Aidoc announced on Monday that it's working with NVIDIA to develop a framework for more effective deployment and integration of artificial intelligence tools in healthcare.

The Blueprint for Resilient Integration and Deployment of Guided Excellence, or BRIDGE, a guideline that aims to accelerate AI adoption across the healthcare industry.

WHY IT MATTERS
The Blueprint for Resilient Integration and Deployment of Guided Excellence, or BRIDGE, is expected for release in early 2025, the companies say. It's meant to be a "robust, evidence-driven framework for seamlessly integrating AI into clinical workflows," they say, "helping healthcare organizations scale AI innovation with greater speed and confidence."

The plan aims to set clear pathways for healthcare systems to simplify the design, validation, deployment and monitoring of AI tools for faster adoption and scaling.

The guidelines focus on four key areas, according to Aidoc and NVIDIA: standardized validation, interoperability, scalable deployment and continuous monitoring. They're meant to help health systems align with other industry frameworks such as MONAI, which was co-developed by NVIDIA and other academic and industry researchers in 2019.

BRIDGE will be developed in collaboration with providers, academic partners and other industry leaders, the companies say, building on real-world AI initiatives and focusing on common challenges in AI integration.

THE LARGER TREND
One of the biggest of those challenges is scaling AI effectively, often because important considerations around integration weren't addressed early enough in the development process. The BRIDGE guideline aims to help with scalability and interoperability early on, assisting with implementation of AI solutions across multiple sites simultaneously.

Another has to do with fragmentation. The companies note that, despite the approval of more than 900 FDA-cleared AI tools for medical imaging, many providers still aren't able to build a comprehensive and integrated AI plan. BRIDGE offers the chance to build a vendor-neutral roadmap toward that goal, they say.

It will be designed for developers and providers alike, helping them think through the practicalities of real-world deployments and navigate the complexities of AI adoption, according to Aidoc and NVIDIA.

Aidoc has been busy. This past week, through its work with the Coalition for Health AI, it unveiled new progress on "model cards," similar to ingredient and nutrition labels on food products, designed to standardize the output artificial intelligence and machine learning models.

NVIDIA earlier this year introduced more than two dozen new generative AI microservices, focused on a variety of healthcare use cases (genomics, imaging, drug discovery), designed to help integrate AI into existing applications that can be run from the cloud or on-prem. It later integrated those microservices with AWS.

ON THE RECORD
"AI holds the potential to revolutionize patient care, but its progress has been stalled by fragmented systems and the inability to scale effectively," said Demetri Giannikopoulos, chief transformation officer at Aidoc in a statement.

"The BRIDGE guideline will focus on breaking down these barriers, offering a powerful, evidence-based framework that health systems can rely on to not just adopt AI but to help scale it across their operations. This will drive both operational efficiency and significantly better outcomes for patients and clinicians alike."

Mike Miliard is executive editor of Healthcare IT News
Email the writer: mike.miliard@himssmedia.com
Healthcare IT News is a HIMSS publication.