Introduction

Health data in FHIR format is rich but highly nested. Without a solid ETL pipeline and smart data modeling, you end up drowning in complexity.

It then becomes challenging how HL7 FHIR data flowing from a maternal health program can be used to generate the metrics used to compute value points for facilities in a program

In this guide, we’ll walk through the journey from raw FHIR bundles to dashboards, highlighting the architectural choices and open-source building blocks that make it all possible.

Who Should Read This?

Whether you’re a:

  • Data Engineer interested in orchestration, data modeling, and analytics pipelines
  • Product Manager or Digital Health Implementer evaluating integration, scalability, and deployment
  • Developer looking to customize or extend the solution
  • Health Informatics Expert exploring value-based care models powered by real-time, interoperable data

you’ll find everything you need to understand how we transform complex HL7 FHIR data into analytics-ready formats.

What is covered

  1. ETL Automation
    How we extract, transform, and load FHIR resources at scale while preserving data integrity. We assume you are using the resources defined in MNCH FHIR profile

  2. Data Flattening & Modeling
    The strategies we use to denormalize FHIR data for efficient metric calculation and reporting.

  3. Metric Computation
    Generating the ValuePoints metrics demonstrated for a maternal health program.

  4. Visualization & Reporting
    Turning flattened data into dashboards and reports that drive actionable insights.

By the end of this section, it’ll be clear how the ValuePoints Tool leverages open-source technologies to deliver a scalable, interoperable analytics solution for real-time health data.

Key Repositories

Below are the core projects that lead to the calculation of value points: