Global Health Systems & Outcomes Dataset
Purpose
To create an analysis-ready global dataset linking health-system capacity, health expenditure, universal health coverage, and key population health outcomes.
Source Datasets & Licences
Primary sources: WHO Data and selected World Bank indicators.
Many WHO datasets are available under CC BY 4.0 unless a specific indicator states otherwise. Each selected indicator will undergo a source and licence review before it is included in the final DataLab dataset.
What You Will Learn
- Working with international public-health indicators
- Understanding indicator definitions and comparability
- Preparing country-year health datasets
- Validating rates, ratios, units, and time periods
- Joining multi-source data responsibly
- Documenting limitations for public-health analysis
Expected Tasks
Participants may be assigned to:
- Extract health outcome and health-system indicators
- Review metadata, definitions, and units
- Standardise countries and years
- Check missingness, duplication, and outliers
- Merge selected WHO and World Bank fields
- Draft codebook and methodology notes
- Test the final dataset with sample analyses
Timeline & Weekly Commitment
- Week 1: Orientation, source review, and indicator assignment
- Week 2: Data extraction and metadata review
- Week 3: Cleaning, harmonisation, and merging
- Week 4: Validation and documentation
- Week 5: Quality review and final project presentation
Expected commitment: 4–6 hours per week.
Fee & What It Covers
Your $25 participation fee covers project guidance, documentation resources, quality-assurance review, contributor management, certificate eligibility, and access to the final project-learning materials.
Contributor Recognition Requirements
Recognition requires successful completion of assigned work, adherence to quality standards, documented contribution, and acceptance of feedback from the project lead.
Project Rules & Consent
Participants must cite all original data sources, comply with source-specific licence conditions, and avoid making health claims unsupported by the data. DataLab reserves the right to exclude work that does not meet quality or ethical standards.