Cloud for healthcare: your blueprint for medical-grade connectivity

Take the quiz: Which cloud platform fits your MedTech strategy?

What does 'medical-grade connectivity' actually require?

Medical-grade connectivity isn't just about connecting devices – it’s about doing so in a way that complies with clinical regulations, protects patient data, and scales reliably across complex healthcare environments.

At Zühlke, we've broken the challenge down into nine capability areas that any cloud platform needs to deliver on: regulatory compliance, security architecture, cloud platform design, device management, interoperability, scalability, clinical integration, quality assurance, and operational excellence. These nine pillars are then mapped to an eight-phase architectural blueprint – covering the full journey from the moment a device powers on to long-term data governance and disaster recovery.

The infographic below outlines this framework at a glance. Our whitepaper unpacks each pillar in detail, with a domain-by-domain assessment of how AWS, Azure, and GCP support implementation of these requirements.

Download the whitepaper

The nine capability areas that any cloud platform needs to deliver on

Assessing the top three cloud providers

Ideally suited for Microsoft-native organisations due to low entry barriers

Azure Health Data Services are the natural fit if your organisation already runs on Microsoft tools. Its IoT Hub and Device Provisioning Service support zero-touch, large-scale device provisioning – meaning devices can authenticate automatically at power-on without pre-configuration.

Azure Digital Twins provides semantically rich modelling of device-patient-ward relationships, while Health Data Services brings together FHIR, DICOM, and MedTech capabilities in a unified workspace. Identity management through Entra ID integrates natively with existing Active Directory environments, and Microsoft Sentinel offers healthcare-specific threat detection and incident response.

Ideally suited for global-scale device fleets due to an existing exhaustive service catalogue

AWS offers the deepest service catalogue and the most mature IoT device management. IoT Greengrass provides a proven edge runtime with store-and-forward for offline operation, while IoT Core supports MQTT v5 for reliable clinical data transmission.

HealthLake is a fully managed FHIR R4 service with built-in NLP via Amazon Comprehend Medical for extracting clinical entities from unstructured data. Amazon SageMaker rounds out the ML pipeline for clinical decision support. For compliance, AWS CloudTrail creates cryptographically verifiable, tamper-evident audit records across the entire architecture.

Ideally suited for data-first organisations with diverse clinical systems

GCP leads on analytics and AI. Its Cloud Healthcare API supports the broadest range of FHIR versions — DSTU2, STU3, R4, and R5 — alongside native DICOM and HL7v2, making it well-suited for architectures integrating with diverse clinical systems.

Native streaming export to BigQuery enables real-time analytics on FHIR data without ETL pipelines. Vertex AI and BigQuery ML provide the infrastructure for clinical decision support at population scale. Cloud Spanner's multi-region strong consistency is particularly valuable for clinical databases requiring geographic resilience during failover.

Three things to get right before you commit

Choosing the right platform matters, but it's rarely where projects succeed or fail. Three practical considerations worth thinking about early:

Plan for lock-in from day one

Some vendor dependency is unavoidable. Device management and clinical integrations often rely on platform-specific services. Build your exit strategy during the design phase, not two years into your deployment.

Factor in regulatory timelines

Cloud architecture audits for connected medical devices aren't quick. If you're targeting EU MDR or similar frameworks, build the submission timelines into your roadmap from the start.

Be honest about skills gaps

If your team doesn't know the platform you're choosing, building that capability – whether through hiring, training, or external support – is a real cost and timeline risk. Better to plan for it up front.