Training on Data Governance and Quality Assurance in Health Analytics
Learn how to manage, protect, and optimize health data to support accurate reporting and regulatory compliance.
Duration
10 days
Live instruction
Delivery
Physical + Virtual
Cohort based
Level
Intermediate
Working professionals
Certification
NITA reimbursable
For Kenyan cohorts
Language
English
All materials
About this programme
This specialized course provides health sector professionals with practical knowledge and tools to manage, protect, and optimize data used in health analytics. The course covers data governance frameworks, compliance, data quality standards, ethical handling, and implementation of effective oversight mechanisms. Through case studies and applied exercises, participants gain the capability to strengthen data integrity, support accurate health analytics, and uphold regulatory requirements.
Duration
10 Days
Who Should Attend
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Health data analysts and informatics officers
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Health IT and digital transformation professionals
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Data managers, HIS coordinators, and quality control specialists
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Public health researchers and monitoring & evaluation personnel
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Compliance and regulatory officers within healthcare organizations
What you'll walk away with
By the end of this course, participants will:
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Understand data governance principles and frameworks applicable to health systems
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Assess and improve data quality to support reliable analytics and reporting
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Implement policies and procedures for ethical and compliant data management
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Strengthen data protection, privacy, and security within health analytics workflows
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Develop a structured data governance and quality assurance roadmap
What we cover, module by module
Module 1: Introduction to Data Governance in Health Systems
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Importance of governance in health analytics
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Core components and industry standards
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Case Study: Data governance failure and its impact on clinical outcomes
Module 2: Data Governance Frameworks and Policies
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Developing governance structures and roles
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Policy creation, implementation, and monitoring
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Workshop:Designing a governance framework
Module 3: Data Quality Concepts and Dimensions
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Understanding accuracy, completeness, consistency, and reliability
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Key determinants of data quality in healthcare
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Case Study:Analysis of data errors in hospital patient records
Module 4: Data Quality Assessment and Audit Techniques
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Data validation tools and methodologies
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Conducting health data audits
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Practical Exercise:Performing a data quality check
Module 5: Ethical Data Use and Regulatory Compliance
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Data privacy regulations (GDPR, HIPAA, NHIF policies)
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Ethical data collection and management practices
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Case Study: Legal implications of improper patient data handling
Module 6: Data Protection, Security & Risk Management
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Cybersecurity in health data systems
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Risk assessment and mitigation strategies
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Scenario Simulation:Managing a data breach in a health organization
Module 7: Health Analytics and Data Quality Integration
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Linking data governance to analytical outputs
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Ensuring quality in statistical and predictive modeling
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Case Study:Impact of data governance on disease surveillance analytics
Module 8: Stakeholder Roles and Data Stewardship
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Responsibilities and accountability frameworks
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Integrating departments and system owners
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Group Exercise: Mapping a data stewardship structure
Module 9: Designing and Implementing a Data Governance Strategy
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Blueprint development and execution planning
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Aligning with national health system strategies
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Workshop: Drafting a governance roadmap
Module 10: Monitoring, Evaluation & Continuous Improvement
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Governance performance indicators
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Implementing quality monitoring mechanisms
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Final Action Plan: Developing a long-term quality and governance improvement strategy
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Case Study: Successful implementation in a national health data system
Where the change lands
Personal Impact
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Enhances professional competency in managing data quality and compliance
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Strengthens analytical decision-making and data stewardship skills
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Increases confidence in implementing governance frameworks
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Positions participants for strategic roles in digital health transformation
Organizational Impact
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Improves accuracy of health analytics, reporting, and decision-making
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Strengthens data compliance with health regulatory bodies and data privacy laws
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Reduces risks related to data breaches, inaccuracies, and system inefficiencies
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Enhances reliability and trust in data used for health planning and research
Common questions.
Still not sure? Send us a note and a facilitator will get back to you within a business day.
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Course finder
Find the right course for you
Prefer to talk it through? Send us an enquiry and a facilitator will scope a fit within a business day.
For corporate teams
Training 10+ professionals?
We deliver Training on Data Governance and Quality Assurance in Health Analytics in-house at your offices, at a venue we arrange, or fully virtual. Customise the curriculum against your KPIs, and get a bespoke price for the cohort size you need.