Introduction

Every annotation label, every model evaluation and every training dataset in healthcare AI is built on something profoundly sensitive: real people’s health information. Handling that data lawfully, securely and ethically is not an optional extra — it is the licence to operate. The Health Data Handling & Regulatory Compliance program trains specialists to manage protected health information responsibly across its entire lifecycle, from collection and consent through de-identification, storage, sharing and eventual deletion.

This program translates complex law and security practice into the concrete decisions an annotation or AI data professional actually faces. Learners study the global frameworks that shape the field — notably HIPAA and the GDPR — and then ground that knowledge in the Kenyan Data Protection Act 2019 and the wider African regulatory landscape, so graduates can operate compliantly both locally and for international partners. Practical modules cover de-identification of images and clinical text, security controls for annotation teams, and the compliance operations that keep an organisation audit-ready.

Delivered by Shevs Connect Institute (SCI), the program assumes completion of the HEALTHCARE AI TRAINER & DATA ANNOTATION PROGRAM. It is essential for anyone working on SCILabel or similar platforms, and for the data stewards, project leads and coordinators who must ensure healthcare AI work meets regulatory and ethical standards. Graduates leave able to build and run a credible compliance framework for a healthcare AI data operation.

This specialist program is designed to be taken after the foundation program above. The foundation course establishes the core concepts and working practices that this program builds upon.

Learning Outcomes

On successful completion of this program, graduates will be able to:

• Identify what counts as health data and classify it correctly (PHI, PII and special-category data).
• Apply core data-governance principles across the AI data lifecycle.
• Explain lawful bases for processing and the role of informed consent in healthcare and research.
• Distinguish de-identification, anonymisation and pseudonymisation, and choose the right approach.
• De-identify medical images (including DICOM headers and burned-in text) and clinical free text.
• Summarise the key requirements of HIPAA and the GDPR for health data.
• Apply the Kenya Data Protection Act 2019 and understand the role of the Data Protection Commissioner.
• Implement practical security controls for annotation teams, including access control and encryption.
• Conduct a Data Protection Impact Assessment (DPIA) for an annotation project.
• Build a compliance program with policies, auditing and an incident-response plan.

Course Features

• Six in-depth modules totalling 60 structured lessons plus 5 major hands-on assignments.
• Clear, plain-language treatment of HIPAA, GDPR and the Kenya Data Protection Act 2019.
• Practical de-identification labs for both imaging and clinical text.
• Templates and worked examples for DPIAs, data inventories and incident response.
• A strong focus on the Kenyan and African context alongside global standards.
• A portfolio-ready capstone: a compliance framework for an annotation operation.
• Direct relevance to SCILabel governance and partner due-diligence requirements.
• A Certificate of Completion in Health Data Handling & Regulatory Compliance from Shevs Connect Institute.