Healcisio AI Research : Healcisio Receives Phase II STTR Funding to Continue Critical Care AI Research
Healcisio, a leader in AI and digital healthcare, has recently announced that it has received a $1 million Small Business Technology Transfer (STTR) Phase II award from the National Institute of Allergy and Infectious Diseases (NIAID). This funding will advance the development of Healcisio’s critical care decision support platform and a new AI-powered software suite for abstracting and reporting quality measures.
A Major Milestone
This funding marks a significant milestone for Healcisio. The company has been at the forefront of integrating AI into healthcare, focusing on improving patient outcomes through predictive analytics and quality assessment tools.
Proven Success in Sepsis Management
In a peer-reviewed, prospective implementation study for sepsis AI, Healcisio demonstrated a remarkable reduction in sepsis mortality by 17%. Additionally, they improved SEP-1 bundle compliance by nearly 10%. These results underscore the potential of AI in enhancing clinical decision-making and patient care.
Future Plans
Over the next year, Healcisio plans to expand this work to two additional health systems. They will also deploy new generative AI tools related to quality assessment for in-hospital care of sepsis patients. These efforts aim to streamline quality reporting and reduce the burden on healthcare providers.
CEO’s Perspective
Aaron Boussina, Healcisio’s CEO, emphasized the importance of predictive analytics in healthcare delivery. He stated, “Predictive analytics is an increasingly important part of the healthcare delivery process; however, it’s only one factor in a highly complex system. Maturing how we measure quality and making it efficient is long overdue and can profoundly benefit patients and providers. We think Healcisio’s holistic approach to this problem will drive meaningful change for the treatment of sepsis and many other complex medical conditions.”
The Burden of Quality Reporting
Currently, hospitals that receive CMS funding must self-report various quality measures related to the care they deliver. The annual cost of quality reporting in US physician practices has been reported as 785 hours per physician and over $15 billion. One of the most debated and time-consuming measures is related to sepsis, known as SEP-1. This measure requires significant manual abstraction and time to complete.
Leveraging Large Language Models
Using the latest advances in Large Language Models (LLMs), Healcisio has developed several quality measure automation tools. These include an LLM-based system that ingests patient charts via Fast Healthcare Interoperability Resources (FHIR) and outputs a completed Severe Sepsis and Septic Shock (SEP-1) abstraction.
Multi-Site Deployment
As part of the multi-site deployment of its sepsis AI model, Healcisio will partner with quality improvement stakeholders. This collaboration aims to alleviate the clinical workload associated with manual chart reviews, reallocating precious clinician time to enhance care quality initiatives at the patients’ bedside.
The Future of AI in Healthcare
The advancements made by Healcisio in AI for critical care are just the beginning. The integration of AI in healthcare has the potential to revolutionize how we approach patient care and quality reporting. By reducing the burden on healthcare providers and improving patient outcomes, AI can drive significant improvements in the healthcare system.
Key Takeaways
- Funding Award: Healcisio received a $1M STTR Phase II award from the NIAID.
- Proven Success: Demonstrated a 17% reduction in sepsis mortality.
- Future Plans: Expanding to two additional health systems and deploying new generative AI tools.
- Quality Reporting: Developing automation tools for quality measure reporting.
FAQ
Q: What is Healcisio?
A: Healcisio is a leader in AI and digital healthcare, focusing on critical care decision support and quality measure reporting.
Q: What is the SEP-1 measure?
A: SEP-1 is a quality measure for sepsis care, requiring significant manual abstraction and time to complete.
Q: How does Healcisio’s AI help with SEP-1?
A: Healcisio uses LLM-based systems to automate SEP-1 abstraction, reducing the manual workload for clinicians.
Q: What are the future plans for Healcisio?
A: Healcisio plans to expand its sepsis AI model to additional health systems and deploy new generative AI tools for quality assessment.
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