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
Fees

USD 1,750 per participant