Strengthening Health Data Systems for Evidence-Based Policy

India is implementing the world’s largest public health insurance program, Ayushman Bharat, which aims to cover over 600 million beneficiaries. Odisha, which ranks 16th among Indian states in health indices with an infant mortality rate of 36 per 1,000 live births and a maternal mortality ratio of 136 per 100,000 live births, faces unique challenges in healthcare delivery due to its geography and socioeconomic factors. As the state prepares for Ayushman Bharat implementation alongside its own Gopabandhu Jan Arogya Yojana (GJAY) that aims for universal health coverage, robust health information systems have become essential for effective policy planning, resource allocation, and monitoring healthcare access across its 30 districts, particularly for the 83% of the population living in rural areas.

DPIC is working with the Department of Health and Family Welfare to enhance data analytics capabilities and strengthen evidence-based decision-making. This collaboration focuses on two key areas: comprehensive analysis of healthcare utilization patterns and scheme efficiency under GJAY and examining data systems for immunization and vital statistics. By bringing analytical rigour to these critical domains, DPIC aims to support the state government in developing more responsive and effective health policies that address the needs of all communities, particularly vulnerable populations in rural and underserved areas.

Our approach employs comprehensive data assessment methodologies to identify opportunities for system enhancement. For the GJAY analysis, DPIC has conducted a thorough review of publicly available data resources while requesting administrative data for deeper insights into healthcare utilization patterns, socioeconomic dimensions of access, and health system capacity. The immunization data work involves examining relationships between various data sources, including population projections, birth registration records, and health management information systems. This methodical assessment helps identify data discrepancies and opportunities for system integration that can strengthen planning and monitoring frameworks.

As this work progresses, several opportunities have emerged for strengthening Odisha’s health data ecosystem. Potential areas for exploration include developing integrated dashboards that connect utilization patterns with health outcomes, designing analytical tools to identify coverage gaps and use of machine learning and AI tools for improved diagnostics, disease prediction and personalized health care. By building more robust health information systems, DPIC’s work contributes to Odisha’s journey toward achieving better health outcomes for all its citizens.