Improving Adherence to Heart Failure Management Guidelines via Abductive
  Reasoning
  Management of chronic diseases such as heart failure (HF) is a major public
health problem. A standard approach to managing chronic diseases by medical
community is to have a committee of experts develop guidelines that all
physicians should follow. Due to their complexity, these guidelines are
difficult to implement and are adopted slowly by the medical community at
large. We have developed a physician advisory system that codes the entire set
of clinical practice guidelines for managing HF using answer set
programming(ASP). In this paper we show how abductive reasoning can be deployed
to find missing symptoms and conditions that the patient must exhibit in order
for a treatment prescribed by a physician to work effectively. Thus, if a
physician does not make an appropriate recommendation or makes a non-adherent
recommendation, our system will advise the physician about symptoms and
conditions that must be in effect for that recommendation to apply. It is under
consideration for acceptance in TPLP.
