Training on Advanced M&E and Data Management for Health Programs

Introduction to Strategic Information in Health Programs

• Need for reliable information in health programs
• Components of strategic information
• Uses of strategic information
• Strategic information and program life cycle
• Decision making using strategic information

M&E System Strengthening for Health Programs

• Why M&E System strengthening in health?
• Use of M&E System strengthening tool
• Content of M&E System strengthening tool

Introduction to M&E

• Definition of Monitoring and Evaluation
• Why Monitoring and Evaluation is important
• Key principles and concepts in M&E
• M&E in project lifecycle
• Complementary roles of Monitoring and Evaluation

M&E Frameworks

• Conceptual Frameworks
• Results Frameworks
• Logical Framework Analysis (LFA)
• LogFrame – Design of projects using LogFrame

M&E Health Indicators

• Indicators selection
• Indicator metrics
• Linking indicators to results
• Indicator matrix
• Tracking of indicators

M&E Plans in Health Programs

• Importance of an M&E Plan
• Documenting M&E System in the M&E Plan
• Components of M&E Plan-Monitoring and Evaluation components
• Using M&E Plan to implement M&E in a Project

Data Collection Tools and Techniques

• Sources of M&E data –primary and secondary
• Sampling during data collection
• Qualitative data collection methods
• Quantitative data collection methods
• Participatory data collection methods
• Introduction to data triangulation

Gender Perspective in M&E for Health Programs

• Importance of gender in M&E
• Integrating gender into program logic
• Setting gender sensitive indicators
• Collecting gender disaggregated data
• Analyzing M&E data from a gender perspective
• Appraisal of projects from a gender perspective
• Issues with integrating gender into M&E

Data Quality in health programs

• Importance of data quality in health programs
• Data quality elements
• Routine Data Quality Assessments
• Data Quality Audit
• Data Quality Assurance

Qualitative Data Analysis in Health Programs

• Principles of qualitative data analysis
• Data preparation for qualitative analysis
• Linking and integrating multiple data sets in different forms
• Thematic and content analysis for qualitative data
• Manipulation and analysis of data using NVivo

Quantitative Data Analysis in Health Programs – (Using SPSS/Stata)

• Introduction to statistical concepts
• Creating variables and data entry
• Data reconstruction
• Variables manipulation
• Descriptive statistics
• Understanding data weighting
• Inferential statistics: hypothesis testing, T-test, ANOVA, regression analysis

Health Programs Evaluation

• Determining evaluation points from results framework
• Components of evaluations: implementation and process evaluations.
• Evaluation designs- experimental, quasi-experimental and non-experimental
• Performance evaluation process
• Evaluation findings sharing and dissemination

Data Demand and Use for Health Programs

• Using data to inform Policies and Programs
• Determinants of Data Use
• Understanding Data and Information Flow
• Linking Data to Action
• Knowledge management for data use in health programs

Use of GIS in M&E for Health Programs

• Benefits of using GIS in health programs
• Geographic approaches to global health
• GIS advantages for M&E in Health
• Using GIS software and data
• GIS data sources health related issues
• GIS analysis and mapping techniques