SDG Monitoring Digital Tools for Health Training Course

Course Overview

SDG Monitoring Digital Tools for Health Training Course is designed to equip healthcare professionals, public health specialists, monitoring and evaluation officers, health program managers, epidemiologists, researchers, policymakers, and development practitioners with advanced knowledge and practical skills in monitoring, analyzing, and reporting Sustainable Development Goal (SDG) health indicators using modern digital technologies. As countries accelerate progress toward SDG 3: Good Health and Well-being and other health-related Sustainable Development Goals, healthcare organizations require robust Health Management Information Systems (HMIS), Results-Based Management (RBM), Monitoring, Evaluation, Accountability and Learning (MEAL), Universal Health Coverage (UHC), digital health transformation, health information systems, implementation science, evidence-based policymaking, and health systems strengthening to measure progress accurately and improve health outcomes. This comprehensive course enables participants to utilize innovative digital tools to collect, analyze, visualize, and communicate SDG health performance while supporting national and global reporting obligations.

The course provides participants with practical knowledge in SDG indicator frameworks, health data governance, digital data collection, performance measurement, indicator harmonization, dashboard development, geospatial analysis, statistical reporting, predictive analytics, artificial intelligence, cloud-based reporting, and healthcare decision-support systems. Participants will learn how to integrate DHIS2, Health Management Information Systems (HMIS), Electronic Medical Records (EMRs), SurveyCTO, KoboToolbox, Open Data Kit (ODK), Power BI, Tableau, Excel, SPSS, STATA, R, Python, GIS, and cloud collaboration platforms to monitor SDG indicators related to maternal and child health, communicable diseases, non-communicable diseases, nutrition, immunization, environmental health, emergency preparedness, health financing, and healthcare quality. The course demonstrates how digital technologies improve the timeliness, accuracy, transparency, and accessibility of SDG monitoring systems.

Participants will further explore advanced concepts including health data interoperability, FAIR data principles, data quality assessment, SDG metadata standards, geospatial intelligence, machine learning, predictive health analytics, real-time dashboards, performance scorecards, data visualization, policy analysis, implementation science, and digital innovation for health governance. Practical exercises emphasize transforming healthcare data into actionable intelligence that supports national development planning, donor reporting, healthcare investment decisions, and continuous quality improvement. Participants will also gain practical experience in integrating multiple data sources into unified digital reporting ecosystems that enhance accountability and strengthen evidence-informed healthcare policies.

Through instructor-led workshops, software demonstrations, practical laboratories, collaborative group exercises, field simulations, and comprehensive healthcare case studies, participants will gain hands-on experience in designing, implementing, and managing digital SDG monitoring systems. Upon successful completion of the course, participants will possess the technical expertise required to strengthen SDG monitoring frameworks, improve healthcare performance measurement, enhance evidence-based decision-making, support digital health transformation, promote accountability, and accelerate progress toward national and global health development goals across ministries of health, hospitals, universities, NGOs, humanitarian organizations, research institutions, and international development agencies.

Course Objectives

1. Understand the SDG health indicator framework and global monitoring requirements.
2. Design digital systems for monitoring health-related SDG indicators.
3. Utilize digital data collection tools for SDG health reporting.
4. Analyze SDG health indicators using advanced statistical software.
5. Develop interactive dashboards and visual reports for SDG monitoring.
6. Strengthen data quality, governance, and interoperability for SDG reporting.
7. Apply GIS and geospatial analytics to monitor health inequalities.
8. Integrate artificial intelligence and predictive analytics into SDG monitoring.
9. Produce evidence-based reports for national and international stakeholders.
10. Support strategic healthcare planning through digital SDG monitoring systems.

Organizational Benefits

1. Strengthens monitoring of SDG health indicators and national targets.
2. Improves healthcare planning through evidence-based decision-making.
3. Enhances compliance with international reporting requirements.
4. Strengthens monitoring, evaluation, accountability, and learning systems.
5. Improves healthcare data quality and governance.
6. Supports digital transformation within healthcare institutions.
7. Enhances donor confidence through transparent reporting.
8. Strengthens organizational capacity in health analytics and visualization.
9. Improves policy development using real-time digital evidence.
10. Accelerates progress toward Sustainable Development Goals and Universal Health Coverage.

Target Participants

This course is suitable for:

• Monitoring and Evaluation Officers
• Public Health Specialists
• Health Program Managers
• Ministry of Health Officials
• Epidemiologists
• Health Information Managers
• Data Analysts
• Health Researchers
• Hospital Administrators
• Policy Analysts
• Digital Health Specialists
• Biostatisticians
• NGO and Humanitarian Project Staff
• Development Partners
• Health Informatics Specialists
• GIS Specialists
• Quality Improvement Officers
• Healthcare Consultants
• SDG Coordinators
• Professionals responsible for SDG monitoring, health information systems, policy development, and healthcare performance management.

