GGrantIndex
← Search

SBIR Phase I: A software product that empowers healthcare teams with community resource information and facilitates post-treatment care coordination.

$224,935FY2018TIPNSF

Medical Innovators Company, Llc, Houston TX

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to develop and test feasibility of a web-based software and machine learning technology that is able to empower healthcare teams with community resource information as well as facilitate coordination of post-treatment care. Lack of access to community resources such as housing, food and transportation (also known as social determinants of health) has been associated with negative health outcomes such as unplanned hospital readmissions and emergency room visits. This leads to high healthcare costs. Therefore, healthcare teams (i.e. social workers, case managers and discharge planners) spend a significant amount of time to locate appropriate community resources for their patients. Our innovation will leverage a community of healthcare professionals and the resource providers to ultimately find community resources for patients in a faster and less costly manner. The machine learning technology supported by this award will connect healthcare professionals with relevant community resources that ultimately reduces the cost and time associated with this process. A successful implementation of this technology will lead to improved post-treatment care outcomes for the patients and reduced cost of care. The proposed project will develop and test the feasibility of a web-based software platform to empower healthcare professionals to share community resources. Novel machine learning technology will be developed to facilitate appropriate and efficient exchange of community resources. Healthcare professionals using the platform will be able to get onto the platform as well as search and share resources. The machine learning algorithm leverages the relationships of healthcare professionals and resource providers to coordinate community resource sharing. A successful implementation of this algorithm will provide substantial improvements on the ability to acquire timely community resources as compared current methods. The goal of this research is to validate whether the machine learning technology is able to help healthcare professionals identify appropriate community resources.

View original record on NSF Award Search →