Course Description

Health is a very sensitive sector in any economy. Most countries economic development is anchored in health sector. Due to the sector continued complexity and multi-faceted nature that warrant huge work in research, monitoring and evaluation, well-chosen and implementable monitoring and evaluation tools and techniques are inevitable. Such skills are useful in ensuring that health sector projects and programmes are implemented as designed and planned. This course equips the participants with adequate skills to develop and manage robust M&E systems for effective management of health related projects and programmes. Participants will be introduced to M&E frameworks indicators, tools and techniques for M&E. 

Learning outcomes

By the end of this course the participants will be able to:

• Design health sector projects using logical framework analysis approach
• Define different health indicators
• Track performance indicators over the life of the project
• Evaluate health projects and programmes against objectives and targets
• Conduct successful monitoring for health related projects and programmes
• Conduct impact evaluations of health related projects and programmes

Who should enroll?

This training course is recommended for researchers, project staff, development practitioners, managers and decision makers who work in health sector.

Why train with us

Vital Extra Learning guarantees our clients:

• State-of-the-art facilities and training infrastructure
• Extended tradition of hand-holding during post engagement
• Service delivery through highly seasoned industry experts.
• Value for money

TOPICS TO BE COVERED

Module 1: Introduction to M&E

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

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

Module 2: Data Collection and Quality in health programs

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

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

Module 3: Data Management and Analysis

Introduction to Stata

• Introduction to Statistics Concepts
• Stata Basics: Program window features, Data Structures and Types of Variables
• Data Management using Stata
• Output Management
• Basics of stata programming

Descriptive Statistics

• Describing quantitative data
• Describing qualitative data (Tabulating data with Stata)

Stata Graphics

• Graphing quantitative data
• Graphing qualitative data

Correlation, Chi-square and mean comparison analysis

Correlation  

• Correlation
• Subgroup Correlations
• Scatterplots of Data by Subgroups
• Overlay Scatterplots

Chi-Square 

• Goodness of Fit Chi Square All Categories Equal
• Goodness of Fit Chi Square Categories Unequal
• Chi Square for Contingency Tables

Comparing Means

• One Sample t-tests
• Paired Sample t-tests
• Independent Samples t-tests
• Comparing Means Using One-Way ANOVA 

Comparing Means Using Factorial ANOVA 

• Factorial ANOVA Using GLM Univariate
• Simple Effects

Module 4: Regression Analysis and Nonparametric Statistics 

Regression Analysis

• Assumptions of selected types of regression
• Linear regression; Binary logistic regression; ordered logistic regression; multinomial logistic regression and Poisson regression

Nonparametric Statistics 

• Mann-Whitney Test
• Wilcoxon’s Matched Pairs Signed-Ranks Test
• Kruskal-Wallis One-Way ANOVA
• Friedman’s Rank Test for k Related Samples

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

Module 5:

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

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