GC & Phenikaa open AI-enabled screening center in Hanoi
GC (GC Holdings) and Vietnam's Phenikaa Group have opened the GC&PHENIKAA Healthcare Center in Hanoi. The joint venture launched on December 5, marking a new screening option for local patients and providers.
At the opening ceremony, Ambassador to Vietnam Choi Young-sam of the Republic of Korea, GC Corp. CEO Heo Yong-jun, Phenikaa Group Chair Ho Xuan Nang, and Hanoi Department of Health Deputy Director Nguyen Dinh Hung attended to mark the occasion.
What the center offers
- Approximately two-hour comprehensive screening covering 14 major cancers and 30+ diseases.
- End-to-end digital workflow built on GC's medical information system (HIS, LIS, PACS, EMR) from registration to imaging, reporting, and result delivery.
- Non-chart operation via RFID wristbands to reduce paperwork and streamline patient flow.
- AI diagnostic solution that analyzes imaging and test data to flag early abnormalities, supporting specialist review for higher accuracy and efficiency.
Why it matters for Vietnam's healthcare system
GC positions the center as a platform to transfer Korea's clinical experience and technology while building capacity with Vietnamese medical staff. The goal: improve access to services that meet international standards at appropriate cost levels and strengthen local expertise in operating modern screening programs.
"Through this center, we will spread a prevention-centered health management culture and make a practical contribution to Vietnamese society," said Heo Yong-jun, CEO of GC (GC Holdings).
Next steps
Phenikaa-X and GC are co-developing a localized HIS to fit Vietnam's care delivery environment. Starting with Hanoi, GC plans to expand its screening network to major cities and grow its digital healthcare services-such as personalized care and disease prediction-using the data accumulated through the center.
Practical notes for clinicians and administrators
- Workflow impact: A unified HIS/LIS/PACS/EMR can cut turnaround times and reduce errors during handoffs. Map your current processes to identify quick wins (e.g., order-entry standardization, image routing, structured reports).
- AI governance: Establish clear protocols for how AI findings support, not replace, specialist reads. Track concordance rates, escalate thresholds, and audit outcomes regularly.
- Data quality and privacy: Define minimum data sets, labeling standards, and retention policies. Align with local regulations and international best practices where applicable.
- Change management: Plan focused training for radiology, pathology, and nursing staff. Start with pilot pathways, monitor KPIs (time-to-result, recall rates), and iterate.
If you're refining screening pathways, WHO's guidance on early detection provides useful reference points: WHO: Cancer early detection.
Teams looking to level up AI skills for clinical operations and data analysis can explore role-based learning paths here: AI courses by job role - Complete AI Training.
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