Implementation of Big Data Analytics for Diabetes Management: Needs Assessment in the Rwanda Healthcare System
arXiv:2605.26786v1 Announce Type: cross Abstract: Diabetes is a chronic metabolic disease that can lead to serious health problems if not diagnosed and managed early. Big Data Analytics (BDA) and machine learning offer practical tools for analyzing large health datasets and supporting early detection and better treatment decisions. However, their use in routine clinical practice is still limited. This study examines the readiness of Rwanda's healthcare system to adopt big data analytics for diabetes management. As the country continues to expand its use of electronic medical records and health
The increasing availability of electronic medical records in developing nations like Rwanda, coupled with advancements in AI and big data analytics, creates an opportune moment for assessing their application in healthcare.
This study highlights the global trend of leveraging AI and big data for healthcare, underscoring how even resource-constrained systems are exploring advanced technological solutions to improve public health outcomes.
The focus from theoretical potential of big data in healthcare shifts to practical implementation readiness within specific national healthcare systems, particularly in the Global South.
- · AI/Big Data Healthcare providers
- · Rwandan healthcare system
- · Patients with chronic diseases
- · Digital health infrastructure developers
- · Healthcare systems relying on traditional methods
Rwanda gains insights into the necessary steps and resources to integrate big data analytics for diabetes management.
Successful implementation in Rwanda could serve as a model for other developing nations, accelerating AI adoption in healthcare across the Global South.
This could lead to increased investment in digital health infrastructure and AI talent development in these regions, potentially fostering new economic growth sectors.
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