# Maternal Health Data Innovation and Coordination Hub

> **NIH NIH U24** · JOHNS HOPKINS UNIVERSITY · 2024 · $1,957,470

## Abstract

Project Summary
The Johns Hopkins University (JHU) seeks to strengthen the coordination of innovative research and practice
efforts in maternal health through collaboration with the National Institutes of Health (NIH) and
their Implementing a Maternal Health and Pregnancy Outcomes Vision for Everyone (IMPROVE) initiative
grantees. The overarching goals of this project are to establish and maintain a Maternal Health Data Innovation
and Coordination Hub to support Maternal Health Research Centers of Excellence, and to facilitate the reuse
of the data they generate. The project will be implemented by a multidisciplinary team of maternal health
experts and biostatisticians at JHU’s Bloomberg School of Public Health, and informatics and data science
specialists at JHU’s School of Medicine, with support from an Experts’ Bureau comprised of subject matter
experts in health equity, bioethics, health economics, patient safety, patient and family engagement in
research. Key project activities are to establish and maintain a secure, cloud-based coordination platform with
controlled access, and a public-facing Data Hub website; develop common data elements using a modified
Delphi approach; support the use of a common data model; provide data collection and analysis tools with
integrated quality assurance workflows; provide support for statistical analyses using traditional and artificial
intelligence/machine learning techniques; prepare and share data with NIH repositories; provide technical
assistance and skills coaching, training, and professional development opportunities to Research
Centers/IMPROVE grantees. Our proposal has technical and conceptual areas of innovation. Most notably, the
proposed integration of the Data Hub with an existing research coordination platform with demonstrated
feasibility -- JHU’s Precision Medicine Analytics Platform (PMAP). It utilizes the Observational Health Data
Science and Informatics (OHDSI) open-source community and the Observational Medical Outcomes
Partnership (OMOP), employed by large NIH-funded research. OMOP is based upon standard clinical
terminologies; enables extraction, ingestion, collation of variables of interest into an observational research
registry; and has the capability for data storage, security, analysis, and transfer among participating sites. Also
innovative are the proposed training and career development opportunities, including tuition scholarships, data
challenge awards, and a mentorship program. We anticipate that these activities will lead to short-term and
intermediate outcomes (e.g. improved data science capabilities; generation of findable, accessible,
interoperable, and reusable data), which, over the long-term, will advance research to improve maternal health
outcomes and promote equity. Process and outcomes evaluations will ascertain the extent to which our project
is successfully supporting Research Centers. Data science methods and findings from research projects will be
disseminated...

## Key facts

- **NIH application ID:** 10901905
- **Project number:** 5U24HD113136-02
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Andreea Alina Creanga
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,957,470
- **Award type:** 5
- **Project period:** 2023-08-15 → 2030-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10901905

## Citation

> US National Institutes of Health, RePORTER application 10901905, Maternal Health Data Innovation and Coordination Hub (5U24HD113136-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10901905. Licensed CC0.

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