Health and epidemiology
Health programme data, service utilisation and routine HMIS analytics, counted correctly and defensible under review.
Health decisions ride on data that is often incomplete, duplicated, or spread across systems that do not agree. Reported twice, recorded three ways, missing for a month. None of it shows up in a chart; it shows up in a decision that was slightly wrong, made confidently.
We clean and reconcile that data, separate what it genuinely supports from what it does not, and build the dashboards and models a health agency can stand behind, with every figure traceable to its source.
What we help with
From routine data to a figure you can defend.
Routine and HMIS analytics
Analysis and dashboards over routine health management information, including DHIS2-lineage sources, cleaned and reconciled before anything is reported.
Service utilisation dashboards
Live views of whether funded services are reaching enrolled beneficiaries, with funding streams kept honestly apart and a denominator that does not flatter.
Survey and prevalence analysis
Rigorous analysis of health and household survey data, with the method and assumptions stated plainly.
Data quality and reconciliation
Double-reporting, impossible dates and inconsistent naming surfaced and resolved transparently, not silently patched.
Statistical and epidemiological modelling
The analysis the question actually calls for, in Stata, R or SQL, chosen for the problem rather than for show.
Protected handling of personal data
Identifiers masked, sensitive fields generalised, and access scoped, within your governance framework.
Proof
A live, trustworthy utilisation dashboard, built from a messy source.
Our case studies include a live utilisation dashboard for a publicly funded health scheme, where separating the funding streams corrected an inflation that had overstated activity several times over, with every headline figure independently recomputed before handover.
Working on a health programme?
Tell us the decision the data has to support. If we are not the right fit, we will say so, and point you to someone who is.