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

Abstract

Abstract. 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.

Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications

“…In the application layer, the algorithms of our CDSS are developed with CLP-CPG models. A CLP-CPG model refers to the development of a combined clinical practice guideline for a specific patient with the aid of constraint logic programming (CLP) [ 14 ]. The CLP-CPG model is motivated by the fact that the diagnosis and treatment plan for a specific patient may not be made in consideration of only one CPG; instead, the consideration of combining multiple CPGs is necessary to develop a treatment for patients, especially for those with comorbidity [ 17 ].…”

“…Unfortunately, the development of this model needs to be conducted manually by physicians using a specialized clinical guideline editor instead of automatically by a computer. In [ 14 ], the authors propose a methodology as well as its specific implementation for automatically combining multiple clinical guidelines; however, the data of patients need to be manually entered by physicians.…”