Training Course on Workshop On Monitoring And Evaluation For Health Programs

Module 1: Introduction to Monitoring and Evaluation in Health Programs
Foundations of M&E
Definition, purpose, and key concepts: monitoring vs. evaluation, indicators, outputs, outcomes, and impact.
Differences between formative, process, outcome, and impact evaluations.
Importance of M&E in Health Programs
Enhancing accountability, transparency, and evidence-based decision-making.
Supporting continuous improvement and policy development.
Program Cycle and M&E Integration
Understanding how M&E fits into program planning, implementation, and scaling.
Activity: Review existing health programs and identify gaps in their M&E components.

Module 2: Designing M&E Frameworks
Logic Models and Results Frameworks
Linking inputs, activities, outputs, outcomes, and impact.
Mapping causal pathways for program success.
Setting Goals, Objectives, and Indicators
SMART indicators: Specific, Measurable, Achievable, Relevant, Time-bound.
Balancing quantitative and qualitative indicators for comprehensive evaluation.
Alignment with Program Objectives
Ensuring M&E frameworks reflect organizational goals and stakeholder priorities.
Workshop: Develop a results framework for a hypothetical health intervention, including KPIs and expected outcomes.

Module 3: Data Collection and Management for M&E
Data Sources and Collection Methods
Routine health information systems, surveys, focus groups, interviews, and observation.
Selecting appropriate methods for different program types and objectives.
Data Quality Assurance
Cleaning, validation, and verification techniques to ensure accuracy and reliability.
Addressing missing data, biases, and inconsistencies.
Data Storage and Ethical Considerations
Maintaining confidentiality, privacy, and compliance with regulations.
Digital Tools for Data Collection
Mobile data collection apps, electronic surveys, and cloud-based platforms.
Exercise: Develop a data collection plan and practice cleaning and managing sample health datasets.

Module 4: Data Analysis, Interpretation, and Reporting
Quantitative Data Analysis
Descriptive statistics, trend analysis, and basic inferential methods.
Using Excel, SPSS, or other software for analysis.
Qualitative Data Analysis
Coding, thematic analysis, and interpreting narratives from interviews and focus groups.
Data Visualization and Reporting
Creating charts, tables, dashboards, and GIS maps to communicate findings effectively.
Stakeholder-Oriented Reporting
Tailoring reports to policymakers, funders, and program teams.
Simulation: Analyze sample M&E datasets and prepare a comprehensive report with actionable insights.

Module 5: Using M&E for Program Improvement and Decision-Making
Translating Data into Action
Identifying gaps, successes, and areas for improvement.
Linking evaluation findings to decision-making and program adjustments.
Integrating M&E into Strategic Planning
Using results to guide resource allocation, program scaling, and policy formulation.
Continuous Learning and Feedback Loops
Establishing mechanisms for regular review, reflection, and adaptation.
Sustainability and Capacity Building
Building organizational capacity for ongoing M&E and evidence-based practice.
Capstone Project: Design a complete M&E plan for a health program, including framework, indicators, data collection methods, analysis plan, reporting
strategy, and recommendations for improvement