Cost and resource utilization associated with use of computed tomography to evaluate chest pain in the emergency department: the Rule Out Myocardial Infarction using Computer Assisted Tomography (ROMICAT) study.
Academic Article
Overview
abstract
BACKGROUND: Coronary computed tomographic angiography (cCTA) allows rapid, noninvasive exclusion of obstructive coronary artery disease (CAD). However, concern exists whether implementation of cCTA in the assessment of patients presenting to the emergency department with acute chest pain will lead to increased downstream testing and costs compared with alternative strategies. Our aim was to compare observed actual costs of usual care (UC) with projected costs of a strategy including early cCTA in the evaluation of patients with acute chest pain in the Rule Out Myocardial Infarction Using Computer Assisted Tomography I (ROMICAT I) study. METHODS AND RESULTS: We compared cost and hospital length of stay of UC observed among 368 patients enrolled in the ROMICAT I study with projected costs of management based on cCTA. Costs of UC were determined by an electronic cost accounting system. Notably, UC was not influenced by cCTA results because patients and caregivers were blinded to the cCTA results. Costs after early implementation of cCTA were estimated assuming changes in management based on cCTA findings of the presence and severity of CAD. Sensitivity analysis was used to test the influence of key variables on both outcomes and costs. We determined that in comparison with UC, cCTA-guided triage, whereby patients with no CAD are discharged, could reduce total hospital costs by 23% (P<0.001). However, when the prevalence of obstructive CAD increases, index hospitalization cost increases such that when the prevalence of ≥ 50% stenosis is >28% to 33%, the use of cCTA becomes more costly than UC. CONCLUSIONS: cCTA may be a cost-saving tool in acute chest pain populations that have a prevalence of potentially obstructive CAD <30%. However, increased cost would be anticipated in populations with higher prevalence of disease.
