Background: A considerable number of patients receive chelation therapy to treat their coronary artery disease. However, there is no current empirical evidence to support its use.
Aim: To better understand patient's decision-making processes regarding the use of chelation therapy as a treatment for coronary artery disease.
Methods: Based on qualitative interviews with 32 coronary artery disease patients, a taxonomy of decision-related issues, hierarchical decision-model, and survey based on the model were developed. The model was then pilot tested with another group of 30 patients and revised accordingly. The final model was tested with another group of 167 patients (27 current users, 72 previous users, and 68 never users of chelation therapy). The primary examination of the model was to determine the degree to which it successfully identified people who fell within each behavioral group. This was done by dividing the total number of successes by the total number of cases on all paths (or questions in the questionnaire).
Results: The most important elements in the decision to use or not use chelation therapy were: previous experience with or learning about chelation therapy, openness to alternative treatments, satisfaction with current level of (traditional) care, physician opinion regarding chelation therapy, costs associated with chelation therapy, perceived access to chelation therapy provider, current state of health (good or bad), and wanting to do 'all one can' for heart health. When tested, the ability of the model to predict the appropriate outcome was nearly 93%. The most salient junctures in the model that led participants to different behavioral outcomes were: considering using non-traditional treatments; perceptions regarding potential risks and benefits; cost; and believing that using chelation therapy was 'doing all that they can' to help their heart health.
Conclusions: Descriptive decision-modeling is a useful method to depict cardiac patients' decision-making concerning the use of chelation therapy. It can also assist healthcare providers and policy makers in directing interventions and policy aimed at enhancing the use of evidence-based therapies for cardiac patients.
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