Laying the foundation: why all FHIR projects need a strong start

Many FHIR modeling projects start with energy and ambition.

There is commitment from the organization, enthusiastic people on the team, and the intent to build something meaningful and future-proof. But somewhere between the initial excitement and the first deliverables, things start to go wrong.

We see it all the time: teams lose momentum, structures fall apart, implementation guides (IGs) end up looking messy and confusion creeps in. Not because people aren’t skilled or motivated, but because the foundation isn’t solid.

Common pitfalls from the field

In my work with clients around the world, I’ve guided many FHIR implementation teams through the early phases of their projects. And although every organization is different, the challenges they face at the start are surprisingly similar:

• There are no documented agreements on naming, versioning, or folder structure
• No clarity on how to collaborate in Simplifier.net
• No consistent feedback workflow, validation rules or publication process
• The IG lacks consistency, branding and usability
• People are figuring things out while trying to deliver results

One client said it best: “We thought we were modeling, but we were really improvising.” And that’s exactly where the Data Modeling Launch comes in.

Why we created the Data Modeling Launch

At Firely, we believe in starting strong. That means defining the right working agreements, tooling setup and modeling principles before diving into the deep end of FHIR profiling.

The Data Modeling Launch is a 3-week program designed to help teams set up their modeling environment the right way. It’s not a training and it’s not consulting by the hour. It’s a structured onboarding approach to help you:

• Make decisions about modeling conventions
• Set up your Simplifier.net projects professionally
• Start your IG with a consistent, branded structure
• Set up automated validation and QA processes
• Create the foundation for long-term collaboration

And we do all that with you not for you.

What you’ll walk away with

After three online workshops with your team, spread over three weeks, you’ll have:

• Profiling guidelines — covering naming conventions, profile governance, versioning, and feedback workflows
• Authoring workflow set up — including Simplifier.net project structure, sync strategies, and publishing options
• A branded IG template — visually consistent and easy to maintain, including templating and navigation logic
• Automated validation set up — enabling your team to run QA rules locally, in Simplifier.net, and in your CI/CD pipeline

In addition, we document everything in your project space so it’s accessible to your entire team, even after the sessions are done.

By the end, you’ll have a reusable, professional setup with clear workflows, consistent styling, and automated validation.

A structured approach to FHIR modeling

The Data Modeling Launch isn’t about teaching you what a profile is. It’s about helping you agree on how your organization wants to use profiles, what your release process looks like, and how you make your IGs understandable and maintainable.

In week one, we focus on tooling setup, the authoring workflow, and profiling guidelines. Week two is about example creation, validation and IG authoring. Week three is for publication, release management and feedback workflows.

This rhythm helps teams move from “we should start modeling” to “we have a working modeling setup” in just three weeks.

Once your modeling foundation is in place, you can confidently begin designing your FHIR profiles and building out your use cases.

Need more support?

Since the Data Modeling Launch doesn’t cover the actual design of your FHIR data models, our consultants are here to help. If you’re still looking for more, our FHIR data modeling training course provides an in-depth discussion of the conformance mechanism offered by FHIR.

Final thoughts

FHIR has the potential to transform the way we structure and exchange health data. But like any powerful framework, it needs to be applied with care and consistency. So if you’re starting a FHIR project, don’t leave your modeling setup to chance. Start strong.

👉 Discover the Data Modeling Launch