Filtering clinical guideline interactions with pre-conditions: A case study on diabetes guideline

Clinical Guidelines are meant to support healthcare providers to offer a better service via evidence-based recommendations that apply according to certain circumstances given a certain disease or condition. However, the high number of recommendations in a single guideline makes it humanly impossible to verify for all possible interactions. The goal of this work is twofold: (i) to analyse pros and cons of formalising a real guideline using the TMR model and then (ii) to infer interaction among (some of) the recommendations from the the Scottish Guideline on Diabetes. To this end we extend the TMR Model to formalize the pre-conditions that define in which circumstances a recommendations may apply and we implemented the reasoning in SWI-Prolog. The results show that (i) properly formalising the diabetes guideline is a cross-disciplinary task that requires both the formalisation know-how and the medical background; and (ii) indeed the diabetes guideline presents conflicting recommendations which can be automatically detected provided the suitable modeling and background knowledge. It is reasonable to conclude that these conclusions hold for other guidelines too.