Health Program Evaluation Training Course

Health Program Evaluation Training Course

Introduction

Health Program Evaluation is a critical pillar in strengthening public health systems, improving health outcomes, and ensuring evidence-based decision-making in both public and private healthcare sectors. In an era defined by global health security, data-driven programming, and results-based management (RBM), organizations are increasingly required to demonstrate the effectiveness, efficiency, and impact of their health interventions. Health Program Evaluation Training Course equips participants with advanced competencies in monitoring and evaluation (M&E), impact assessment, and health systems strengthening, enabling them to design, implement, and assess high-quality health programs using internationally recognized frameworks.

The course integrates modern approaches such as digital health analytics, real-time data systems, performance indicators, and logic models to ensure that health interventions are not only implemented but also rigorously evaluated for sustainability and scalability. Participants will gain hands-on experience in data collection methodologies, epidemiological analysis, statistical interpretation, and program optimization strategies. By the end of the course, learners will be able to transform raw health data into actionable insights that drive policy formulation, funding accountability, and community health impact.

Course Duration

10 days

Course Objectives

1. Master Health Program Evaluation frameworks and global standards 
2. Apply Monitoring & Evaluation (M&E) systems in real-world health programs 
3. Design effective Logical Frameworks (LogFrame) and theory of change models 
4. Develop and track Key Performance Indicators (KPIs) in health interventions 
5. Conduct advanced health data analytics and interpretation
6. Strengthen skills in epidemiological evaluation methods
7. Implement results-based management (RBM) in health projects 
8. Utilize digital health information systems (DHIS2 & eHealth tools)
9. Perform impact assessment and outcome evaluation
10. Enhance data quality assurance and validation techniques
11. Build capacity in public health research methodologies
12. Integrate evidence-based decision-making in healthcare programs
13. Improve health system performance measurement and accountability

Target Audience

1. Public Health Officers 
2. Monitoring & Evaluation Specialists 
3. NGO & Development Program Managers 
4. Healthcare Administrators 
5. Epidemiologists and Biostatisticians 
6. Ministry of Health Policy Makers 
7. Donor Agency Program Officers 
8. Research Scientists & Health Data Analysts 

Course Modules

Module 1: Foundations of Health Program Evaluation

• Concepts of evaluation in public health 
• Types of evaluation: formative, process, outcome 
• Evaluation standards and frameworks 
• Role of stakeholders in evaluation 
• Case Study: Evaluation of immunization program coverage in rural clinics 

Module 2: Monitoring & Evaluation Systems

• M&E system design principles 
• Indicators development 
• Data flow structures 
• Feedback mechanisms 
• Case Study: HIV program M&E system in sub-Saharan Africa 

Module 3: Logical Framework Approach (LogFrame)

• Inputs, outputs, outcomes, impact structure 
• Theory of change mapping 
• Risk assumptions analysis 
• Indicator alignment 
• Case Study: Malaria elimination project LogFrame design 

Module 4: Key Performance Indicators (KPIs)

• SMART indicators development 
• Health performance metrics 
• Indicator tracking systems 
• Data visualization techniques 
• Case Study: Maternal health KPI tracking system in hospitals 

Module 5: Epidemiology for Evaluation

• Disease surveillance systems 
• Incidence and prevalence analysis 
• Study designs in public health 
• Outbreak investigation methods 
• Case Study: Cholera outbreak response evaluation 

Module 6: Data Collection Methods

• Quantitative vs qualitative methods 
• Surveys and questionnaires 
• Interviews and focus groups 
• Mobile data collection tools 
• Case Study: Community health survey for nutrition programs 

Module 7: Health Data Management Systems

• DHIS2 architecture and usage 
• Data entry and validation 
• Data security and governance 
• Reporting dashboards 
• Case Study: National health information system implementation 

Module 8: Statistical Analysis in Health Evaluation

• Descriptive and inferential statistics 
• Regression and correlation analysis 
• Hypothesis testing 
• Data interpretation techniques 
• Case Study: Vaccine effectiveness statistical evaluation 

Module 9: Impact Assessment Methods

• Causal inference approaches 
• Baseline and endline studies 
• Quasi-experimental designs 
• Counterfactual analysis 
• Case Study: Impact of HIV awareness campaigns 

Module 10: Quality Assurance in Health Data

• Data quality dimensions 
• Error detection methods 
• Validation frameworks 
• Audit systems 
• Case Study: Improving hospital reporting accuracy 

Module 11: Health Economics in Evaluation

• Cost-effectiveness analysis 
• Cost-benefit analysis 
• Resource allocation models 
• Efficiency measurement 
• Case Study: Evaluation of universal health coverage program 

Module 12: Results-Based Management (RBM)

• RBM cycle and principles 
• Performance tracking systems 
• Accountability frameworks 
• Results reporting 
• Case Study: Donor-funded malaria control program 

Module 13: Digital Health & eHealth Evaluation

• Mobile health applications 
• Telemedicine evaluation 
• AI in health analytics 
• Digital dashboards 
• Case Study: Telehealth adoption in rural healthcare 

Module 14: Reporting & Data Visualization

• Dashboard design principles 
• Storytelling with data 
• Policy report writing 
• Visualization tools (Excel, Power BI) 
• Case Study: National health performance dashboard 

Module 15: Capstone Health Program Evaluation Project

• Integrated evaluation design 
• Field or simulated project execution 
• Stakeholder presentation 
• Policy recommendation drafting 
• Case Study: Comprehensive evaluation of a national vaccination campaign 

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.