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.
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