Authors: Guy Amit; Yizhar Toren; Linda R. Davrath; Eran Toledo; Shimon Abboud
Addresses: Biological Signal Processing Ltd., 22a Wallenberg St. Tel-Aviv 69719, Israel ' Biological Signal Processing Ltd., 22a Wallenberg St. Tel-Aviv 69719, Israel ' Biological Signal Processing Ltd., 22a Wallenberg St. Tel-Aviv 69719, Israel ' Biological Signal Processing Ltd., 22a Wallenberg St. Tel-Aviv 69719, Israel ' Biomedical Engineering Department, Faculty of Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel
Abstract: Exercise ECG testing (EET) has limited accuracy in diagnosing coronary heart disease (CHD). High-frequency QRS (HFQRS) analysis is a new technology that improves the diagnostic performance of EET. We analysed the potential economic and healthcare benefits of HFQRS technology. The changes in utilisation of cardiac imaging tests and expenditures on medical treatment were studied using probabilistic models. A decision tree model was used to assess the expected costs of CHD workup and a prognostic Markov model was used to estimate long-term consequences. The models indicated that compared with EET, HFQRS-based workup results in a reduction in superfluous imaging tests. Analysis of long-term changes indicated a reduction in adverse events among CHD patients, with a decrease in overall medical costs and an increase in quality-adjusted life years. HFQRS technology is a promising tool for diagnosing CHD that may reduce medical costs while providing favourable prognostic outcomes.
Keywords: high-frequency ECG; electrocardiograms; myocardial ischemia; stress testing; coronary heart disease; cost effectiveness; probabilistic modelling; QRS complex; exercise ECG testing; EET; medical imaging; medical diagnosis; cardiac disease; cardiovascular disease.
International Journal of Medical Engineering and Informatics, 2013 Vol.5 No.1, pp.68 - 80
Available online: 25 Jan 2013 *Full-text access for editors Access for subscribers Purchase this article Comment on this article