  The health outcomes of high-need patients can be substantially influenced by
the degree of patient engagement in their own care. The role of care managers
includes that of enrolling patients into care programs and keeping them
sufficiently engaged in the program, so that patients can attain various goals.
The attainment of these goals is expected to improve the patients' health
outcomes. In this paper, we present a real world data-driven method and the
behavioral engagement scoring pipeline for scoring the engagement level of a
patient in two regards: (1) Their interest in enrolling into a relevant care
program, and (2) their interest and commitment to program goals. We use this
score to predict a patient's propensity to respond (i.e., to a call for
enrollment into a program, or to an assigned program goal). Using real-world
care management data, we show that our scoring method successfully predicts
patient engagement. We also show that we are able to provide interpretable
insights to care managers, using prototypical patients as a point of reference,
without sacrificing prediction performance.
