Introduction

In today's data-driven world, effective data management and analysis are essential for monitoring and evaluating (M&E) the performance of priority health programs. Accurate, timely, and actionable insights are crucial for improving health outcomes, optimizing resource allocation, and achieving program objectives. This training course equips participants with practical tools and techniques to collect, analyze, and interpret data effectively to drive evidence-based decisions in health program M&E.

Health programs face increasing complexity due to evolving health challenges, dynamic policy environments, and diverse stakeholder needs. This course addresses these challenges by focusing on the critical role of data in designing, implementing, and assessing health interventions. Participants will gain proficiency in data collection tools, statistical analysis, and visualization techniques to enhance program impact and accountability.

Organizations managing priority health programs must strengthen their data management and analysis capabilities to track progress, evaluate effectiveness, and report outcomes. This training provides a comprehensive framework for developing robust M&E systems, ensuring data quality, and leveraging digital solutions for real-time analytics. Participants will also learn to use key metrics to align program strategies with health goals.

The course emphasizes practical, hands-on learning tailored to the unique requirements of priority health programs such as maternal and child health, infectious disease control, and non-communicable disease prevention. By the end of this course, participants will be well-equipped to transform data into meaningful insights, fostering sustainable health interventions and policy development.

Programme Curriculum

Training Course on Data Management and Analysis for M&E in Priority Health Programmes

Introduction

In today's data-driven world, effective data management and analysis are essential for monitoring and evaluating (M&E) the performance of priority health programs. Accurate, timely, and actionable insights are crucial for improving health outcomes, optimizing resource allocation, and achieving program objectives. Training Course on Data Management and Analysis for M&E in Priority Health Programmes equips participants with practical tools and techniques to collect, analyze, and interpret data effectively to drive evidence-based decisions in health program M&E.

Health programs face increasing complexity due to evolving health challenges, dynamic policy environments, and diverse stakeholder needs. This course addresses these challenges by focusing on the critical role of data in designing, implementing, and assessing health interventions. Participants will gain proficiency in data collection tools, statistical analysis, and visualization techniques to enhance program impact and accountability.

Organizations managing priority health programs must strengthen their data management and analysis capabilities to track progress, evaluate effectiveness, and report outcomes. This training provides a comprehensive framework for developing robust M&E systems, ensuring data quality, and leveraging digital solutions for real-time analytics. Participants will also learn to use key metrics to align program strategies with health goals.

The course emphasizes practical, hands-on learning tailored to the unique requirements of priority health programs such as maternal and child health, infectious disease control, and non-communicable disease prevention. By the end of this course, participants will be well-equipped to transform data into meaningful insights, fostering sustainable health interventions and policy development.

Duration

5 days

Course Objectives

This training course aims to:

  1. Introduce fundamental concepts of data management and analysis in M&E.
  2. Strengthen understanding of data collection tools and techniques.
  3. Equip participants with skills to clean, organize, and analyze health data.
  4. Enhance knowledge of statistical software and data visualization tools.
  5. Build capacity to develop M&E frameworks for health programs.
  6. Address strategies for ensuring data quality and integrity.
  7. Explore the use of digital tools and dashboards for real-time M&E.
  8. Train participants in reporting and presenting data to stakeholders.
  9. Provide insights into linking data analysis with program decision-making.
  10. Facilitate learning through real-world case studies in health M&E.

Organizational Benefits

Organizations participating in this course will:

  1. Improve the effectiveness of their health programs through data-driven insights.
  2. Build internal capacity for robust M&E processes.
  3. Enhance accountability and transparency in program implementation.
  4. Strengthen the quality and reliability of data for informed decision-making.
  5. Develop real-time reporting mechanisms to track health program progress.
  6. Foster a culture of evidence-based planning and evaluation.
  7. Reduce inefficiencies and optimize resource allocation in health programs.
  8. Boost the organization’s compliance with donor and stakeholder requirements.
  9. Enhance program impact through data-informed strategic adjustments.
  10. Gain competitive advantage in securing funding through demonstrated M&E capacity.

