REDCap is free to license through Vanderbilt's consortium for qualifying institutions — but "free to license" doesn't mean "free to run." Someone still has to provision the server, configure SSL, keep PHP and MySQL patched, manage the DEV/TEST/PROD pipeline, and handle the HIPAA-relevant infrastructure controls. That gap is where commercial hosting options like REDCap Cloud step in — and where their pricing model becomes a real constraint for active research programs.

The per-project pricing problem

REDCap Cloud and similar platforms typically price per active project, which means your infrastructure cost scales directly with your research output. A program running five studies pays roughly five times what a program running one study pays, even though the underlying server infrastructure required doesn't scale linearly at all. For institutions actively growing their research portfolio, that pricing model works against the exact behavior — launching more studies — that the institution wants to encourage.

What flat-rate managed infrastructure looks like instead

The alternative is managed infrastructure priced on server tier and support level, not project count. One properly configured REDCap environment can run unlimited projects at no additional cost, because the constraint was never "how many projects" — it was "how much server capacity and administrative attention." A managed provider handles:

What to Ask Before Signing

Is pricing per-project, per-server, or flat-rate? What's included in "support" — is it infrastructure only, or does it include REDCap application-level help? Who executes the BAA, and does the provider have zero access to your actual REDCap data, in line with the consortium license terms?

For institutions where REDCap is one piece of a broader research and public health data infrastructure — sitting alongside data lakes, interoperability pipelines, or EMPI systems — the case for flat-rate managed infrastructure gets even stronger: it's one predictable line item instead of a cost that grows every time a new study launches.

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Whether it's a data lake that needs building, an EMPI that needs replacing, or a document pipeline eating your team's time — start with a real conversation.

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