Ngepah Nicholas, Saba Charles S, Mouteyica Ariane Ephemia Ndzignat, Ohonba Abieyuwa
School of Economics, College of Business and Economics, University of Johannesburg, Auckland Park Kingsway Campus, PO Box 524, Auckland Park, Johannesburg, South Africa.
Global Health. 2025 Jul 28;21(1):41. doi: 10.1186/s12992-025-01135-2.
This study examines the impact of Artificial Intelligence (AI) on maternal mortality in alignment with Sustainable Development Goal (SDG) 3.1, which aims to reduce maternal mortality to below 70 per 100,000 live births by 2030. Despite advancements, maternal mortality remains disproportionately high in developing countries due to weaker healthcare infrastructure.
Using panel data from 70 countries (1990-2022), sourced from WHO's Global Burden of Disease (GBD), World Bank's World Development Indicators (WDI), UNCTAD, and the World Robotics database, we apply the Difference-in-Differences (DiD) approach to assess AI's impact over time and the Auto-Regressive Distributed Lag (ARDL) model to examine short- and long-term effects.
AI adoption significantly reduces maternal mortality, particularly in developing countries, where post-2000 advancements have led to notable declines. ARDL results show that 27% of deviations from long-term maternal mortality trends are corrected annually, highlighting AI's sustained impact. The DiD analysis indicates AI's greatest benefits in resource-limited settings, including improving early diagnostics, personalized care, and remote monitoring. In developed countries, AI's effects are marginal due to existing advanced healthcare systems.
AI presents a transformative solution for reducing maternal mortality, particularly in low-resource settings. Policymakers should prioritize AI-driven healthcare, expand digital infrastructure, and ensure equitable access to maximize its benefits. AI integration is crucial for addressing maternal health disparities and accelerating progress toward SDG 3.1.
本研究结合可持续发展目标3.1，探讨人工智能（AI）对孕产妇死亡率的影响，该目标旨在到2030年将孕产妇死亡率降至每10万活产低于70例。尽管取得了进展，但由于医疗保健基础设施薄弱，发展中国家的孕产妇死亡率仍然过高。
利用来自世界卫生组织全球疾病负担（GBD）、世界银行世界发展指标（WDI）、联合国贸易和发展会议以及世界机器人数据库的70个国家（1990 - 2022年）的面板数据，我们采用差分法（DiD）来评估人工智能随时间的影响，并使用自回归分布滞后（ARDL）模型来检验短期和长期影响。
采用人工智能显著降低了孕产妇死亡率，特别是在发展中国家，2000年后的进步导致了显著下降。ARDL结果表明，每年有27%的孕产妇死亡率与长期趋势的偏差得到纠正，突出了人工智能的持续影响。DiD分析表明，在资源有限的环境中，人工智能的益处最大，包括改善早期诊断、个性化护理和远程监测。在发达国家，由于现有的先进医疗系统，人工智能的影响很小。
人工智能为降低孕产妇死亡率提供了变革性解决方案，特别是在资源匮乏地区。政策制定者应优先考虑人工智能驱动的医疗保健，扩大数字基础设施，并确保公平获取以最大化其益处。人工智能整合对于解决孕产妇健康差距和加速实现可持续发展目标3.1至关重要。
