Transforming Healthcare: Overcoming AI Adoption Challenges in Under-Resourced Hospitals
The Push for AI in Healthcare
Under-resourced hospitals are navigating a steep learning curve in adopting artificial intelligence (AI) solutions. However, with the rapid advancements in analytics and automation technology, these institutions have a unique opportunity to improve patient outcomes and reduce operational costs.
The Promise of AI
AI holds significant potential to enhance health equity, boost access to care, and improve financial performance within healthcare organizations. Moreover, it’s also poised to aid in recruitment efforts, making hospitals more attractive to potential employees.
Unique Challenges for Rural Providers
Despite the benefits, providers in small, rural, and medically underserved communities face specific hurdles in modernizing their AI approaches. To address these challenges, the Health AI Partnership (HAIP), initiated by the Duke Institute for Health Innovation and Duke University School of Medicine, aims to provide critical support.
A Collaborative Approach
Launched in 2021, HAIP collaborates with five under-resourced healthcare organizations over a year-long program named the Practice Network. This initiative seeks to empower these organizations in building trust in AI models and managing their applications long-term.
Practical Implementations
The inaugural cohort of the Health AI Partnership is exploring various AI technologies, including ambient scribes, a "no-show" algorithm, and sepsis warning codes, alongside retinal diabetic retinopathy scanning. Participants gain access to best practices, mentorship, and troubleshooting support.
Sharing Knowledge at HIMSS AI Forum
At the upcoming HIMSS AI in Healthcare Forum on July 10-11 in Brooklyn, network members will showcase how they effectively integrate AI into everyday healthcare practices.
Bridging Knowledge Gaps
Approximately ten months into the initiative, HAIP leaders report a surge in potential use cases being explored within the participating organizations. The diversity of technology includes large language models and clinical decision support systems being introduced by partners such as the Community-University Health Care Center in Minnesota and four federally qualified health centers across the nation.
The Decision Framework
Central to HAIP’s program is an eight-key decision point framework, accompanied by 31 best practice guides to streamline AI implementation.
Challenges in Physician Recruitment
Alifia Hasan, innovation portfolio manager at DIHI, highlights that hospitals unable to provide advanced services, like ambient scribes, encounter significant challenges in recruiting capable physicians.
Navigating Vendor Relationships
Even with vendor support, healthcare organizations often struggle to assess AI products due to their limited expertise. This can lead to unfavorable contract terms during negotiations.
Addressing Resource Gaps
Suresh Balu, co-lead at HAIP, emphasizes the common recognition of a significant resource gap within these organizations. Regular discussions with experts help bridge the knowledge divide and empower hospitals to effectively implement AI solutions.
Building a National Network
At the HIMSS forum, Hasan will unveil HAIP’s vision for expanding the Practice Network nationally. The aim is to establish a hub-and-spoke model, allowing other institutions to deliver similar technical support to more under-resourced healthcare organizations across the U.S.
Confronting the Digital Divide
Mark Sendak, co-lead at the Institute, describes the digital divide faced by these organizations as daunting. With approximately 1,600 community health centers in the U.S., working with just a handful underscores the urgent need for wider support.
Leveraging Office Hours
The program’s “office hours” feature is particularly valuable, allowing participants to engage directly with HAIP’s AI experts for tailored advice on implementation challenges.
Learning from Real-World Experience
During the panel discussion at the HIMSS Forum, representatives from the five participating organizations will share their real-world experiences in AI adoption, detailing the challenges they’ve faced and how they measure ROI for their efforts.
Understanding Lifecycle Challenges
Balu notes that a significant focus of the forum will be addressing nuanced challenges associated with the development, deployment, and monitoring of AI solutions in healthcare.
Acknowledging HIMSS’s Role
Leaders from HAIP credit HIMSS for its efforts to incorporate under-resourced and community hospitals into the broader conversation surrounding AI implementation, thereby addressing the industry’s digital divide.
Conclusion: A Bright Future Ahead
As under-resourced hospitals strive to overcome barriers to AI adoption, initiatives like the Health AI Partnership provide a beacon of hope. By fostering collaboration, education, and support, these organizations not only enhance their operational capabilities but also contribute to a more equitable healthcare landscape. The upcoming HIMSS AI in Healthcare Forum is an essential platform to continue this vital conversation and explore new horizons in health technology.
