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Management of chronic diseases such as heart failure, diabetes, and chronicobstructive pulmonary disease (COPD) is a major problem in health care. Astandard approach that the medical community has devised to manage widelyprevalent chronic diseases such as chronic heart failure (CHF) is to have acommittee of experts develop guidelines that all physicians should follow.These guidelines typically consist of a series of complex rules that makerecommendations based on a patient's information. Due to their complexity,often the guidelines are either ignored or not complied with at all, which canresult in poor medical practices. It is not even clear whether it is humanlypossible to follow these guidelines due to their length and complexity. In thecase of CHF management, the guidelines run nearly 80 pages. In this paper wedescribe a physician-advisory system for CHF management that codes the entireset of clinical practice guidelines for CHF using answer set programming. Ourapproach is based on developing reasoning templates (that we call knowledgepatterns) and using these patterns to systemically code the clinical guidelinesfor CHF as ASP rules. Use of the knowledge patterns greatly facilitates thedevelopment of our system. Given a patient's medical information, our systemgenerates a recommendation for treatment just as a human physician would, usingthe guidelines. Our system will work even in the presence of incompleteinformation. Our work makes two contributions: (i) it shows that highly complexguidelines can be successfully coded as ASP rules, and (ii) it develops aseries of knowledge patterns that facilitate the coding of knowledge expressedin a natural language and that can be used for other application domains. Thispaper is under consideration for acceptance in TPLP.

A Physician Advisory System for Chronic Heart Failure Management Based on Knowledge Patterns