Monitoring and Evaluation for Health Programmes

Statement of Need

Monitoring and Evaluation (M&E) is central to effective health programme planning, implementation, accountability, and continuous improvement. Strong M&E systems enable health programmes to track progress, measure performance, assess outcomes, and generate evidence to support decision-making and resource allocation.

With growing digitalisation in health systems and increasing availability of routine and real-time data, artificial intelligence (AI) is transforming how monitoring and evaluation functions are designed and implemented.

AI-powered tools can automate data cleaning, improve analysis, predict emerging trends, identify programme risks, support real-time dashboards, and strengthen evidence based decision-making.

Who Attends

• Demonstrate a comprehensive understanding of the core principles, concepts, and established frameworks underpinning Monitoring and evaluation in health programmes.
• Design robust results-based M&E frameworks strategically aligned with programme goals and health priorities.
• Develop context-appropriate indicators, realistic targets, and comprehensive performance measurement plans for health programmes.
• Apply AI-supported tools in health data collection, cleaning, analysis, and visualisation.
• Analyse and interpret programme data using both conventional and AI-enabled methods.
• Utilize AI powered tools to detect emerging trends, predict risks, and generate actionable insights that support proactive and responsive health programme performance monitoring.
• Conduct evaluations and assess programme outcomes using evidence-based approaches.
• Prepare dashboards, reports, and visual summaries for communication with diverse stakeholders and audiences.
• Integrate M&E findings and AI-generated insights into programme learning cycles, adaptive management processes, and policy decisions.

How participants will benefit

• Foundations of Monitoring and Evaluation in Health Programmes
• M&E Framework Design, Indicators and AI-Enabled Data Systems
• Data Collection, Data Quality and AI for Data Analysis
• Evaluation, Learning and Predictive Analytics
• Reporting, Dashboards, Visualization and Use of Findings

Topics Include

• Designing and implementing stronger M&E systems for health programmes
• Apply AI tools to strengthen data analysis and reporting
• Improve programme performance monitoring and learning
• Use predictive insights for strategic decision-making
• Strengthen reporting quality, transparency and accountability
• Increase use of data and evidence in planning and policy