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AIVIS: Next Generation Vigilant Information Seeking Artificial Intelligence-based Clinical Decision Support for Sepsis

Award Number: R42AI177108
ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/07/2023
PERIOD OF PERFORMANCE END DATE: 06/30/2025

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AIVIS: Next Generation Vigilant Information Seeking Artificial Intelligence-based Clinical Decision Support for Sepsis - Abstract Sepsis, a heterogeneous syndrome characterized by whole-body inflammation caused by the body's response to an infection, is the most expensive and deadly condition treated in hospitals, with over 270,000 cases of sepsis-related deaths in the U.S. alone. The cornerstones of optimal sepsis care are early recognition accompanied by appropriate antimicrobial therapy, and use of evidence-based hemodynamic therapies such as fluid resuscitation and vasoactive medications. While data-driven approaches based on machine learning (ML) have shown promise in finding patterns in high-dimensional clinical data to forecast sepsis among hospitalized patients, there are no clinically validated and FDA-approved clinical decision support (CDS) system that can reliably identify patients at risk of developing sepsis. Moreover, existing ML-based solutions are as good as the quality of the data presented to them, and the presence of outliers and missingness can have deleterious effects on their performance. For instance, it has been suggested that such systems are essentially looking over clinician's shoulders-using clinical behavior as the expression of preexisting intuition and suspicion to generate a prediction. As such, there is a critical need for sepsis prediction tools that can effectively use the routinely collected EHR data, assess prediction confidence, and if needed, take necessary steps to gather additional information to reduce prediction uncertainty and improve diagnostic accuracy without significant demand on the end-users. This project aims to assess the clinical utility, safety, and efficacy of a novel uncertainty-aware sepsis prediction system designed and developed in collaboration between UC San Diego Health and Healcisio Inc., a UCSD start-up focused on scalable development and commercialization of advanced analytical systems in critically care settings. The Healcisio system is explicitly designed to improve compliance with the Centers for Medicaid and Medicare Services (CMS) care protocol for sepsis (the SEP1 bundle) and to address the existing delays and variabilities in determining the sepsis onset time, so that life-saving antibiotics and hemodynamic support can be delivered in a timely fashion. To maintain software quality assurance a quality management system (QMS) will be developed to accompany a 510(k) FDA submission package to demonstrate safety and effectiveness. To enhance hospital quality improvement (QI) teams’ ability to measure impact of earlier recognition and SEP-1 bundle compliance, a novel quality measure (SEP1+) and a causal impact analysis tool is introduced. Ultimately, the novel technologies developed and tested under this project will enhance our ability to use advanced analytics to predict adverse events, assess patients’ response to therapy, and optimize and personalize care at the beside through a rapid-cycle ‘learning healthcare system’ framework.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $0 )
2026	2024	CLAIRYON, INC.	9500 GILMAN DRIVE	LA JOLLA	CA	92093	SAN DIEGO	USA	Allergy and Infectious Diseases Research	000	2	2/24/2026	EXTENSION WITH OR WITHOUT FUNDS	$0
2026	2024	CLAIRYON, INC.	9500 GILMAN DRIVE	LA JOLLA	CA	92093	SAN DIEGO	USA	Allergy and Infectious Diseases Research	001	2	3/12/2026	EXTENSION WITH OR WITHOUT FUNDS	$0
														Subtotal = $0

Issue Date FY: 2025 ( Subtotal = $0 )
2025	2023	CLAIRYON, INC.	9500 GILMAN DRIVE	LA JOLLA	CA	92093	SAN DIEGO	USA	Allergy and Infectious Diseases Research	000	1	6/16/2025	NEW	$0
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $1,000,000 )
2024	2024	HEALCISIO INC	3906 CAMINITO CASSIS	SAN DIEGO	CA	92122	SAN DIEGO	USA	Allergy and Infectious Diseases Research	000	2	5/29/2024	EXTENSION WITH OR WITHOUT FUNDS	$1,000,000
														Subtotal = $1,000,000

Issue Date FY: 2023 ( Subtotal = $257,723 )
2023	2023	HEALCISIO, INC.	3906 CAMINITO CASSIS	SAN DIEGO	CA	92122	SAN DIEGO	USA	Allergy and Infectious Diseases Research	000	1	7/7/2023	NEW	$257,723
														Subtotal = $257,723

Grand Total All Awards = $1,257,723

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AIVIS: Next Generation Vigilant Information Seeking Artificial Intelligence-based Clinical Decision Support for Sepsis

Award Number: R42AI177108

ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 07/07/2023

PERIOD OF PERFORMANCE END DATE: 06/30/2025

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