Health Analytics students’ perceptions of learning the applications of data science and health science: A descriptive qualitative study
1
Department of Family Science and Primary Care, University of Witswatersrand, Johannesburg, South Africa
2
School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
Popul. Med. 2026;8(Supplement Supplement 1):
ABSTRACT
BACKGROUND:
Artificial Intelligence (AI) and its applications such as data science and machine learning, are now being readily integrated in different areas, including health systems science. Preparing health science students in a tertiary institute to use and integrate data science is not widely done due to the lack of technical teaching capacity. Concepts such as Artificial Intelligence and its applications are not commonly taught in health sciences curriculum. The aim of this study was to investigate health system science students’ views on learning to use AI concepts in a health science context among postgraduate students. Methods and findings A focus group was conducted among Health Systems Science (HSS) Honours students who had taken the Health Analytics module offered at the Department of Family Medicine and Primary Care (DFMPC), at the University of the Witwatersrand. An inductive, data-driven thematic analysis was conducted. Thematic analysis of participants’ experiences in the health analytics module highlighted a strong motivation to integrate data science with healthcare, particularly as a non-clinical pathway into the sector. Students entered the module with interdisciplinary ambitions shaped by personal constraints, career transitions, and technological curiosity. They emerged with a reshaped professional identity as analysts embedded within health systems. However, their learning was limited by structural and curricular challenges, notably the accelerated block format and limited opportunities for hands-on coding practice.
CONCLUSIONS:
The emergence of new health science professions highlights the importance of integrating AI into tertiary education to produce graduates equipped for evolving workforce demands. Modules such as Health Analytics represent a meaningful step toward this goal. Findings from the focus group revealed strong student interest in such programs, while also highlighting areas for improvement that could strengthen the module and enhance students’ understanding of AI concepts within healthcare systems.
Artificial Intelligence (AI) and its applications such as data science and machine learning, are now being readily integrated in different areas, including health systems science. Preparing health science students in a tertiary institute to use and integrate data science is not widely done due to the lack of technical teaching capacity. Concepts such as Artificial Intelligence and its applications are not commonly taught in health sciences curriculum. The aim of this study was to investigate health system science students’ views on learning to use AI concepts in a health science context among postgraduate students. Methods and findings A focus group was conducted among Health Systems Science (HSS) Honours students who had taken the Health Analytics module offered at the Department of Family Medicine and Primary Care (DFMPC), at the University of the Witwatersrand. An inductive, data-driven thematic analysis was conducted. Thematic analysis of participants’ experiences in the health analytics module highlighted a strong motivation to integrate data science with healthcare, particularly as a non-clinical pathway into the sector. Students entered the module with interdisciplinary ambitions shaped by personal constraints, career transitions, and technological curiosity. They emerged with a reshaped professional identity as analysts embedded within health systems. However, their learning was limited by structural and curricular challenges, notably the accelerated block format and limited opportunities for hands-on coding practice.
CONCLUSIONS:
The emergence of new health science professions highlights the importance of integrating AI into tertiary education to produce graduates equipped for evolving workforce demands. Modules such as Health Analytics represent a meaningful step toward this goal. Findings from the focus group revealed strong student interest in such programs, while also highlighting areas for improvement that could strengthen the module and enhance students’ understanding of AI concepts within healthcare systems.
| eISSN: | 2654-1459 |
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