GSMA Foundry and NUHS scale 5G, AI and XR in live healthcare
A new collaboration between GSMA Foundry and Singapore’s National University Health System (NUHS) aims to operationalize connected health at scale, with Ericsson and Singtel anchoring the 5G foundation.
Why connected healthcare needs 5G SA now
Healthcare digitization has moved from pilots to production, but most sites still struggle with deterministic connectivity, secure data exchange and workflow integration. This partnership elevates proven use cases—remote surgical support, XR training, robotics and hospital-at-home—onto purpose-built 5G standalone (SA) networks with edge AI, signaling that connected care is entering a scale-out phase rather than another proof-of-concept cycle.
Ecosystem partners and clinical roles
GSMA Foundry convenes the mobile ecosystem; NUHS brings a complex, multi-hospital environment with clinical governance; Ericsson supplies 5G infrastructure and platforms; Singtel contributes 5G SA, network slicing and secure virtual private networks. The coalition blends standards leadership with live clinical settings—a prerequisite for credible outcomes data and replicable architectures.
From remote surgery to smart hospitals: what’s being built
The program combines private 5G with digital twin, XR, IoT and ambient AI to improve outcomes and operational resilience across care pathways.
Priority 5G healthcare use cases
Early focus areas include 5G-enabled remote surgical assistance with ultra-reliable, low-latency links; immersive XR training and simulation that compress learning curves; autonomous and semi-autonomous robotics for logistics and point-of-care tasks; AI-guided imaging such as vein visualization; and intelligent facilities management that leverages digital twins to optimize patient flow, bed capacity and energy consumption. Hospital-at-home models extend acute and sub-acute care beyond the ward using wearables, medical IoT and assured connectivity.
5G SA, MEC and XR: the enabling stack
The reference architecture centers on 5G SA for deterministic performance, with network slicing to separate clinical traffic from administrative and visitor flows. Mobile edge computing hosts latency-sensitive AI inference and XR rendering, while secure device onboarding and policy control span IoT sensors, medical devices and robotics. XR endpoints, including headsets such as Microsoft’s HoloLens 2, support holographic surgical planning and guided procedures. Ambient AI, fed by multimodal data, augments workflows without adding clinician burden. Digital twins stitch real-time telemetry to facility and patient pathways, enabling predictive and prescriptive actions.
Network design for clinical-grade 5G
Healthcare-grade connectivity requires more than bandwidth; it demands deterministic behavior, isolation and verifiable security.
Deterministic QoS and slice governance
Mission-critical applications need tight jitter and latency bounds, not just peak throughput. Operators should productize clinical-grade slices with admission control, QoS policies, and APIs for dynamic prioritization during surge events. Align offers to 3GPP features in 5G-Advanced (Release 18) that enhance positioning, uplink performance and mobility robustness for dense indoor campuses.
MEC placement and data locality
Clinical AI and XR rendering run best where data is produced—on-prem or metro edge—to meet sub-20 ms round-trip targets and satisfy data residency. Reference designs must define where inference, caching and digital twin orchestration live, along with observability to prove SLOs to hospital IT and compliance teams.
Zero trust, resilience and compliance
Zero-trust patterns with device identity, micro-segmentation and continuous posture assessment are mandatory. Designs should anticipate failover between private and public 5G, and document chain-of-custody for clinical data to align with regulatory frameworks and hospital risk committees. Exposure of network events via standardized APIs can feed SIEM and clinical safety cases.
Business impact: ROI from connected health
The value thesis combines clinical improvements with hard operational savings and new revenue streams.
Clinician efficiency and workforce augmentation
XR-guided training reduces time-to-competency; remote assistance shortens specialist wait times; and robotic workflows trim non-value-added minutes from nursing shifts. Ambient AI can reduce documentation overhead and improve care coordination, translating to higher throughput and better patient experience scores.
Telco monetization with managed healthcare slices
Operators can package private 5G, slicing, MEC and security as managed services with outcome-based SLAs tied to uptime, latency and coverage in high-density indoor spaces. Partnerships with ISVs and device makers enable vertical bundles—XR for surgery, robotics-as-a-service for logistics, or hospital-at-home connectivity kits—expanding beyond connectivity ARPU into platform and application revenue.
Execution challenges to scale across health systems
Scaling from showcase to system-wide adoption hinges on integration discipline and clinical validation.
Interoperability with EHR, PACS and ITSM
Solutions must interoperate with EHRs and PACS via healthcare standards such as HL7 FHIR and DICOM, integrate device telemetry into clinical data lakes, and respect existing ITSM and CMMS workflows. Vendor-neutral architectures and clear data ontologies reduce lock-in and accelerate rollout across sites.
Safety cases, quality and clinical evidence
Remote assistance and robotics require human factors testing, risk management and rigorous post-market surveillance. Health systems will look for peer-reviewed outcomes, cost-utility analyses and safety cases before moving beyond pilots.
TCO transparency and scalable blueprints
Hospitals demand transparent TCO across radios, edge compute, devices, security and lifecycle support. Reference designs, blueprint SKUs and repeatable deployment playbooks can compress time-to-value and de-risk multi-site expansion.
MWC26: production-readiness signals to watch
Live demonstrations will reveal how close these solutions are to production-grade deployment.
Live demos and validation metrics
NUHS, Ericsson and Singtel will present a robot nurse companion, 3D holographic surgical planning with HoloLens 2, AI-augmented vein detection and hospital-at-home platforms—all running on differentiated 5G connectivity. Evaluate end-to-end latency, handover behavior, device management, and how clinical apps are orchestrated at the edge.
Roadmap signals for 5G-Advanced and 6G
Expect roadmaps that exploit 5G-Advanced features for better indoor positioning, uplink and power efficiency, plus discussion on network APIs for dynamic QoS. The trajectory toward 6G—AI-native networks, integrated sensing and tighter compute-network convergence—will influence how future clinical-grade slices and digital twins are delivered.
Action plan for providers and telcos
Use this partnership as a blueprint to de-risk your own connected health programs.
Steps for healthcare providers
Identify high-friction workflows where latency and mobility matter, then pilot private 5G with clear clinical and operational KPIs. Start with XR training or logistics robotics to build change-management muscle, and establish data governance for AI models and digital twins. Demand evidence-backed SLAs tied to clinical priorities.
Steps for operators and vendors
Productize healthcare-ready slices with packaged MEC, security and observability, and recruit ISV partners for XR, robotics and digital twin analytics. Publish reference architectures and compliance artifacts, and price offers to outcomes—not just bandwidth. Prepare for multi-campus rollouts with repeatable playbooks and co-selling motions into clinical leadership.
