Turning clinical patient data into research-grade intelligence.
Hembox is a national registry that standardises how disease is captured, tracked, and understood across every department and facility — the foundation for research, clinical decision support, and the data-driven tools we're building next.
One record per patient, not a folder per department.
Clinical disease data in Nigeria has largely been tracked on paper, in silos — department by department, facility by facility. Hembox brings that data onto one standardised platform built to onboard every department, not just one — so clinicians get a complete patient picture, and researchers, for the first time, get a dataset large and clean enough to actually learn from.
- 01Standardised capture.One structured record per patient, across every participating facility and department.
- 02Automated clinical scoring.Validated staging and risk scores — starting with ISS, R-ISS, Sokal, and IPSS-R for haematology — computed instantly from entered data, not by hand.
- 03Built for the local context.Diagnostic delay, financial toxicity, and drug availability tracked as first-class data, not an afterthought.
Connecting Clinical Data.
Advancing Research.
Improving Patient Outcomes.
That's the whole plan, in one line. Everything below is how we're getting there.
One core platform. Every department plugs in without touching it.
New diseases — in any department — plug into the registry through a fixed contract. The patient record, scoring engine, and timeline never get rewritten to make room. That's not a promise, it's the architecture: 14 haematology modules already prove it holds, and the same pattern is what every future department will use.
Stays stable, per department
Patients, accounts, and facility isolation — patients, accounts — are the one layer every module attaches to and none of them modify.
One folder, one contract
Each disease app — haematology today, any department next — ships its own eCRF schema, models, and staging logic, then registers itself. No core release required to add the next one.
One scoring engine
Department-specific calculators like ISS, Sokal, and IPSS-R register into one disease-agnostic engine, so every module — in any department — gets audit-grade, server-computed scores.
A registry is the first layer.
The goal is a platform that keeps getting more useful as more facilities join and more data accumulates.
Unified patient registry
Demographics, history, labs, treatment, and outcomes — one record per patient, shared safely across facilities with strict access control.
Disease modules, department by department
14 haematology modules live today — Multiple Myeloma, the leukaemias, lymphomas, MDS, MPN, and more — each on the same pluggable architecture every future department will use.
Research-ready data pipeline
De-identified, validated, export-ready datasets — built for cohort studies, survival analysis, and machine learning, not just chart review.
Clinical intelligence, next
Lab-trend analytics, decision-support alerts, and predictive models trained on the registry itself — the long-term goal this data collection makes possible.
Built in phases, deliberately.
A solid core first, then the layers that turn a registry into a research and intelligence platform.
Core registry & all 14 haematology disease modules. Patient records, role-based access, facility isolation, and full eCRF + automated scoring for every module are built and working.
Research data pipeline & warehouse. De-identification, validated exports, and the data foundation the next phase's models will train on.
Decision support, national analytics & interoperability. AI-assisted data quality, predictive models, and dashboards built on real data volume from participating facilities.
Building or researching in this space?
We're onboarding partner facilities and departments, and talking to researchers, clinicians, and collaborators as the platform comes together.