Data Analysis & Safety/Risk Considerations - The investigators will use generalized linear models to test the primary and secondary hypotheses (McCullagh and Nelder, 1989). Logistic generalizations of the traditional, multivariate GLM are appropriate when the dependent variable is binary and the probability of an event is modeled, as is the case with adherence in this study. When the dependent variable is a count, a commonly used generalized model uses the natural logarithm of the count, as with re-hospitalizations and ED visits in this study. In compliance with NIH guidelines for data safety and monitoring activities, a number of quality control steps will be used to ensure the on-going safety of participants and the scientific integrity of this feasibility intervention study. The proposed study poses only very minimal risks to participants. All participants will receive usual care. Participation in the study will not replace patients' regular health care attention. Data safety will be monitored by the PI, the Data Safety Officer (Dr. Karl Swedberg), and the study co-investigators. Any adverse events will be reported immediately to the Duke IRB and the NIH.