Abstract
Routine Health Information Systems (RHISs) continuously need to be evaluated and
modernised to improve their relevance and ability to respond to public health issues. In the
provision of Environmental Health Services (EHS) in South Africa, the Environmental Health
Information System (EHIS) under the District Health Information System (DHIS) needs to be
strengthened to spot trends of exposure to environmental stressors in communities and use data
to provide evidence-based interventions. Moreover, EHS in South Africa has been noted to
lack a data science approach driven by an effective EHIS.
This study evaluated the EHIS in South Africa using municipalities that provide EHS in the
province of KwaZulu-Natal as a case study, and developed a framework for a digital system as
a research intervention. An explanatory sequential mixed methods research design was used to
achieve this aim. This study was divided into three phases that entailed a quantitative phase,
a qualitative phase, and a Delphi study to validate and refine the research intervention.
This study was conducted in 11 municipalities that provided EHS in the KwaZulu-Natal
Province, South Africa. The study started with a quantitative phase, whereby data were
collected through a self-administered questionnaire from 105 environmental health
practitioners (EHPs) who were conveniently sampled from a population of 228. The
quantitative phase also entailed document reviews where a data extraction sheet was used to
guide the extraction of data from the documents of the 11 targeted municipalities. When the
quantitative phase was completed, a qualitative phase followed, and 10 purposively selected
environmental health managers were interviewed from a population of 42. This phase used a
semi-structured interview guide as a data collection instrument. In terms of data analysis, for
quantitative data, descriptive and inferential statistical methods were followed using IBM SPSS
Statistics 29.0. For qualitative data, deductive and inductive thematic analysis methods were
followed using the ATLAS.ti software version 24.0.0.29576. Data from both phases were
integrated at the interpretation and reporting level through a narrative-weaving approach to
derive the joint findings of this study.
Approval for this study was obtained from the Faculty of Health Science’s Research Ethics
Committee (REC-2469-2023) and the Higher Degrees Committee (HDC-01-94-2023) at the
ix
University of Johannesburg. Permission to access the municipalities was received from the
South African Local Government Association, as well as the management of the municipalities
that participated.
The results of this study found a dire need for the improvement and modernisation of
environmental health data management and information utilisation to change the way EHPs
work, enhance record-keeping, increase efficiency, and promote data-driven decision-making.
Areas of concern included the over-reliance on paper-based data collection tools and storage,
duplication of data and work activities, as well as the lack of adequate smart devices and
technical tools. Capacity-building, quality assurance, data management support and provision
of data feedback were also shown to require improvements. However, it was evident that the
EHPs and their managers were enthusiastic about the utilisation of information for planning
and decision-making as well as collaborations. To demonstrate the power of data-driven
insights, among the EHPs, it was found that when they engaged in data analysis (p<0.001) and
integration (p<0.001), they were more inclined to use the generated information for planning
and decision-making. Data integration was also found to be instrumental in promoting data
analysis (p<0.001) and enabling collaborations (p<0.001).
In response to these findings, a Digital EHIS Framework was developed, refined, and validated
based on input from a panel of eight purposively selected experts who participated in the Delphi
study. The Digital EHIS Framework highlight important factors and processes for a functional
EHIS and for consideration to enhance operational efficiencies, promote data-driven planning
and decision-making and improve the delivery of EHS through digital transformation. As a
result, the Digital EHIS Framework emphasises the adoption of digital technologies and
leveraging presented opportunities to enhance the effectiveness of EHS, reduce the
environmental health burden of disease, and yield better health outcomes in the community.