A healthcare integration should demonstrate that the correct information reaches the correct record, is interpreted under agreed definitions and has a visible acceptance or rejection outcome. Define identity, units, terminology, versions and correction rules alongside the API connection. A successful network response does not establish semantic or operational correctness.
Let’s plan your healthcare integration.
Bring your requirements and the decisions you need to make. We’ll help you clarify the scope, explore the trade-offs and plan the next step.
Define an interface contract
Choose one exchange and its purpose. Identify the originating system, receiving system, data owner, authorised audience and expected timing. Record which application owns corrections and what happens to records already received.
The HL7 FHIR overview describes resources and healthcare information exchange. Implementations still need agreed versions, profiles, terminology and validation appropriate to their exchange; the label FHIR does not remove those decisions.
Write a mapping and acceptance worksheet
| Boundary | Requirement to document | Failure to demonstrate |
|---|---|---|
| Identity | Identifier authority and matching rules | Record cannot be matched safely |
| Structure | Required fields and profile/version | Missing or invalid element |
| Meaning | Units, codes and status definitions | Valid format with wrong interpretation |
| Timing | Event time and processing time | Delayed or out-of-order update |
| Correction | Link to original information | Received value later amended |
| Delivery | Stable exchange identifier and acknowledgement | Timeout after acceptance |
| Access | Permitted source and recipient | Request crosses an access boundary |
The worksheet is for technical discovery. Clinical meaning and acceptance decisions need appropriate domain ownership rather than assumptions made by the integration code.
Separate transport, validation and use
Track whether an exchange was sent, received, structurally validated and accepted into the intended workflow. These states may occur at different times and require different evidence.
Preserve a rejected record and its reason under the agreed data-handling policy. Identify who can resolve the issue, whether a corrected submission is expected and whether downstream work must pause. Avoid silently discarding an error because the sending application already marked the message complete.
Test an illustrative correction
Suppose an external system transmits a result, then issues a correction using an agreed reference. The receiving system should associate both messages with the intended record and make their relationship understandable to authorised staff.
Test the correction arriving before a delayed original, a duplicate transmission and an acknowledgement lost after acceptance. Define the handling with clinical and technical owners. This scenario tests information integrity; it does not recommend how a clinician should interpret or act on a result.
Reconcile the exchange population
Count exchanges in meaningful units: messages, records or business events as appropriate. Explain accepted, pending, rejected and superseded items without confusing a retry with a new outcome.
Set responsibility for investigating differences between systems. A grand total alone can conceal incorrect associations, so include record-level tracing and authorised sample review.
Questions implementation teams ask
Can a schema validator establish compatibility?
It checks part of the contract. Identity, terminology, timing, authorisation and the receiving workflow also need evidence.
Should rejected messages retry automatically?
Distinguish temporary delivery failures from business or data rejection. Repeating an invalid payload does not resolve its cause.
Prepare the integration brief
Bring authorised example exchanges, mappings and correction scenarios. Review the API requirements checklist and healthcare development scope before committing to delivery estimates.