A Constraint Logic Programming Approach to Identifying Inconsistencies in Clinical Practice Guidelines for Patients with Comorbi

This paper describes a novel methodological approach to identifying inconsistencies when concurrently using multiple clinical practice guidelines. We discuss how to construct a formal guideline model using Constraint Logic Programming, chosen for its ability to handle relationships between patient information, diagnoses, and treatment suggestions. We present methods to identify inconsistencies that are manifested by treatment-treatment and treatment-disease interactions associated with comorbidity. Using an open source constraint programming system (ECLiPSe), we demonstrate the ability of our approach to find treatment given incomplete patient data and to identify possible inconsistencies. Key words: Clinical practice guideline, comorbidity, Constraint Logic Programming

• Type: Journal
• Year: 2011
• Where: AIME
• Authors: Martin Michalowski, Marisela Mainegra Hing, Szymon Wilk, Wojtek Michalowski, Ken Farion
• Keywords: AIME 2011, Artificial Intelligence, Clinical Practice Guideline, Constraint Logic Programming, Constraint Programming System