspective" from substituting Fast-SENC for a portion of SPECTs assuming an average number of annual SPECT tests performed in US hospitals.
Results: In the payer model, using Fast-SENC followed by coronary angiography (CA) and percutaneous coronary intervention (PCI) treatment when necessary is less costly than the SPECT method when considering both direct and indirect costs of testing. Expected costs of the Fast-SENC were between $2,510 and $2,632 per correct diagnosis, while expected costs for the SPECT were between $3,157 and $4,078. Fast-SENC reduced false positives by 50% and false negatives by 86%, generating additional cost savings. The hospital model showed total costs per CAD patient visit of $825 for SPECT and $376 for Fast-SENC.
Limitations: Limitations of this study are that clinical data are sourced from other published clinical trials on how CAD diagnostic strategies impact clinical outcome, and that necessary assumptions were made which impact health outcomes.
Conclusion: The lower cost, higher sensitivity and specificity rates, and faster, less burdensome process for detecting CAD patients make Fast-SENC a more capable and economically beneficial stress test than SPECT. The payer model and hospital model demonstrate an alignment between payer and provider economics as Fast-SENC provides monetary savings for patients and resource benefits for hospitals.
Keywords: C50; Coronary artery disease; I15; cardiac magnetic resonance imaging; coronary heart disease; cost impact analysis; hospital value analysis.