Maternal Health Data Innovation and Coordination Hub
Overview
The Maternal Health Data Innovation and Coordination Hub works to strengthen the coordination of new and innovative research and practice efforts in maternal health. The Hub is a multidisciplinary effort bringing together experts in maternal health, biostatistics, and health informatics from the Bloomberg School of Public Health and the School of Medicine at Johns Hopkins University. Colleagues from the Johns Hopkins Biostatistics Center, Technology Innovation Center, Center for Indigenous Health, and Applied Physics Laboratory, as well as the Observational Health Sciences & Informatics (OHDSI) Community at Columbia University will support the work of the Data Hub.
Johns Hopkins University
Contact
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Co-Principal Investigator: Andreea Creanga, MD PhD
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Co-Principal Investigator: Paul Nagy, PhD
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Program Coordinator: Amanda Burgess, MPH
Overarching Goals
Establish the coordination infrastructure to foster communication and collaboration across Maternal Health Research Centers of Excellence and other IMPROVE grantees.
Provide support to Maternal Health Research Centers of Excellence for standardized data collection and analyses using both traditional statistical methods and artificial intelligence/machine learning techniques.
Identify and examine research questions of common interest across multiple Maternal Health Research Centers of Excellence.
Strengthen Maternal Health Research Centers of Excellence affiliates’ data science and innovation capabilities through technical assistance, skills coaching, training, and mentorship.
How We Support Research
Scientific liaisons from the Data Innovation and Coordination Hub will work closely with each of the ten Research Centers and with the National Institutes of Health to facilitate high quality data collection, analysis, and sharing of data and key research findings. The Hub will facilitate the development and utilization of common data elements and research methodologies across Research Centers to generate reliable and comparable results.
Of special interest is standardizing clinical data collection using electronic health records automation with the Observational Medical Outcomes Partnership (OMOP) common data model, which enables large-scale observational research. The Hub will offer training and career development opportunities in data science to Research Centers’ affiliates to further develop their research and data science capacity.
Partner Organizations
- Johns Hopkins Medicine Technology Innovation Center
- Johns Hopkins Applied Physics Laboratory
- Johns Hopkins International Center for Maternal & Newborn Health
- Johns Hopkins Center for Indigenous Health
- Observational Health Data Science & Informatics Community at Columbia University
"Each year tens of thousands of Americans experience severe pregnancy complications, raising the risk of future health concerns such as high blood pressure, diabetes and mental health conditions. Through this grant, we hope to strengthen the data science and innovation capabilities of the Maternal Health Research Centers of Excellence and contribute to their developing and testing of new interventions to prevent and treat pregnancy complications."