Course Outline

Module 1: Introduction to SDG Monitoring for Health

• Sustainable Development Goals overview
• SDG 3 framework
• Global health indicators
• National reporting obligations
• Indicator metadata
• Results-Based Management integration

Case Study: Developing a national SDG health monitoring framework for maternal and child health.

Module 2: Digital Health Information Systems

• Health Management Information Systems (HMIS)
• DHIS2 implementation
• Electronic Medical Records
• Data interoperability
• Health information architecture
• Digital governance

Case Study: Integrating HMIS and DHIS2 to strengthen SDG health reporting.

Module 3: Digital Data Collection Technologies

• SurveyCTO
• KoboToolbox
• Open Data Kit (ODK)
• Mobile data collection
• Cloud synchronization
• Field supervision

Case Study: Collecting community health data for SDG monitoring using mobile digital platforms.

Module 4: SDG Indicator Management

• Indicator selection
• Indicator calculation
• Performance tracking
• Target setting
• Metadata management
• Benchmarking

Case Study: Monitoring national immunization coverage against SDG performance targets.

Module 5: Data Quality and Governance

• Data quality assessment
• Data validation
• Data governance
• FAIR data principles
• Data security
• Compliance frameworks

Case Study: Improving healthcare data quality for national SDG reporting.

Module 6: Statistical Analysis and Health Analytics

• SPSS analysis
• R programming
• STATA applications
• Descriptive statistics
• Predictive analytics
• Trend analysis

Case Study: Analyzing maternal mortality trends using advanced statistical software.

Module 7: Dashboard Development and Data Visualization

• Power BI dashboards
• Tableau visualization
• Executive scorecards
• Healthcare dashboards
• Interactive reporting
• Data storytelling

Case Study: Developing interactive dashboards to monitor regional SDG health performance.

Module 8: GIS and Geospatial Intelligence

• Geographic Information Systems
• Disease mapping
• Spatial statistics
• Health inequality analysis
• Environmental health mapping
• Geographic decision support

Case Study: Mapping healthcare service accessibility to identify underserved populations.

Module 9: Artificial Intelligence and Digital Innovation

• Artificial Intelligence applications
• Machine learning
• Predictive modeling
• Big data analytics
• Automated reporting
• Decision-support systems

Case Study: Using AI-driven predictive analytics to forecast healthcare service demand for SDG planning.

Module 10: Reporting and Policy Communication

• National SDG reports
• Donor reporting
• Policy briefs
• Executive summaries
• Stakeholder communication
• Knowledge dissemination

Case Study: Preparing a comprehensive national SDG health performance report for international development partners.

Module 11: Monitoring, Evaluation, Accountability and Learning (MEAL)

• Results-Based Management
• Performance monitoring
• Evaluation integration
• Organizational learning
• Adaptive management
• Continuous improvement

Case Study: Integrating SDG monitoring into a national healthcare monitoring and evaluation framework.

Module 12: Emerging Trends in Digital SDG Monitoring

• Cloud-based health analytics
• Digital twins
• Blockchain for health data
• Learning Health Systems
• Precision public health
• Future innovations in SDG monitoring

Case Study: Designing an integrated national SDG digital monitoring ecosystem combining DHIS2, AI-powered analytics, GIS intelligence, Power BI dashboards, cloud computing, and real-time health performance reporting to accelerate progress toward Sustainable Development Goals.

General Information

1. Customized Training: All our courses can be tailored to meet the specific needs of participants.
2. Language Proficiency: Participants should have a good command of the English language.
3. Comprehensive Learning: Our training includes well-structured presentations, practical exercises, software demonstrations, web-based tutorials, collaborative group work, healthcare simulations, and real-world healthcare case studies. Our facilitators are seasoned experts with over a decade of experience in public health, monitoring and evaluation, health information systems, digital health, SDG reporting, data analytics, and health systems strengthening.
4. Certification: Upon successful completion of the training, participants will receive a certificate from Foscore Development Center (FDC-K).
5. Training Locations: Training sessions are conducted at Foscore Development Center (FDC-K) centers. We also offer options for in-house and online training customized to the client's schedule.
6. Flexible Duration: Course durations are adaptable, and content can be adjusted to fit the required number of training days.
7. Onsite Training Inclusions: The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a Certificate of Successful Completion. Participants are responsible for their travel expenses, airport transfers, visa applications, dinners, health/accident insurance, and personal expenses.
8. Additional Services: Accommodation, pickup services, flight booking, and visa processing arrangements are available upon request at discounted rates.
9. Equipment: Tablets and laptops can be provided to participants at an additional cost.
10. Post-Training Support: We offer one year of free consultation and coaching after the course.
11. Group Discounts: Register as a group of more than two participants and enjoy a discount ranging from 10% to 50%.
12. Payment Terms: Payment should be made before the commencement of the training or as mutually agreed upon, to the Foscore Development Center account. This ensures better preparation for your training.
13. Contact Us: For any inquiries, please reach out to us at training@fdc-k.org or call +254712260031.
14. Website: Visit www.fdc-k.org for more information.