Multi-level medical knowledge formalization to support medical practice for chronic diseases

Abstract Medical processes combine medical actions which are performed by health care professionals while they observe signs and symptoms and decide about interventions, prescriptions, or tests, in order to deal with the health problem that affects a particular patient. Our research was centered in the representation of knowledge for the purpose of decision making in medical processes for chronic diseases. In order to achieve this objective, we followed three steps: (1) We performed an analysis and comparison of formal languages for procedural knowledge representation from a decision-making perspective. (2) We proposed an intuitive, easy, and effective mechanism of medical knowledge formalization. And, (3) we defined a methodology to model medical processes. Our new formalism to represent knowledge is called the extended Timed Transition Diagram (eTTD) and can be used to describe three basic levels of decision making in a long-term treatment: therapy strategy, dosage, and intolerances. The methodology can be applied manually to build eTTDs from clinical practice guidelines (CPGs) or automatically to construct them using the information available in clinical records about individual, multi-level medical processes. We validated eTTDs with clinical practice guidelines for arterial hypertension. The obtained models can be used as a baseline framework for medical, procedural decision support systems development.