Journal of Health & Medical Informatics

A Knowledge-Base of Prevalent Diseases in Sunyani Municipality, Ghana Using Ontological Engineering

Abstract

Stephen Appiah*, Adebayo Felix Adekoya, Crispin Bapuuroh, Christian Akowua-Kwakye

Several works in healthcare diseases support systems in recent time are being inspired by a lot of semantic web technology. Specifically, there has been a rise in the number of knowledgebase system that has been developed using ontological engineering. For two decades, Sunyani Municipality records a lump number of diseases with a few such as Typhoid Fever, Malaria, Diarrhoea Diseases, Pneumonia, Anaemia, and so on being prevalent. Healthcare systems in the Municipal do not have a centralised knowledge base for these prevalent diseases, hence the need for a centralised knowledge-based system. This study proposes a knowledge-based system using ontological engineering to assist the formulation of a strong foundation for establishing a meaningful decision-making support system for the proper diagnosis and management of these diseases in the Municipality. We analysis 3,377,403 number of cases from 2013- 2017 and thereafter categorised the case into different classes of diseases. Using a threshold ratio of +1% between several cases for a particular disease (Pdc) and total number cases in its category (Cr), we characterised about thirtyfive (35) diseases as prevalent. Consequently, we designed a robust knowledge-based for the identified prevalent diseases by adopting the Cyc method, which includes three processes in connection with ontological engineering technique. The system was well rated of about 77% after staff from two primary health facilities in the municipality.