For the better part of a decade, “healthcare interoperability” has been treated as the finish line. FHIR APIs, HL7 v2 feeds, CommonWell, Carequality – an enormous amount of engineering effort has gone into making sure that clinical data can move between systems. And it’s worked. A referral can carry structured patient data. A payer can query a clinical data repository. An EHR can expose a FHIR endpoint that a third-party app can read from and write to.
But here’s the uncomfortable truth most healthcare IT teams eventually run into: getting the data to move is not the same as getting the work done.
The gap after the API call succeeds
Consider a referral. FHIR interoperability gets you a ServiceRequest resource landing cleanly in a specialist’s system, fully structured, with the right patient identifiers attached. That’s a real achievement. But now what?
- Someone still has to notice the referral arrived.
- Someone still has to check whether the clinical documentation is complete.
- Someone still has to determine urgency.
- Someone still has to decide whether prior authorization is needed before scheduling.
- Someone still has to follow up if the receiving provider doesn’t respond in a reasonable window.
- Someone still has to keep a record of who decided what, and when.
None of that is an interoperability problem. The data already arrived. What’s missing is the process that turns “data has arrived” into “the right next action happens, and is tracked to completion.” That’s orchestration, and it’s a fundamentally different engineering problem than data exchange.
Interoperability answers “can the data move.” Orchestration answers “what happens next.”
It’s worth being precise about the distinction, because the two get conflated constantly in vendor marketing:
Interoperability is about format and access: can System A read a structured, standards-compliant representation of something System B holds? FHIR, HL7v2, and X12 all live here. The output of good interoperability is availability – the right data, in the right shape, in the right place.
Orchestration is about behavior over time: given that data is now available, what sequence of steps, decisions, and approvals needs to happen, by whom, in what order, with what fallback if a step fails or times out? This is a workflow engine’s job – modeling states, transitions, retries, and human checkpoints – and it’s largely indifferent to how the underlying data got there.
You can have perfect interoperability and zero orchestration. That’s most healthcare software today: data flows beautifully between systems, and then it sits in an inbox, a worklist, or a fax queue waiting for a person to notice it, interpret it, and manually push it to the next step. The bottleneck moved from “can the systems talk” to “who notices, and how fast.”
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