Coalition for AI in Health
Accelerating AI Implementation in Healthcare System
Advocating for Improving Patient Care with AI
The Mission
AI technology has the potential to revolutionize healthcare nationally by enhancing diagnostics, tailoring treatment plans, and providing predictive insights into patient care. However, barriers such as substantial initial costs and technical complexities hinder its widespread adoption. Our initiative, AIinHealth, advocates for a national approach that includes financial incentives, regulatory support, and comprehensive educational programs to promote the integration of AI in healthcare settings across the United States. By addressing these challenges through targeted policies, we can set a national precedent for healthcare innovation. This initiative not only aims to improve patient outcomes throughout the country but also positions the U.S. as a global leader in demonstrating the transformative benefits of AI in healthcare.
Our Policy Recommendations
Financial Incentives
01
To support the adoption of AI in healthcare, substantial tax credits are proposed for hospitals that invest in AI technologies, helping to cover the costs of software acquisition and integration. Additionally, grants will be provided for AI projects, with a focus on ensuring equitable technology distribution in underserved areas. Furthermore, it is recommended to modify reimbursement models to reward healthcare providers for improved outcomes achieved through AI interventions.
Financial Incentives
02
Educational and Training Programs
Education and Training Programs
Our policy recommends funding training programs to help healthcare professionals become proficient in using AI tools, enhancing their capabilities in delivering advanced care. Simultaneously, public awareness campaigns will be initiated to educate the general public about the benefits of AI in healthcare, promoting understanding and acceptance of these technologies.
Public-Private Partnerships (PPP)
03
Our proposal encourages fostering public-private partnerships by offering tax incentives and co-funding opportunities that facilitate collaborative development and deployment of AI solutions. Additionally, it supports the creation of innovation clusters that bring together hospitals, tech companies, and academic institutions to collaborate and share resources and knowledge, driving forward healthcare innovation.
Public-Private Partnerships
04
Infrastructure Support
Infrastructure Support
Our recommendation suggests to provide low-interest loans or grants to healthcare facilities for upgrading their IT infrastructure, which is crucial for supporting sophisticated AI applications. To ensure seamless integration of AI tools, the development of interoperability standards among different healthcare IT systems is also promoted.
Innovation and Research Incentives
05
To foster continued innovation in the AI healthcare field, additional tax credits are proposed for research and development expenditures. Supporting open data initiatives that provide researchers with access to anonymized healthcare data is also crucial, as this data is essential for training and refining AI models, ultimately leading to more effective healthcare solutions.
Innovation and Research Incentives
06
Intellectual Property (IP) Incentives
Intellectual Property Incentives
The proposal includes providing expedited patent review processes to encourage the rapid development and deployment of innovative AI healthcare technologies. There is also a recommendation to implement a reduced royalty scheme for the use of government-funded AI research, aiming to stimulate further innovation without the heavy burden of licensing costs.
Current Focus
Tax Credits for Healthcare Systems
Provide significant refundable tax credits to hospitals that invest in AI technologies, which will cover the expenses related to acquiring and integrating software.
Technology Upgrade Funds for Healthcare Systems
Allocate grants to healthcare facilities to enhance their IT infrastructure, enabling support for AI applications.
The current focus of the Coalition for AI in Health is to enhance the passage of crucial legislation in Congress and local and state governments, aiming to significantly advance the integration of Artificial Intelligence technologies in healthcare settings. Central to this legislative effort are proposals for financial incentives that include substantial refundable tax credits for hospitals that invest in AI technologies, covering costs associated with software acquisition and integration. Additionally, the coalition advocates for the establishment of technology upgrade funds, which would provide grants to healthcare facilities to upgrade their IT infrastructure, thereby supporting the effective implementation of AI applications. These initiatives are designed to remove financial barriers and facilitate a broader adoption of AI in healthcare, enhancing patient care and operational efficiency across the sector.
Jeongwook (Luke) Yun
Executive Director
Luke is an undergraduate at the University of Texas at Austin studying biomedical engineering. He has a passion at the intersection between policy, artificial intelligence, and healthcare. He has experience in developing artificial intelligence models with medical data at Harvard Medical School and Massachusetts Institute of Technology.
Mitchell Litvinov
Chief Operating Officer
Mitchell is an undergraduate at the University of Texas at Austin, studying biomedical engineering. He aspires to become a physician-scientist, driven by a deep commitment to ensuring equitable healthcare for all. With a strong focus on computational imaging, Mitchell aims to leverage artificial intelligence to advance medical practices. He brings valuable research experience from Harvard Medical School and the University of Texas at Austin, eager to contribute his expertise to impactful healthcare innovations.
Our initiative has also received guidance from key members from Columbia Medical School, Harvard Medical School, New York University School of Global Public Health, the University of Texas at Austin Dell Medical School, and many more.
