Context

Maternal mortality reflects the level of development in a society and involves various social and familial factors. In 2000, the UN established the goal of Improving Maternal Health within the Millennium Development Goals (MDGs), aiming to reduce maternal mortality rate (MMR) by 75% between 1990 and 2015. However, this goal was not achieved.

Currently, the Good Health and Well-Being goal within the Sustainable Development Goals (SDGs) seeks to reduce MMR to less than 70 per 100,000 live births by 2030. This issue disproportionately affects developing countries, with Latin America and the Caribbean experiencing stagnation at 67.2 maternal deaths per 100,000 live births.

To contribute to the analysis and solution of this problem through data science and artificial intelligence, we developed this synthetic patient dataset as part of the project "Computational Phenotypes of Maternal Morbidity Using AI".

 

Torres-Silva, EA, Laura Herrera Almanza, Carolina Crispin Fory, Juan José Gaviria Jimenez, Ana María Guevara Zambrano, Briam Jimenez Franco, and Florez-Arango, Jose. (2025). Maternal Health in Colombia: Synthetic Data [Data set]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/11094440