Use of artificial intelligence in healthcare in South Africa: A scoping review

Abstract

Background: Artificial intelligence (AI) transformed healthcare worldwide and has the potential to address challenges faced in the South African healthcare sector, such as limited public institutional capacity, staff shortages, and variability in skills levels that exacerbate the demand on the healthcare system that can lead to compromised care and patient safety.

Aim: This study aimed to describe how AI, especially machine learning is used in healthcare in South Africa over the last 5 years.

Method: The Joanna Briggs Institute (JBI) methodology for scoping reviews was used. Peer-reviewed articles in English, which were published from 2020 to date were sourced and reviewed using the Population, Concept, Context (PCC) framework.

Results: A total of 35 articles were selected. The results showed a focus on conventional machine learning, a health focus on HIV and/or tuberculosis (TB) and cancer, and a lack of big data in fields other than cancer.

Conclusion: There has been an increase in the use of machine learning in the analysis of health data, but access to big data appears to be a challenge.

Contribution: There is a need to have access to high-quality big data, inclusive policies that promote access to the benefits of using machine learning in healthcare, and AI literacy in the health sector to understand and address ethical implications.