Many poor healthcare outcomes and the majority of wasted healthcare spending can be attributed to bad decision making. It is widely accepted that decision support systems are needed to address this issue, and that machine learning has a key role to play in constructing such systems. However, learning to predict the impact of care decisions is made challenging by the need to scale out to complex populations being managed for complex diseases across complex care networks. We will present some recent work that addresses these challenges.