Health Network Research Group LLC — National Science Foundation STTR Phase I: SH

Description

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase 1 project includes: accelerating the pace of healthcare improvement by making information on high-need/high-cost patients instantly accessible and individually tailored to health care providers; transforming health intervention databases into active and dynamic learning communities about caring for high-need/high-cost patients; reducing the burden on safety net providers to sort and sift through dozens of information sources about delivering care to high-need/high-cost patients. Health Information Networking Tool (HINT) will be a unique combination of customized algorithms that will fill in critical gaps in knowledge, especially around health disparities, the social determinants of health and underserved conditions; boost opportunities for safety net providers to connect with peers to engage in collaborative problem-solving; reduce duplication and repetition of errors and failed interventions across safety net healthcare organizations; increase public recognition for safety net institutions that develop promising interventions; and enable technical advancements in machine learning to suggest models of care for high-need/high-cost patients. The commercial impact for HINT includes: reducing the cost and improving the quality of care delivered to high-need/high cost populations; and creating opportunities for safety net institutions and providers to market their expertise on caring for complex, underserved patients. The proposed project was conceived on the belief that ingenious solutions in caring for society's most vulnerable populations occur daily across the safety net health system; that HINT will accelerate innovation by bringing an unprecedented resource to disseminate voluminous and constantly changing healthcare information; that the proposed information network will reduce the fragmentation of information and duplication in errors and failed interventions that currently occur; and finally that unlocking and disseminating innovations and advice from peers - in similar institutions and caring for similar patients - will accelerate successful practices to improve the health of high-need/high-cost patients. HINT proposes to develop unique crawling, clustering, text mining, collaborative filtering, bipartite matching, and ranking algorithms. The team will integrate the six algorithms into a customized social content management system, and address challenges around design and functionality.