Under-resourced hospitals encounter significant challenges in adopting artificial intelligence (AI), but these hurdles can be overcome by staying updated with the fast-evolving analytics and AI tools. The healthcare industry is increasingly leaning towards automation to enhance efficiency and patient outcomes.
AI has the potential to:
- Enhance health equity and access to care
- Improve an organization’s financial performance
- Support recruitment efforts
However, healthcare providers in small, rural, and underserved communities face unique challenges in implementing AI solutions. The Health AI Partnership, initiated by the Duke Institute for Health Innovation and Duke University School of Medicine, aims to assist these organizations.
Launched in 2021, the partnership has been collaborating with five under-resourced healthcare organizations to enhance their understanding of AI models and manage their long-term use through a 12-month program known as the Practice Network.
The organizations involved in the first cohort of the Health AI Partnership are:
- North Country Healthcare in Arizona
- San Ysidro Health in San Diego County, California
- Health Center of Southeast Texas
- WakeMed health system in North Carolina’s Research Triangle
- Community-University Health Care Center in Minnesota
These organizations are implementing various AI tools, including ambient scribes, a “no-show” algorithm, sepsis warning codes, and retinal diabetic retinopathy scanning. Through this partnership, they gain access to best practices, industry mentors, and implementation support, meeting regularly to address their specific AI challenges.
Knowledge Gaps and Support
Approximately ten months into their engagement, leaders from HAIP report that the mentoring and peer learning program has significantly increased the number of AI use cases being explored by these organizations.
Key components of the program include:
- An eight-key decision point framework
- 31 best practice guides for implementing health AI
Alifia Hasan, innovation portfolio manager at DIHI, emphasized the need for a dynamic community that continuously evaluates best practices as new tools are integrated. She noted that the pressure to survive drives these organizations to explore AI in clinical care and operations.
Recruitment challenges are also prevalent; organizations that do not offer advanced services like ambient scribes may struggle to attract physicians.
Despite vendor assistance, participating organizations often find it difficult to evaluate AI products due to gaps in expertise and experience in negotiations, leading to unfavorable contract terms.
Future Plans and Implementation Support
At the upcoming HIMSS AI in Healthcare Forum on July 10-11 in Brooklyn, participants from the Practice Network will share their experiences with AI integration in routine care.
The partnership aims to expand the Practice Network nationally through a hub-and-spoke model, allowing other institutions to provide similar technical assistance to more under-resourced healthcare organizations across the U.S.
Mark Sendak, population health and data science lead at DIHI, highlighted the intimidating digital divide faced by these organizations, noting that they are currently working with only four out of 1,600 community health centers.
Office hours, where participants meet with AI experts to discuss specific implementation challenges, have proven particularly beneficial.
During the forum, representatives from the five participating organizations will discuss their AI adoption challenges and share real-world strategies for measuring return on investment.
Leaders from the partnership attribute much of the progress in including under-resourced hospitals in AI discussions to HIMSS, which has been instrumental in addressing the digital divide.
The HIMSS AI in Healthcare Forum is scheduled for July 10-11 in Brooklyn. Learn more and register.
Andrea Fox is senior editor of Healthcare IT News.
Email: afox@himss.org
Healthcare IT News is a HIMSS Media publication.