Providing appropriate support for the most vulnerable individuals carries enormous societal significance and economic burden. Yet, finding the right balance between costs, estimated effectiveness and the experience of the care recipient is a daunting task that requires considering vast amount of information. We present a system that helps care teams choose the optimal combination of providers for a set of services. We draw from techniques in Open Data processing, semantic processing, faceted exploration, visual analytics, transportation analytics and multi-objective optimization. We present an implementation of the system using data from New York City and illustrate the feasibility these technologies to guide care workers in care planning.