The potential use of advanced data analytics in healthcare has seen significant interest in both research and practice. Fundamentally, the contribution of IS and analytics research in healthcare is to identify and assess the impact of interventions that can make a significant difference to the quality and cost of care. The American Heart Association (AHA) recently issued a scientific statement calling for research on heart failure transition care to identify impactful processes and practices. This paper presents our conceptualization of ingress and egress patient flow management to investigate the impact of transition care. The larger research question we attempt to address is: How can we identify and inform impactful transition of care interventions that manage demand uncertainty, and improve resource allocation and utilization, while providing improved quality of care for heart failure patients? We present preliminary results of text-mining and process analytics and discuss our plans for quasi-experimental validation.