Supported by a USTDA grant, this initiative aims to integrate advanced AI into clinical workflows at Jordan’s premier cancer institute.
The King Hussein Cancer Center (KHCC), a regional hub for advanced cancer treatment, has selected ReMedi Health Solutions as the lead U.S. prime contractor for a major AI readiness initiative. The project, funded by the U.S. Trade and Development Agency (USTDA), marks a significant milestone in bringing intelligent, mission-critical technology into the hospital’s electronic health record (EHR) ecosystem.
KHCC, which treats approximately 60% of all cancer cases in Jordan, operates within the sophisticated Hakeem EHR environment. Unlike many AI initiatives that rely on cloud-native data, this project is designed to work directly within the systems clinicians use daily.
ReMedi Health Solutions, in collaboration with technology partner Folio3, will focus on strengthening the center’s AI governance and implementation frameworks. The project centers on three core pilots:
- Business Intelligence: Enhancing operational visibility.
- Breast Cancer Diagnostics: Leveraging AI for earlier detection.
- Clinical Trials Screening: Improving access to life-saving research.
“AI succeeds in a hospital when it respects how clinicians and operations work together,” says Dr. Sonny Hyare, CEO of ReMedi Health Solutions. The firm’s approach prioritizes embedding AI tools into specialty workflows, ensuring that technology reduces administrative burdens rather than increasing them.
Dr. Asem Mansour, CEO of KHCC, notes that the initiative is a vital step toward future-proofing the center’s care. “Expanding the use of AI will help reduce administrative burdens, support clinical decision-making, provide personalized medicine, and enhance KHCC’s research capabilities.”
This engagement is aligned with Jordan’s Artificial Intelligence Strategy and Implementation Plan (2023-2027) and the U.S. Partnership for Global Infrastructure and Investment. By integrating AI into the national Hakeem system, the project establishes a scalable model for how complex healthcare environments can transition from AI interest to clinical readiness.
