Postgraduate Diploma in IoMT Platforms and Health Data Orchestration
Online 800-hour Postgraduate Diploma in IoMT Platforms and Health Data Orchestration. 8 modules covering ISO/IEEE 11073 (medical device communication), HL7 FHIR and Apache Kafka. Dedicated tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe the architecture of the Internet of Medical Things.
Apply interoperability standards between devices and clinical systems.
Design streaming ingestion and processing flows.
Orchestrate health data pipelines with flow tools.
Select cloud platforms suitable for health data.
Integrate cybersecurity requirements and medical device regulation.
Develop value-added analytical services on IoMT data.
Who it's for
- IoMT platform architect looking to specialise in IoMT Platforms and Health Data Orchestration.
- Health data engineer looking to specialise in IoMT Platforms and Health Data Orchestration.
- Medical device integration engineer looking to specialise in IoMT Platforms and Health Data Orchestration.
- Healthcare cybersecurity specialist looking to specialise in IoMT Platforms and Health Data Orchestration.
- DevOps engineer in healthcare looking to specialise in IoMT Platforms and Health Data Orchestration.
- Connected health product manager looking to specialise in IoMT Platforms and Health Data Orchestration.
- Engineering or science graduates seeking to enter digital health.
What you'll work with
- ISO/IEEE 11073 (medical device communication)
- HL7 FHIR
- IEC 80001-1 (risk management for networks with medical devices)
- IEC 81001-5-1 (health software cybersecurity)
- Regulation (EU) 2017/745 (MDR)
- Directive (EU) 2022/2555 (NIS2)
- IHE PCD Profiles (patient care devices)
8 modules · 800 h
1.1IoMT concept and its layers1.2Hospital and home-based devices1.3Edge, fog and cloud architectures1.4MQTT, CoAP and AMQP protocols1.5Connectivity: Wi-Fi, BLE, LoRaWAN and 5G1.6Gateways and data concentrators1.7Latency and availability requirements1.8Use cases: ICU, operating theatre and home1.9Market and technology players1.10Case study: IoMT architecture for an inpatient ward
2.1HL7 FHIR reference model2.2Device, Observation and Patient resources2.3HL7 v2 and hospital messaging2.4IEEE 11073 SDC for networked devices2.5IHE PCD and DEC profiles2.6openEHR and clinical archetypes2.7SNOMED CT, LOINC and UCUM terminologies2.8FHIR servers: HAPI and cloud platforms2.9Conformance testing and Implementation Guides2.10Lab: deploying a HAPI FHIR server
3.1Real-time ingestion with Kafka3.2Stream processing with Flink and Spark3.3Time-series databases3.4Data lakes and lakehouses in healthcare3.5ETL and ELT transformations3.6Normalisation and mapping to common models3.7OMOP CDM model for research3.8Real-time data quality3.9Metadata management and lineage3.10Practical: Kafka pipeline from vital signs to FHIR
4.1Orchestrators: Airflow, Prefect and Dagster4.2Clinical workflows and BPMN4.3Microservices and API gateways4.4Containers and Kubernetes in healthcare4.5Events and event-driven architectures4.6Integration with interoperability engines4.7Patient identity management: MPI4.8Observability: logs, metrics and traces4.9Scalability and high availability4.10Lab: Airflow DAG to consolidate device data
5.1Healthcare cloud services: Azure, AWS and Google5.2Managed IoT platforms5.3Device twins and fleet management5.4Secure OTA updates5.5Edge computing in the hospital5.6Data sovereignty and European cloud5.7ENS and ISO 27017 certifications5.8Costs and FinOps5.9Multicloud and hybrid strategies5.10Practical: device registration and management on an IoT platform
6.1Medical device cybersecurity: MDCG 2019-166.2IEC 81001-5-1 standard6.3IEC 80001-1 for networks with medical devices6.4Network segmentation and zero trust6.5Vulnerability management and SBOM6.6Encryption and key management6.7GDPR and the European Health Data Space6.8Software as a medical device6.9NIS2 Directive in the health sector6.10Case study: STRIDE threat modelling of an IoMT platform
7.1Real-time clinical dashboards7.2Smart alerts and prioritisation7.3AI models deployed on the platform7.4MLOps in healthcare environments7.5Asset management and RTLS location7.6Predictive maintenance of equipment7.7Research with federated data7.8Platform operational indicators7.9Return on investment assessment7.10Practical: real-time vital signs dashboard for a unit
8.1Definition of the clinical use case8.2Device and connectivity selection8.3Platform architecture8.4FHIR interoperability model8.5Ingestion and orchestration pipelines8.6Security and compliance analysis8.7Functional end-to-end prototype8.8Deployment and operations plan8.9Report and presentation8.10Final review with the tutor
How you'll learn
100% online training on the SEIUM Institute campus, with downloadable material, recorded classes and a dedicated technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine the programme with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Apache Kafka, Apache NiFi, Azure Health Data Services, Node-RED, Kubernetes, in free, academic or evaluation versions. Practice is based on real procedures from a medical device integration laboratory, real-time ingestion load tests and the deployment of an IoMT pipeline in the cloud. Assessment is continuous per module, plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Describe the architecture of the Internet of Medical Things.
Apply interoperability standards between devices and clinical systems.
Design streaming ingestion and processing flows.
Orchestrate health data pipelines with flow tools.
Select cloud platforms suitable for health data.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory texts.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme comprises 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
You work with Apache Kafka, Apache NiFi, Azure Health Data Services, Node-RED and Kubernetes. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM Institute own diploma, awarded on passing the continuous assessment and the integrative project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed on a course or diploma in the same area are credited towards the advanced programme. Check the recognition policy when you enrol.
Related programmes
Postgraduate Diploma in Data-Driven Sports Technique Optimisation
Online 800-hour Postgraduate Diploma in Data-Driven Sports Technique Optimisation. 8 modules covering Regulation (EU) 2016/679 (GDPR, biometric data), Sports Act 39/2022 and Kinovea. Assigned tutor and…
Postgraduate Diploma in Organisational Resilience and Supply Chains
Online 800-hour Postgraduate Diploma in Organisational Resilience and Supply Chains. 8 modules covering ISO 22316 (organisational resilience), ISO 22301 (business continuity) and anyLogistix. Assigned tutor and…
Postgraduate Diploma in Mobility, Seating and Lifting Systems
Online Postgraduate Diploma in Mobility, Seating and Lifting Systems, 800 h. 8 modules covering ISO 7176 (wheelchairs), UNE-EN 12183 (manual wheelchairs) and SolidWorks. Dedicated tutor and…
More in Health, Biomechanics, Wearables & Operational Safety
All Health, Biomechanics, Wearables & Operational Safety programmes → · How to apply · Fees & financing · Scholarships