SBIR/STTR Research Award

SBIR Phase I: System for Patient Risk Stratification through Electronic Health Record Analytics

Award identifier 6eded7e631358d66a4e3d961543d09e1c593caba875beba9ff71af230e944bd4Awarding agency National Science Foundation

Award amount

$150,000

Program and phase

SBIR · Phase I

Award year

2014

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
RADIAL ANALYTICS INC
Proposal award date
2014-07-01
Contract end date
2015-06-30
UEI
ZBS2LJQK34K5
Solicitation number
Not reported
Topic code
SH

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project focuses on using analytics and technology to drive greater efficiency and effectiveness in healthcare. Recent legislative changes are driving all players within the healthcare ecosystem toward greater accountability. This Phase I project specifically includes technologies to automatically assess patient risk and thereby reduce post-discharge readmissions rates. This Phase I project has the potential to support a broad range of customers across both the provider and the payer landscape, by providing cost-effective readmissions control solutions that respond to new legislative pressures. In terms of commercial potential, the Institute of Medicine of the National Academies has estimated that preventable hospital readmissions account for $20 billion/year in wasteful healthcare spending. The addressable market for the proposed Phase I proof-of-concept for patient risk stratification to support readmission control is approximately $100MM. In the future, this research project will serve as a foundation to support broader population health analytics, the addressable market for which exceeds $500MM/year and is growing at a rate of 24% annually. The proposed project aims to develop a data mining system to capture and analyze information from electronic medical records in order to risk-stratify patients after they have been discharged from hospital. Leveraging interoperability standards that are required by federal regulation, the system will seamlessly aggregate data from multiple electronic medical record systems in a vendor-agnostic manner. A custom analytics engine will detect emergent patterns and draw inferences about each patient?s risk of readmission. If successful, this research will validate the end-to-end concept and suggest the broader applicability of this approach to some of the greatest challenges in population health.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

5 SBIR/STTR records share this UEI (2014–2022). Reported award amounts total $2,225,832. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Science Foundation, Department of Health and Human Services

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

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