Global Health Informatics Certificate — Data, Systems & Equity

Learn to design, analyze and implement health information systems and data-driven interventions that improve health outcomes and equity worldwide. Hands-on with DHIS2, EHR workflows, R/Python & data governance.

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Digital Doctors

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0 Hours

18 Enrolled

English

Last updated

Thu, 02-Oct-2025

Course description

Global Health Informatics bridges public health, clinical care, data science, and systems design to improve population health and health equity across borders. This practical, career-focused course teaches you how to collect, clean, analyze, protect, and use health data to inform policy, strengthen health systems, and deploy digital health solutions in low-resource and transnational contexts.

You will learn the full informatics lifecycle: needs assessment and system design; standards and interoperability (including common data models and coding systems); data management and quality; analytical methods for surveillance and program monitoring; implementation science for digital tools; and the ethical, legal, and equity considerations that must guide every project. The course balances conceptual frameworks with hands-on labs using real-world tools and datasets (examples: DHIS2 workflows, basic EHR concepts, SQL queries, and reproducible analyses in R/Python).

Ideal for public health practitioners, clinicians exploring digital health, data analysts entering global health, program managers, and policy makers. By the end of the course you’ll be able to design pragmatic data systems, perform core analyses for decision-making, and lead ethically grounded informatics projects that prioritize fairness and local ownership.

Format & what’s included: modular online lessons, recorded lectures, case studies from multiple regions, practical labs, a short capstone project (design or evaluation of a digital health/data system), and curated resources for further learning.

What will i learn?

  • Describe core concepts, scope, and stakeholders in global health informatics and how they relate to health equity.
  • Map health information workflows in clinical and public health settings and identify data capture points and bottlenecks.
  • Apply interoperability and data standards principles (e.g., HL7/FHIR concepts, coding systems) to design interoperable systems.
  • Perform basic health data management tasks: data cleaning, validation, transformation, and storage best practices.
  • Build reproducible, documented analyses using SQL and an analytics language (R or Python) to support surveillance and program monitoring.
  • Use visualisation and dashboarding techniques to communicate indicators and trends to decision-makers.
  • Design an implementation plan for a digital health intervention, integrating user needs, ethics, privacy, and sustainability.
  • Critically evaluate informatics solutions for equity, data protection, and local ownership, and propose mitigation strategies.
  • Lead a small capstone project that demonstrates application of informatics methods to a real or simulated global health problem.

Requirements

  • Prerequisites (recommended): Basic understanding of public health or clinical care concepts (epidemiology, health systems). Fundamental statistics literacy (descriptive stats, rates). No prior programming required, but comfort with spreadsheets is expected. Students with beginner experience in R/Python/SQL will move faster in labs.
  • Technical requirements: Laptop/desktop with reliable internet access. 8+ GB storage recommended. Modern browser (Chrome/Firefox/Edge). Ability to install free/open-source tools (R/RStudio or Python + Jupyter) and access to an Excel/CSV editor. Access to a cloud sandbox or VM may be provided for hands-on DHIS2/EHR labs (or instructions to use hosted instances).
  • Ethics & data protection: Completion of a short module on data ethics, privacy and local regulatory considerations is mandatory before working with real datasets. Commitment to adhere to data sharing agreements and de-identification standards during labs and the capstone.
  • Time commitment & assessment: Suggested 8–12 weeks (part-time) or an intensive 4-6 week sprint depending on delivery. Assessments: weekly quizzes, lab assignments, peer review, and a capstone project. Certificate issued upon successful completion.

Frequently asked question

Practicing public health professionals, clinicians, program managers, data analysts, and students who want practical skills to design, implement, or evaluate health information systems with a global lens. No advanced coding required.

No—basic spreadsheet skills are sufficient to start. Optional tracks and labs introduce R or Python and SQL for those who want analytic depth. We provide step-by-step notebooks and templates.

Core concepts apply broadly; hands-on labs typically include DHIS2 workflows, EHR data concepts, SQL for queries, and reproducible analysis in R or Python. Dashboarding and basic data visualization are also covered.

No — case studies come from diverse settings (low-, middle-, and high-income countries) so you gain transferable skills adaptable to local context and transnational programs.

Yes — participants who complete the required assessments and capstone receive a certificate of completion. Optional verified/certificate tracks may be available depending on the provider.

A mandatory module covers data protection, informed consent for digital health, de-identification, governance, and equity considerations. Real-world labs use simulated or fully de-identified datasets.

Roles include health informatics officer, data analyst for NGOs, digital health program manager, surveillance analyst, EHR implementation specialist, and monitoring & evaluation (M&E) data lead.

Formats vary. Typical offerings include a mix of self-paced modules and scheduled live Q&A or workshops for labs and capstone mentoring.

Availability depends on the course provider. Many institutions offer scholarships or reduced fees for learners from low- and middle-income countries—check the specific offering page.

Capstones are evaluated on a rubric covering problem definition, system design or analysis, ethical considerations, feasibility, and clarity of communication. Peer feedback is often included.

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Free

Lectures

35

Skill level

Beginner

Expiry period

Lifetime

Certificate

Yes
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