Impact of advanced exercise ECG analysis on cost of coronary artery disease management.
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.
Bigi
Riccardo
R
Cardiology, Department of Medicine and Surgery, University School of Medicine, Milan, Italy.
Ferrando
Alberto
A
Pagano
Eva
E
Cortigiani
Lauro
L
Merletti
Franco
F
Fiorentini
Cesare
C
Gregori
Dario
D
D003324:Coronary Artery Disease / Q000175:diagnosis / Q000191:economics*; D003365:Costs and Cost Analysis; D003663:Decision Trees; D019468:Disease Management; D004562:Electrocardiography / Q000379:methods*; D005080:Exercise Test; D006801:Humans; D008962:Models, Theoretical; D009010:Monte Carlo Method