Decision Support Tool for Revascularisation Options in Coronary Artery Disease

研究简介（原文）

Together with patients and healthcare professionals, we want to design a Decision Support Tool (DST) that will help people with coronary artery disease to understand and choose treatments that best reflect their preferences and values. Coronary artery disease (CAD) is a leading cause of death. Blood vessels supplying oxygen to the heart muscle become narrowed by a gradual build-up of fatty material. This can result in heart attacks, heart failure, and sudden death. One way to treat the blockage is by inserting an inner sleeve called a "stent" into the blood vessel and clearing the blockage by forcing it into the artery wall. Another method involves diverting the blood supply around the blockage using a vessel harvested from another body site; this is called "bypass surgery". The best treatment, either stents or surgery, is different for everyone. A Decision Support Tool (DST) will provide key information on the pros and cons of stents or surgery and how these match an individual's preferences and values. People are then empowered to make shared decisions about treatment with their doctors. Personalising treatment decisions in this way can reduce inequalities in care and improve shared decision making. Our proposed research will develop a DST in the form of a webpage with alternative print material for those at risk of digital poverty. The DST will be developed in multiple languages to improve accessibility. There are two parts to the study: the first part will use the experience of patients, who have already had stent or surgery, and healthcare professionals to design and refine a DST prototype; this will be done through workshops, focus groups, and cognitive interviews. The second part will test whether it is possible to use the DST by people with CAD waiting for a procedure; this will be done through questionnaires and interviews. The result of this study can then subsequently inform an assessment of the refined DST on a national level, with the hopes of enabling more effective shared decision making.

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