Data Analysis & Research Track Overview
Module 2 of the HIC Exchange is the Data Analysis & Research track, designed for Group II — data scientists and policy leads. Where Module 1 focuses on getting data into the platform, this module is about what happens next: turning ingested routine health data into evidence that can change maternal and newborn health outcomes.
The track is built around the maternal and newborn health (MNH) analytics framework that Rwanda uses to answer its most pressing maternal health policy questions — what is the maternal mortality ratio, why are mothers dying, which factors are associated with those deaths, and how do routine figures compare with population-based survey estimates. The framework runs from data quality assessment all the way to decision-ready dashboards built in Apache Superset, the analytics layer of the health intelligence platform.
How the week unfolds
The sessions in this track follow a deliberate arc:
- The analytics framework — the conceptual foundations: the data-to-action chain, the four types of analytics, the national data sources, and how data quality is scored before any metric is trusted.
- Analytical products — how validated data becomes reusable datasets, metrics, charts, and dashboards that programme teams actually use.
- MMR estimation from routine data — a hands-on build of the maternal mortality ratio from DHIS2 routine data, enriched with case-level surveillance detail, culminating in a multi-tab situational-analysis dashboard.
- Policy write-up — translating what the dashboards reveal into a written policy product, so the analysis ends in a recommendation rather than a chart.
By the end of the week, participants have followed a single question — how do we reduce maternal mortality — from raw records through quality-scored data, a defensible metric, and a national dashboard, to a policy recommendation grounded in evidence.
Where to start
Begin with the MNH Analytics sub-module, which contains the core lecture on analytics foundations and the Superset lab where the maternal mortality analytics are built end to end. Then continue with the Data Governance sub-module — NHIC’s governance framework, data classification and quality standards, and the security, privacy, and legal-compliance practices that the analytics work operates under.