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2233743

Cooperative Agreement

Overview

Grant Description
SBIR Phase II: Improved Maternal Health with Predictive Patient Monitoring - The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to develop further a predictive model for health providers to address the life-threatening condition of preeclampsia in pregnant and postpartum patients. Preeclampsia affects 1 in 20 births, or 150,000 women in the U.S. each year. Not only does preeclampsia cost 70,000 lives globally each year, it is also an expensive burden for healthcare systems. It costs nearly three times more to treat a patient with preeclampsia than one without this complication.

When deployed at scale, the technology proposed in this SBIR grant could be a key factor to reducing maternal mortality in the United States, improving obstetric patient outcomes, reducing the cost of obstetric care, and helping to reduce health disparities. The proposed project will research and develop a method to potentially detect preeclampsia. Preeclampsia is a hypertensive disorder of pregnancy. This dangerous condition also costs the U.S. healthcare system $2.18 billion per year or one-third of the total amount spent on maternal healthcare in our country.

Research objectives include optimizing a machine learning model, integrating patient-facing software into electronic health records systems, implementing the predictive model for preeclampsia, integrating with peripheral wellness devices, developing reminder notification mechanisms, determining appropriate interface enhancements, and defining commercialization and regulatory strategies.

Improving maternal health outcomes advances the general health and welfare of American families and can improve our country's economic competitiveness on the world stage. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH PHASE II (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE II", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF22552
Awarding / Funding Agency
Place of Performance
Tucson, Arizona 85747-9192 United States
Geographic Scope
Single Zip Code
Related Opportunity
22-552
Analysis Notes
Amendment Since initial award the End Date has been extended from 05/31/25 to 11/30/25 and the total obligations have increased 21% from $975,040 to $1,176,040.
Emagine Solutions Technology was awarded Cooperative Agreement 2233743 worth $1,176,040 from National Science Foundation in June 2023 with work to be completed primarily in Tucson Arizona United States. The grant has a duration of 2 years 5 months and was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.

SBIR Details

Research Type
SBIR Phase II
Title
SBIR Phase II:Improved Maternal Health with Predictive Patient Monitoring
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to develop further a predictive model for health providers to address the life-threatening condition of preeclampsia in pregnant and postpartum patients. Preeclampsia affects 1 in 20 births, or 150,000 women in the U.S. each year. Not only does Preeclampsia cost 70,000 lives globally each year, it is also an expensive burden for healthcare systems.It costs nearly three times more to treat a patient with preeclampsia than one without this complication. When deployed at scale, the technology proposed in this SBIR grant could be a key factor to reducing maternal mortality in the United States, improving obstetric patient outcomes, reducing the cost of obstetric care, and helping to reduce health disparities._x000D_ _x000D_ The proposed project will research and develop a method to potentially detect preeclampsia. Preeclampsia is a hypertensive disorder of pregnancy. This dangerous condition also costs the U.S. healthcare system $2.18 billion per year or one-third of the total amount spent on maternal healthcare in our country. Research objectives include optimizing a machine learning model, integrating patient-facing software into Electronic Health Records systems, implementing the predictive model for preeclampsia, integrating with peripheral wellness devices, developing reminder notification mechanisms, determining appropriate interface enhancements, and defining commercialization and regulatory strategies.Improving maternal health outcomes advances the general health and welfare of American families and can improve our country’s economic competitiveness on the world stage._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
DH
Solicitation Number
NSF 22-552

Status
(Complete)

Last Modified 3/21/24

Period of Performance
6/15/23
Start Date
11/30/25
End Date
100% Complete

Funding Split
$1.2M
Federal Obligation
$0.0
Non-Federal Obligation
$1.2M
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to 2233743

Transaction History

Modifications to 2233743

Additional Detail

Award ID FAIN
2233743
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
PCYMLAVZ7MN3
Awardee CAGE
805K0
Performance District
AZ-06
Senators
Kyrsten Sinema
Mark Kelly

Budget Funding

Federal Account Budget Subfunction Object Class Total Percentage
Research and Related Activities, National Science Foundation (049-0100) General science and basic research Grants, subsidies, and contributions (41.0) $981,040 100%
Modified: 3/21/24