Improving maternal care and newborn health outcomes using advanced data methods
Official title: Leveraging Causal Inference and Machine Learning Methods to Advance Evidence-Based Maternal Care and Improve Newborn Health Outcomes
Funded at Harvard Medical School · NIH-11023089 · Data updated 2026-11-12
This study is looking at how using smart data techniques can help improve care for mothers and their newborns in the U.S., especially for those who might not have the same access to healthcare, and it aims to find the best ways to support them with effective policies and practices.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Harvard Medical School NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | March 1, 2023 |
| Project end | February 28, 2027 |
| Funding year | 2025 |
| Award (this year) | $53,974 |
| NIH project number | 5F30HD111284-03 |
| Project ID | NIH-11023089 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include pregnant women, especially those from racial and ethnic minorities or low socioeconomic backgrounds, who may face barriers to accessing adequate maternal care.
✕Less likely to help
Patients who are not pregnant or those who do not have access to maternal health services may not benefit from this research.
What this research studies
This research investigates how causal inference and machine learning can enhance maternal care and newborn health outcomes in the U.S., particularly for vulnerable populations. It aims to generate evidence-based policies that address disparities in access to care and improve the effectiveness of maternal health interventions. The study will focus on evaluating the impact of specific policies, such as providing immediate postpartum contraception and improving fetal surveillance, to ensure that care is both accessible and beneficial. By analyzing existing data and outcomes, the research seeks to identify the best practices for maternal health that can lead to better newborn health.
Why it matters
Potential benefit: If successful, this research could lead to improved health outcomes for newborns and better maternal care practices, particularly for at-risk populations.
How similar studies have gone: Other research has shown success in using data-driven approaches to improve maternal and newborn health outcomes, indicating that this methodology is promising.
Where this research is happening
-
Harvard Medical School
Boston, United States Active
Researchers
- Principal investigator: Vatsa, Rajet — Harvard Medical School
- Study coordinator: Vatsa, Rajet
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.