An Ontology for Tuberculosis Treatment Adherence Behaviour

  • Olukunle A. Ogundele, Deshendran Moodley, Christopher J. Seebregts, Anban W. Pillay
  • January 2015, ACM (Association for Computing Machinery)
  • DOI: 10.1145/2815782.2815803

An Ontology for Tuberculosis Treatment Adherence Behaviour

What is it about?

Poor adherence to prescribed treatment, a significant contributor to tuberculosis patients developing drug resistance and failing treatment, is a complex phenomenon influenced by diverse personal, cultural and socio-economic factors that vary between regions and communities. The knowledge required to build models to accurately predict treatment adherence behaviour is extensive and presents challenges in low resource settings where knowledge and data is scarce. To resolve the knowledge gap, we developed an ontology supported by current scientific literature to categorise, clarify and consolidate influencing factors affecting tuberculosis patients' treatment adherence behaviour in a consistent manner.

Why is it important?

The ontology will support an open, sharable and reusable treatment adherence behaviour knowledge repository to enhance evidence-based decision making for tuberculosis management. In particular the use of the ontology to construct a Bayesian decision network model for particular tuberculosis communities is demonstrated.

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The following have contributed to this page: Dr Olukunle A Ogundele