Designing a treatment path for a patient suffering from mul-
tiple conditions involves merging and applying multiple clin-
ical guidelines and is recognised as a difficult task. This is
especially relevant in the treatment of patients with multiple
chronic diseases, such as chronic obstructive pulmonary dis-
ease, because of the high risk of any treatment change having
potentially lethal exacerbations. Clinical guidelines are typi-
cally designed to assist a clinician in treating a single condi-
tion with no general method for integrating them. Addition-
ally, guidelines for different conditions may contain mutually
conflicting recommendations with certain actions potentially
leading to adverse effects. Finally, individual patient prefer-
ences need to be respected when making decisions.
In this work we present a description of an integrated frame-
work and a system to execute conflicting clinical guideline
recommendations by taking into account patient specific in-
formation and preferences of various parties. Overall, our
framework combines a patient’s electronic health record data
with clinical guideline representation to obtain personalised
recommendations, uses computational argumentation tech-
niques to resolve conflicts among recommendations while re-
specting preferences of various parties involved, if any, and
yields conflict-free recommendations that are inspectable and
explainable. The system implementing our framework will
allow for continuous learning by taking feedback from the
decision makers and integrating it within its pipeline.