Envision this:
You are evaluating vendors for Coverage Requirements Discovery (CRD) integration. Your vendors show you their validation reports and present their test results. They demonstrate compliance with HL7® FHIR®. Everything looks ready. Then you go live. And nothing works the way you expected.
This happens far too often in healthcare interoperability. Drummond’s Q2 2026 FHIRplace testing reveals why.
Seven vendors participated in the recent FHIRplace testing sprint, testing for CRD discovery. Seven vendors. Ten weeks. Real payer and provider systems. Real data flowing through organizational test transactions.
336 issues surfaced.
Not theoretical problems, not edge cases. Real incompatibilities that would have triggered support escalations, debugging sessions and delayed workflow if those vendors had deployed without structured testing.
Instead, they caught these issues in a controlled environment, fixed them before launching, and went live confident that their systems would actually work.
Here’s what the 336 issues revealed.
The 336 Issues Vendors Identified Before Go-Live
56% of those issues centered on coverage determination logic.
Here’s what we saw:
A vendor implemented a coverage rule according to the specification. The system implemented the same rule according to the specification. Both appear compliant. Interoperability is assumed. Then you exchange test data and discover the codes are mapped differently.
This scenario played out repeatedly across FHIRplace testing, but it wasn’t the only type of problem vendors encountered.
Beyond coverage determination, the remaining issues were distributed across authentication failures, structural gaps, endpoint-specific problems, and technical barriers.
The breakdown reveals the full scope: technical and transport layer issues accounted for 46 issues; structural gaps for 53; security and authorization accounted for 25; and the remainder was across coverage matching, trigger discovery and endpoint issues. But one category dominated.
Coverage determination issues represented 189 of the 336 total. They dominated not because they’re the only integration gaps vendors encounter, but because they represent the gap that lies between what the specification promises and what happens when production starts.
Why Coverage Determination Rules Diverge in Production
When systems are tested in isolation, that testing validates schema, cardinality, and data types. But isolated testing and vendor evaluation cannot surface issues that emerge when two systems exchange data with each other.
This is how FHIRplace helps.
Multi-party testing reveals what happens when “system A” connects to “system B” for the first time, and both systems must interpret the specification in the context of real-world data exchange.
Here’s a hypothetical example: Your system and a vendor’s system are each validated against the coverage determination rule that says “deny coverage if the patient has not met their deductible.”
Tested separately, with perfect test data, both systems confirm “the rule works correctly.”
However, in the real world, when the vendor submits a patient’s deductible information to your system, your systems interpret what that information means differently.
Your system reads it as: “Patient has not met their deductible. Rule says deny. DENY.”
Vendor system reads it as: “Patient is eligible despite deductible status. Rule allows approval. APPROVE.”
Same data. Same rule. Different answer.
Why does this happen?
Because neither system’s documentation defines exactly how to interpret deductible status in all scenarios. Your system didn’t build its logic from the specification. It built it over years of handling actual claims with your specific payers. You track deductibles separately by benefit type (medical, pharmacy, dental) because that’s how your plans are structured. You’ve learned which payer variations require special handling. You’ve embedded workarounds for edge cases that the specification doesn’t cover.
The vendor built their system the same way, but for a different customer base with different plan structures. They track deductibles universally because their customers typically have unified deductibles. Their embedded logic optimizes for that reality.
Both systems are internally consistent. Both work perfectly for the organizations they were built to serve. But when they try to exchange data, that institutional logic collides.
Same code, same specification, different institutional logic running underneath.
The only way to circumvent this problem is to leverage real-world multi-party testing.
The FHIRplace Credential That Changes Procurement
Each of the 336 issues uncovered represent a real integration failure that seven vendors caught during testing instead of after launch.
Code mapping mismatches, logic interpretation gaps, undocumented business rules that cause unexpected denials, support escalations, and workflow delays. These are systemic incompatibilities that could surface the moment systems try to exchange real world data. This is what the vendors in the FHIRplace testing sprint discovered. Without multi-party testing, you risk encountering similar issues during your integration deployment. Support teams could escalate; workflows may delay. You could spend months debugging problems you could have surfaced during testing.
The vendors in this testing chose a different path. They caught these gaps in a controlled environment, fixed them, and launched with confidence. You can make that same choice.
FHIRplace testing before go-live is not optional infrastructure. It is the primary way to avoid critical integration failures in production.
Contact us to participate in FHIRplace for your next vendor evaluation cycle.