M & E, Data Management & Analysis for Health Sector Programmes

AJT Monitoring and evaluation (M&E) skills are fundamental to the process of designing and implementing programs, analyzing and using data, and conducting advocacy for population and health programs. In order to build the capacity of M&E professionals who are actively engaged in the health sector, this one week course will provide hands-on training in M&E systems and the application of M&E data to decision making in health programming. The workshop offers intensive training that will cover the fundamental concepts and tools for M&E in health programs. Data management and analysis will be done using Ms Excel and Stata but participant can also opt for either SPSS or R. This workshop also presents a practical guide for using a geographic information system (GIS) to integrate, visualize, and analyze geographically-referenced data extracted from key data sets to facilitate monitoring and evaluation (M&E) of HIV/AIDS and related health programs.

• Government Departments & NGOs
• Health experts & Social Care staff in various sectors like Education & Health
• Medical staff in community development tasked with implementation and developing Health policies.

• To learn how to design an M&E-system including assessments for food and nutrition security programmes.
• To Understand the principles of participatory and learning orientated planning, monitoring and evaluation in food and nutrition security
• Understand the role of food and nutrition security in attaining the SDGs
• Have a clear idea for improving M&E systems and impact assessments for food and nutrition security

• Introduction
• Data use frameworks and key concepts
• Data demand
• Information availability

• Introduction
• Data analysis key concepts
• Types of variables
• Basic analysis

• Numerical summaries for discrete variables
• Tables for dichotomous variables
• Tables for categorical variables
• Tables for ordinal variables
• Graphs and charts for dichotomous and categorical variables
• Graphs and charts for ordinal variables
• Tabulations for summary statistics for continuous variables
• Graphs and charts for continuous variables

• Planning for qualitative data analysis
• Reviewing the data
• Organizing your data
• Coding the data
• Introduction to using qualitative data analysis software (NVivo)

• Planning for qualitative data analysis
• Comparison of Data analysis packages
• Basics for statistical analysis
• Testing for normality of data
• Choosing the correct statistical test
• Hypothesis testing
• Confidence intervals
• Tests of statistical significance (Parametric and non-parametric tests)
• Hypothesis testing versus confidence intervals
• Interpreting the data

• Introduction to Impact Assessment
• Programme Design Implications
• Impact Assessment in Programme Design

• Overview of Methods and Approaches
• Comparison overtime (Time series)
• Comparison over space (Sub-national comparisons)
• Counterfactual comparison (With/without project or programme)
• Quantitative Methods: Household Surveys
• Quantitative Methods: Secondary Data
• Qualitative Methods
• Selecting Methods and Approaches

• What is M&E?
• M&E Plans
• M&E Frameworks
• Indicators
• A core set of priority indicators for Health and Social Care programmes
• Data sources collection and use
• Defining a good M&E system
• Relating Monitoring and evaluation to your project cycle
• Including M&E in Health and Social Care programme design
• Identifying the challenges facing Monitoring and evaluation professionals in the Health and Social Care sector
• Participatory M&E systems
• Setting up an M&E strategy in Health and Social Care programmes
• International framework (MDG and SDGs)

• M&E Frameworks basics for Health and Social Care programme - M&E in Health and social care programme context - M&E Frameworks - Developing M&E frameworks - Linking M&E frameworks to indicators - Using data - Logical framework approach to the monitoring and evaluation of Health and Social Care development projects

• Introduction to M&E in Gender and Health
• Prioritizing gender in M&E plans
• Exploring gender in M&E plans
• Selecting indicators to measure gender related outputs and outcomes
• Gender considerations for data collection, interpretation and use

• Agree on the purpose and principles of the project M&E system
• Agree on and design core documents to setup an M&E system
• Establish project M&E system
• Agree on field monitoring data collection and management process
• Agree on Monitoring data analysis process
• Agree on process for monitoring data utilization and reporting
• Review and revise M&E plans based on progress
• Agree on process of evaluation management

• What it is
• Tracking inputs and outputs
• Tools for monitoring inputs and outputs

• Early results and outcomes (Access, use and satisfaction)
• Sector and national level outcomes

• Communication and reporting for M&E
• Contemporarily methods of disseminating

• Data collection methods: How to undertake data collection (quantitative and qualitative)
• M&E field trips
• Increasing questionnaires response rates
• Data collection versus data analysis
• Data quality and data management
• Data quality dimensions
• Functional areas of data management systems
• Double counting
• Obtaining data from Social media

• ICT innovations
• Data collection implementation models
• Key choice of application to collect data in rural areas
• ICT tool for Data processing
• Using Mobile phones for data collection
• Dashboards; analytics, data management and stakeholders access
• Case study