Developing an ontology for wound management at a hospital

Abstract

This study was coined out in the context of a larger project to develop an integrated decision support system to investigate, how ontology could be used to represent and model clinical knowledge in the area of wound management. The use of ontology to represent clinical knowledge, the issues and challenges are still unclear and this study seeks to identify the use of ontology to represent knowledge and information in decision support systems. This study explores how the medical knowledge could be represented in a knowledge base as ontology. The knowledge base/database was developed by consolidating medical literature and information from the nurses. The overall system developed uses the knowledge base containing information about wounds in particular pressure ulcers in the form of ontology that brings out the concepts, functionalities and relationships between them. The system does not identify the best treatment or action but provides support for nurses in making better decisions that result in better outcomes for patients in the area of pressure ulcers. Ontology's are used to represent knowledge along with their association and relations among them. Ontology could be defined as method of interrelating concepts and relations and providing interpretation of terms combined. Ontology is put together using technology and software which is Onto Studio and is put forth using the representation language FLogic. As ontology combines the relational database and the relations between the concepts, it acts as one of the best methods to represent clinical knowledge. This study provides a guideline for representing clinical knowledge using ontology. During the course of representing clinical knowledge one of the major issues identified was the need for in depth knowledge in the area of wounds. This could be overcome by consolidating knowledge from experts in order to identify the best practices and treatments. This study puts forth a framework that would guide in representing clinical knowledge using ontology.