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It is believed that ICT-mediation for home care services increases patient empowerment, independency, self-efficacy and quality of life. Providing elderly people with tailored care services allows us to learn from patient data to predict future care needs. In this article, we demonstrate the contribution of machine learning to homecare services, using data collected by a home care services platform. As an actual case, we show how simulated medication compliance can be measured and modeled using clustering and regression techniques. The approach is validated using data from French nursing home databases. The results show that it is possible to classify situations in elderly healthcare, and schedule resource planning according to expected health problems.