Home 🎓 Towards blended care: Tailored and adaptive coaching for Cardiac Rehabilitation
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🎓 Towards blended care: Tailored and adaptive coaching for Cardiac Rehabilitation

The number of cardiac patients (people with heart problems) is growing all the time. Given that any person who encounters a cardiac condition should undergo cardiac rehabilitation (CR), a program to rehabilitate the heart and learn to manage it in daily life, it is expected that the health system will also grow exponentially in order to meet the high care demand. However, this is not the case. Currently, only 28 percent of the eligible patients get referred to CR because the health system does not have the capacity to include all of them (Van Engen-Verheul et al., 2012). Moreover, the full take-in and supervision of the cardiac patients in CR lead them to find the transition to their daily life after finishing CR quite hard.

One solution to tackle this problem is to delegate some of the care parts at home, called blended care, so that more patients can enter CR while learning to manage their condition early on.

However, there are two main problems concerning this structural change in CR care. First, because of the loss of frequent contact with health professionals, implementing blended care risks losing personalization in care.Secondly, when delegating care at home, health professionals lose insights and feedback into the care delivered at home. Therefore, patient health outcomes might become compromised. In this regard, this project proposes a design concept to support the blended CR care for the patient (with an app) and physiotherapist (with a dashboard) by homogenizing the care delivered at home and the CR center while centralizing the patients by making them active and responsible for their care. Moreover, it personalizes the CR care path, not in terms of exercises or changes in the workflow, but in a way that makes sense to the patient following their CR interests. The concept is composed of an intelligent solution with three different modules that utilize the feedback loops integrated into it to understand the patients’ input and adapt to them, realizing the personalization effect.

The first module concerns the personal goals that patients need to set as they enter the care path and explains the motivation and type of the goal the patient wants to achieve. The second module aims to engage the patients with their exertion data during the care path (a subjective score from six to twenty with which patients report how heavy they find an activity) by helping them actively reflect on their performance and goals to take necessary actions. It realizes this effect by understanding their exertion zones and asking patients subsequent questions to make sense of the data via a quick check-in after rehabilitation. The third module uses the outcomes of the previous modules to provide personalised insights and advice.

Master Thesis: TU Delft repository

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