Why the study?
Does improving exercise ECG accuracy reduce costs and misdiagnoses in patients with suspected CAD?
Does improving exercise ECG accuracy reduce costs and misdiagnoses in patients with suspected CAD?
Improving the sensitivity and specificity of exercise ECG could significantly reduce the costs of CAD management and decrease the number of misdiagnoses.
BACKGROUND: Conventional analysis of exercise electrocardiogram (EX-ECG) has limited accuracy. This study aims to evaluate the potential impact of improving EX-ECG accuracy on costs of diagnosis and number of misdiagnoses of coronary artery disease (CAD). METHODS: A decision-tree model was simulated including sequential application of diagnostic procedures for suspected CAD. The model was structured in two main branches (presence or absence of CAD). A probabilistic sensitivity analysis was then performed for several combinations of improvement in test sensitivity and specificity. RESULTS: A clear trend in cost reduction was observed at improving EX-ECG specificity (about 8-8.5 million dollars, corresponding to a 5.6-7.6% reduction according to the prevalence level). Wrong diagnoses counted for 9-13% of test. Improvements in test parameters lead to reductions in wrong diagnoses, especially when increasing specificity (8.8-12.5%). CONCLUSIONS: A proper improvement in EX-ECG sensitivity and specificity would have a relevant impact on the costs of CAD management, while reducing the number of misdiagnoses.
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Bigi et al. (2010) studied Suspected coronary artery disease (CAD). Improved exercise electrocardiogram (EX-ECG) sensitivity and specificity vs. Conventional analysis of EX-ECG was evaluated on Costs of diagnosis and number of misdiagnoses of CAD.
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