Comparative review of big data analytics and GIS in healthcare decision-making
Odunayo Josephine Akindote, Abimbola Oluwatoyin Adegbite, Samuel Onimisi Dawodu, Adedolapo Omotosho, Anthony Anyanwu, Chinedu Paschal Maduka
Abstract
This research explores the confluence of big data analytics and Geographic information systems (GIS) in healthcare decision-making. The comparative review delineates the unique strengths of each technology, showcasing potential synergies. Big data analytics harnesses advanced analytics for predictive modeling and clinical decision support, while GIS introduces a spatial context for health data analysis. Future trends suggest integrations with artificial intelligence, real-time analytics, and wearable technology. However, challenges encompass data privacy, biases, and interdisciplinary collaboration. Ethical considerations emphasize transparency, informed consent, and the responsible use of patient data. As these technologies evolve, their seamless integration holds the promise of precision health, community-oriented interventions, and proactive pandemic response, reshaping the landscape of healthcare decision-making.