Target Participants

  • Monitoring and Evaluation (M&E) professionals in health programs
  • Data managers and analysts in the health sector
  • Program managers and coordinators in priority health interventions
  • Healthcare administrators and policy-makers
  • Health informatics specialists
  • Researchers and academicians in public health
  • Donor and funding agency representatives
  • NGO staff involved in health programming
  • Students and early-career professionals in health M&E
  • Community health workers and program officers

Course Outline

Module 1: Foundations of Data Management in M&E

  1. Key concepts in M&E and data management
  2. Types of data and data sources in health programs
  3. Data collection methods: Surveys, interviews, and electronic systems
  4. Data quality assurance and validation techniques
  5. Case study: Identifying data gaps in a maternal health program

Module 2: Data Analysis Techniques

  1. Introduction to descriptive and inferential statistics
  2. Data cleaning, coding, and preparation for analysis
  3. Statistical tools and software: SPSS, Stata, and Excel
  4. Analyzing trends and patterns in health data
  5. Case study: Analyzing immunization coverage data

Module 3: Visualization and Reporting

  1. Principles of effective data visualization
  2. Tools for creating visual dashboards: Power BI, Tableau, and others
  3. Crafting data narratives for diverse audiences
  4. Developing concise and impactful M&E reports
  5. Case study: Presenting health program outcomes to stakeholders

Module 4: Digital Innovations in M&E

  1. Role of mobile technology in data collection
  2. Real-time monitoring through digital dashboards
  3. Integrating GIS in health program M&E
  4. Cloud-based platforms for collaborative data management
  5. Case study: Using digital tools in pandemic response monitoring

Module 5: Linking Data to Program Decision-Making

  1. Translating data insights into actionable recommendations
  2. Aligning program strategies with data-driven findings
  3. Building stakeholder buy-in through data evidence
  4. Evaluating the cost-effectiveness of interventions
  5. Case study: Adjusting intervention strategies using M&E data

Module 6: Monitoring and Evaluation Frameworks

  1. Designing logical frameworks and theory of change
  2. Setting indicators and performance targets
  3. Conducting baseline and end-line evaluations
  4. Addressing challenges in health program M&E
  5. Case study: Developing an M&E plan for an infectious disease program

Training Methodology

This course employs an interactive, participant-centered approach, featuring:

  • Expert-Led Lectures: Delivered by M&E professionals with extensive field experience.
  • Hands-On Workshops: Practical exercises on data analysis, visualization, and reporting.
  • Case Studies: Real-world examples of successful health program M&E practices.
  • Group Discussions: Collaborative problem-solving and peer learning.
  • Simulations: Practice scenarios for data collection and decision-making.
  • Digital Tool Demonstrations: Tutorials on using software and platforms for data management.

This methodology ensures participants gain theoretical knowledge and practical skills to strengthen their data management and analysis capabilities in health program M&E.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.com or call +254769199797 

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 FINESKILL TRAINING CENTER account, as indicated in the invoice so as to enable us prepare better for you.

Available Sessions

Aug 10 2026

10 Aug — 14 Aug 2026

online • Virtual session • Limited Availability
Aug 17 2026

17 Aug — 21 Aug 2026

online • Virtual session • Limited Availability
Aug 24 2026

24 Aug — 28 Aug 2026

online • Virtual session • Limited Availability
Aug 31 2026

31 Aug — 04 Sep 2026

online • Virtual session • Limited Availability
Sep 07 2026

07 Sep — 11 Sep 2026

online • Virtual session • Limited Availability
Sep 14 2026

14 Sep — 18 Sep 2026

online • Virtual session • Limited Availability
Sep 21 2026

21 Sep — 25 Sep 2026

online • Virtual session • Limited Availability
Sep 28 2026

28 Sep — 02 Oct 2026

online • Virtual session • Limited Availability
Oct 05 2026

05 Oct — 09 Oct 2026

online • Virtual session • Limited Availability
Oct 12 2026

12 Oct — 16 Oct 2026

online • Virtual session • Limited Availability
Oct 19 2026

19 Oct — 23 Oct 2026

online • Virtual session • Limited Availability
Oct 26 2026

26 Oct — 30 Oct 2026

online • Virtual session • Limited Availability
Nov 02 2026

02 Nov — 06 Nov 2026

online • Virtual session • Limited Availability
Nov 09 2026

09 Nov — 13 Nov 2026

online • Virtual session • Limited Availability
Nov 16 2026

16 Nov — 20 Nov 2026

online • Virtual session • Limited Availability
Nov 23 2026

23 Nov — 27 Nov 2026

online • Virtual session • Limited Availability
Nov 30 2026

30 Nov — 04 Dec 2026

online • Virtual session • Limited Availability
Dec 07 2026

07 Dec — 11 Dec 2026

online • Virtual session • Limited Availability
Dec 14 2026

14 Dec — 18 Dec 2026

online • Virtual session • Limited Availability
Dec 21 2026

21 Dec — 25 Dec 2026

online • Virtual session • Limited Availability
Dec 28 2026

28 Dec — 01 Jan 2027

online • Virtual session • Limited Availability