Addressing AI Challenges in Underserved Hospitals
Underserved hospitals, especially those in rural areas, face significant hurdles when adopting AI technologies. Issues such as high costs, limited interoperability, and workforce constraints hinder their ability to implement AI solutions effectively.
Brianna Day, clinical applications and informatics senior manager at North County Health, highlighted the digital divide during the HIMSS AI Forum. Many rural patients struggle with access to reliable WiFi or smart devices, limiting the reach of digital healthcare tools.
Day also noted that their facility operates on an older electronic health record (EHR) system with many customizations. Despite this, they partnered with a practice network to deploy AI across clinics to enhance care quality and efficiency.
Barriers in AI Adoption
Michelle Oden, an electronic health record support analyst at the Community-University Health Care Center, University of Minnesota, shared challenges related to AI tools for reducing patient no-shows. Their vendor declined access to Epic’s predicted no-show tool, citing readiness issues.
Oden emphasized the lack of clear guidance on evaluating AI model performance using their own data, which complicates adoption efforts. Additionally, language diversity presents challenges; about half of their patients prefer non-English care, and many AI tools do not support all needed languages, such as Vietnamese.
Training and Patient Transparency
Sidney Robinson, IT manager at the Health Center of Southeast Texas, discussed their focus on provider-specific AI tools. Their team involved the EMR vendor to assist with training, aiming to integrate AI smoothly and safely into daily workflows.
Importantly, Robinson stressed the need for patient inclusion and transparency. The health center incorporated AI disclosure notices within patient demographics, allowing patients to opt in or out of AI use during their care.
Local Support and Resources
Oden expressed a desire for more Regional Extension Centers, similar to those established under the Affordable Care Act to support EHR implementation in underserved areas. Such centers could provide hands-on assistance, helping local teams build capacity and confidence with new technologies.
- Addressing digital access gaps is essential for equitable AI deployment.
- Clear pathways to evaluate AI tools on local data can ease adoption.
- Training and patient transparency build trust and comfort with AI.
- Local support centers can accelerate AI integration in underserved hospitals.
Healthcare professionals interested in expanding their AI knowledge can explore practical training options at Complete AI Training.
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