Interoperability of Botswana’s healthcare systems using semantic prescription ontologies

Eunice Chinatu Okon, Tshiamo Sigwele, Galani Malatsi, Tshepiso Mokgetse, Hlomani Hlomani


The developing country of Botswana’s health information system faces interoperability challenges mainly due to the lack of shared patient medical data and histories between private and public healthcare providers, which leads to increased medical errors, increased healthcare costs, and potentially fatal outcomes. This research proposes an intelligent electronic prescription ontology (IEPO) framework to share Botswana’s patient electronic health records (EHRs) between private and public healthcare systems for a standardized and semantically rich data exchange. IEPO was evaluated for interoperability using the recall metric for completeness to capture the degree of all relevant information for exchange and the precision metric for accuracy performance to gauge the degree of error minimization during interoperability. The harmonic means of precision and recall called the F1- score, offered the overall interoperability performance. IEPO outperformed related works by 75% in recall, 54% in precision, and 76% in F1-score, demonstrating improved interoperability performance. Furthermore, IEPO was evaluated for correctness and expressiveness through competency questions via queries, results confirming correct and expressive responses.


Botswana healthcare system; Electronic health records; Electronic prescription; Healthcare interoperability; Medical errors; Ontologies; Semantic web

Full Text:




  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics