Digital health and analytics projects with real programme impact

Client, Ministry of Health and Ghana Health Service

Focus area, National analytics and dashboards

Challenge

Reporting was fragmented and slow, so national planners did not have a single, trusted view during the COVID 19 response.

Contribution

Designed and implemented a data pipeline and dashboard that combine routine data, quality checks, and simple forecasts for daily use by national and regional teams.

Impact

Faster decision cycles, clearer demand signals, and more informed allocation of logistics and human resources.

Technology used
Python, SQL, Power BI, PHP based APIs, secure hosting.

Client, Primary care and community health teams

Focus area, Community health and primary care

Challenge

Paper registers slowed follow up and made high risk households difficult to track across CHPS zones.

Contribution

Delivered a responsive app and web dashboard with offline friendly forms, referral workflows, and supervisory views for subdistrict and district managers.

Impact

Faster referrals, cleaner visit data, and clearer supervision for community health nurses and officers.

Technology used
PHP, Bootstrap, JavaScript, MySQL, light GIS mapping.

Client, Harmonised Health Facility Assessment

Focus area, Health facility assessment and planning

Challenge

Complex survey data from many facilities needed cleaning, scoring, and clear visual outputs for decision makers.

Contribution

Designed a relational data model and automated quality checks, scoring logic, and reporting views for national and regional teams.

Impact

Evidence to guide investments, benchmark facilities, and track quality of care trends over time.

Technology used
Python, R, SQL, Power BI.

Client, Thought leadership and training

Focus area, Surveillance and early warning

Challenge

Disease surveillance data arrives slowly and is not structured for early warning alerts.

Contribution

Showed practical time series and anomaly detection use cases based on routine data and DHIMS2 exports for program teams.

Impact

Greater interest among programme teams in using predictive models for surveillance and planning.

Technology used
Python, Jupyter, SQL, Power BI.

Client, Thought leadership and policy dialogue

Focus area, Future of personalised medicine

Challenge

Treatment decisions in many African settings do not yet use genomic insights or advanced risk profiling.

Contribution

Outlined how digital records, genomic data, and AI can work together for risk profiling and individual care plans in resource constrained settings.

Impact

Strengthened advocacy for investment in genomic and digital health infrastructure and skills.

Technology used
Genomic data platforms, AI models, digital health records.

Client, Health information system teams

Focus area, Health information system architecture

Challenge

Paper records and siloed systems limited visibility across CHPS, facilities, and national teams.

Contribution

Outlined architecture, data standards, and API patterns to move data flows into secure and connected digital platforms.

Impact

Clear roadmaps for stakeholders on how to modernise health information systems over time.

Technology used
PHP, APIs, DHIMS2 integrations, cloud hosting, integration tools.

Client, Programme and M and E teams

Focus area, Monitoring and evaluation

Challenge

Many programmes rely only on standard routine indicators and do not use richer data sources.

Contribution

Introduced data lakes, streaming data, and predictive methods as complements to standard monitoring and evaluation frameworks.

Impact

Programme teams saw new options for deeper analysis of performance and impact.

Technology used
Python, SQL, data warehouse tools, dashboards.

Client, Clinical services and teaching

Focus area, Clinical innovation and diagnostics

Challenge

Diagnostic services face heavy workloads and delays, especially in low resource settings.

Contribution

Showed how AI models can flag abnormal images and patterns in lab results and how to embed them in clinical workflows.

Impact

Raised awareness of both potential and ethical safeguards for AI in diagnostic pathways.

Technology used
AI vision models, decision support tools, integration with clinical systems.