RÉSUMÉ
The growing burden of diabetes has long been under the radar in developing countries such as South Africa (SA). In recent years, there has been an unprecedented and exponential increase in recorded and undiagnosed diabetes mellitus (DM) cases. Unreliable data collection, overburdened health systems and poor infrastructure have all proved to be barriers to achieving optimum disease management. The District Health Information System (DHIS) serves as the data collection tool for the SA public healthcare sector. It is used in all nine SA provinces to gather data without individual patient identifiers. Objective. To analyse and compare the DM data collected by the DHIS in the Western Cape (WC), Eastern Cape (EC), KwaZulu-Natal (KZN) and Gauteng provinces of SA. Methods. An audit of diabetes-related data from the DHIS for 2016 was conducted. The data were then analysed using Excel. Time-series and cross-sectional analyses were made possible using pivot tables. Graphics were designed using Thinkcell software. Results. Of the four provinces surveyed, Gauteng recorded the highest incidence of DM, 67% higher than the reported global DM incidence estimate, while the WC had the lowest incidence. A similar pattern was also noted regarding the incidence of DM in people aged <18 years, with Gauteng having the highest and WC the lowest prevalence results. When comparing the number of DM-related consultations conducted in each province, the metropolitan districts were highlighted as hotspots of activity for DM care. This study found a moderate inversely proportional relationship between the incidence of DM in all provinces and education deprivation (p<0.05). Among the provinces that collected data on screening (excluding EC), KZN recorded the highest number of diabetic screenings. Conclusion. Metropolitan areas were highlighted as areas to be targeted, further reinforcing the current connection observed between urbanisation and DM in SA. The presence and recording of screening efforts is an excellent step in the right direction for the SA public healthcare sector and the DHIS. With improved interprovincial co-ordination regarding standardisation of the criteria and specifications of data collection fields, and enhanced training for data officers and primary collection agents, good quality and rich data is a very close possibility.