A platform that asks clinicians to leave their EHR to use it will be used reluctantly, or not at all. Good integration determines whether a new system fits into that workflow or becomes another system clinicians have to work around.
Epic is the most widely deployed EHR in US health systems, and its integration surface is well defined. Most of the work is in the specifics of a given health system's configuration, and the protocol itself is the smaller part.
Pulling the demographics, problems, medications, results, and encounter data a platform needs, through the EHR's FHIR APIs, with the scopes and consent model the health system requires.
Putting a finding, an observation, or a document into the chart so the clinician sees it where they expect to. Mapping matters here. The wrong coding or unit makes a correct measurement read as something else.
Opening an application from inside the EHR with the current patient and user already established, so there is no re-authentication and no risk of acting on the wrong record.
Reacting to what happens in the EHR as it happens (an order placed, a result filed, a patient admitted) rather than polling for changes on a schedule.
Projects rarely get stuck on the standard. They get stuck on access and configuration: getting the right approvals from the health system, working within what their build exposes, and discovering that a field assumed to be populated is not, or is used differently at one site than another.
Planning for a test environment and a validation period against the real configuration, instead of the documentation, keeps the timeline honest.
Most real deployments involve both the modern API surface and older interface feeds from systems around the EHR.
We have delivered Epic integration alongside broader EHR integration work for healthcare data management, and built real time HL7 FHIR R4 exchange across every facility of a multi site hospital network as part of a HIPAA compliant cloud migration completed with no downtime at cutover.
HL7 v2, CCDA and report exports from an oncology EHR parsed, keyed to one master patient index and loaded into PostgreSQL on a schedule, for a healthcare data company.
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