  Precision medicine is a promising framework for generating evidence to
improve health and health care. Yet, a gap persists between the ever-growing
number of statistical precision medicine strategies for evidence generation and
implementation in real world clinical settings, and the strategies for closing
this gap will likely be context dependent. In this paper, we consider the
specific context of partial compliance to wound management among patients with
peripheral artery disease. Through the use of a Gaussian process surrogate for
the value function, we expand beyond the common precision medicine task of
learning an optimal dynamic treatment regime to characterization of classes of
dynamic treatment regimes and how those findings can be translated into
clinical contexts.
