Health Data Governance Training Course

Health Data Governance Training Course

Introduction

Health Data Governance is a critical pillar in modern healthcare systems, ensuring data privacy, regulatory compliance, interoperability, data security, and ethical management of sensitive patient information. As healthcare becomes increasingly digitalized through Electronic Health Records (EHRs), AI-driven diagnostics, cloud health systems, and big data analytics, the demand for robust governance frameworks has never been higher. Health Data Governance Training Course equips professionals with practical and strategic knowledge to manage, protect, and optimize health data assets in alignment with global standards such as GDPR, HIPAA, ISO 27799, and emerging digital health regulations.

In today’s rapidly evolving healthcare ecosystem, organizations face growing challenges such as data breaches, interoperability gaps, consent management issues, cybersecurity threats, and compliance risks. This course provides a comprehensive foundation in health data lifecycle management, data stewardship, metadata governance, data quality assurance, and AI ethics in healthcare. Participants will gain hands-on skills to implement scalable governance models that improve patient trust, operational efficiency, and regulatory readiness across hospitals, research institutions, insurance systems, and public health agencies.

Course Duration

5 days

Course Objectives

1. Master Health Data Governance Frameworks aligned with global standards 
2. Understand HIPAA, GDPR, and healthcare compliance regulations
3. Develop expertise in Electronic Health Records (EHR) management
4. Implement Data Privacy and Patient Consent Management systems
5. Strengthen Healthcare Cybersecurity and Risk Management strategies
6. Learn Data Quality Assurance and Data Integrity validation techniques
7. Apply AI Governance in Healthcare Data Analytics
8. Design Interoperable Health Information Systems (HIEs)
9. Manage Clinical Data Lifecycle and Data Stewardship roles
10. Build Metadata Management and Data Cataloging systems
11. Address Health Data Ethics and Responsible AI usage
12. Enhance Cloud-based Health Data Governance models
13. Develop Audit, Reporting, and Compliance Monitoring systems

Target Audience

1. Healthcare Data Managers 
2. Hospital IT Administrators 
3. Clinical Informatics Specialists 
4. Public Health Officials 
5. Data Protection and Compliance Officers 
6. Healthcare Analysts and Researchers 
7. Health Tech and AI Developers 
8. Policy Makers in Health Ministries and NGOs 

Course Modules

Module 1: Foundations of Health Data Governance

• Principles of data governance in healthcare 
• Data ownership, stewardship, and accountability 
• Governance frameworks (DAMA-DMBOK, ISO standards) 
• Healthcare data ecosystems overview 
• Case Study: National hospital digitization governance model 

Module 2: Healthcare Data Privacy & Compliance (HIPAA & GDPR)

• HIPAA Privacy and Security Rules 
• GDPR patient rights and data consent 
• Cross-border health data regulations 
• Legal implications of data breaches 
• Case Study: European hospital GDPR compliance transformation 

Module 3: Electronic Health Records (EHR) Governance

• EHR system architecture and data flow 
• Data standardization (HL7, FHIR) 
• Access control and authentication systems 
• Interoperability challenges 
• Case Study: EHR integration across multi-hospital networks 

Module 4: Data Security & Cyber Risk Management in Healthcare

• Cybersecurity threats in healthcare systems 
• Encryption and anonymization techniques 
• Incident response and breach management 
• Risk assessment frameworks 
• Case Study: Hospital ransomware attack response strategy 

Module 5: Data Quality, Integrity & Master Data Management

• Data validation and cleansing methods 
• Master Patient Index (MPI) systems 
• Reducing duplication and inconsistency 
• Data lifecycle quality controls 
• Case Study: National health registry data cleanup initiative 

Module 6: AI, Big Data & Advanced Analytics Governance

• Ethical AI in healthcare decision-making 
• Bias detection in medical algorithms 
• Big data governance frameworks 
• Predictive analytics in healthcare 
• Case Study: AI-based disease prediction governance model 

Module 7: Health Information Exchange & Interoperability

• Health Information Exchange (HIE) systems 
• FHIR APIs and data sharing standards 
• Cross-platform data integration 
• Real-time patient data exchange 
• Case Study: Regional healthcare interoperability project 

Module 8: Cloud Governance & Future of Health Data Systems

• Cloud-based healthcare data storage models 
• Hybrid cloud governance strategies 
• Data sovereignty in healthcare 
• Blockchain in health data management 
• Case Study: Cloud migration of national health records system 

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.