ENHANCING HEALTHCARE MANAGEMENT IN LMICS THROUGH BIG DATA: STRATEGIES FOR DATA QUALITY IMPROVEMENT AND CONTEXTUAL INTEGRATION

The potential of big data to revolutionize healthcare in low- and middle-income countries (LMICs) is hindered by challenges such as limited data availability and poor alignment with local healthcare needs. This study critically analyses the current state of big data in LMIC healthcare and develops a framework to enhance data utility while ensuring contextual relevance and user-friendliness. The methodology involves examining successful big data applications and identifying best practices in data quality improvement, interoperability, and capacity building within digital healthcare systems. The findings offer practical insights for optimising big data analytics in LMICs, addressing issues such as data incompatibility with local healthcare practices and infrastructure constraints. The expected impact includes guiding policymakers and healthcare providers in LMICs towards more effective big data implementations, aiming to improve healthcare delivery and patient outcomes. This study contributes to the advancement of equitable and efficient healthcare systems in LMICs by focusing on tailored, sustainable big data solutions.