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Om Jariwala
Om Jariwala

Posted on AI-assisted

Designing an EHR Integration Layer for a Telehealth Platform

#ehrintegration #healthcare #discuss #devchallenge

When developers hear “EHR integration,” the first thought is usually an API.

But a production telehealth platform needs more than an API client.

It needs an integration layer that can handle authentication, mapping, retries, errors, synchronization and external-system failures.

A simplified architecture looks like:

Patient App
     |
     v
Telehealth API
     |
     v
Integration Layer
     |
     +------> EHR
     |
     +------> Lab
     |
     +------> Pharmacy
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What should the integration layer handle?

1. Authentication

The integration layer should manage the authentication mechanism required by the target system.

Don't spread EHR credentials and integration logic throughout the core application.

Keep the external integration boundary explicit.

2. Data Mapping

Your internal patient model may not match the external EHR representation.

For example:

Telehealth Patient
    |
    +-- firstName
    +-- lastName
    +-- dateOfBirth
    +-- email
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may need to map into a FHIR Patient resource or another format supported by the EHR.

The mapping should be explicit and testable.

3. Patient Identity

This is one of the hardest parts.

The same patient can have different identifiers across systems.

You need a reliable strategy for:

  • Existing patient lookup
  • Patient creation
  • Identifier mapping
  • Duplicate prevention
  • Reconciliation

4. Retry and Idempotency

Consider this:

Telehealth Backend
      |
      | Create Encounter
      v
     EHR
      |
      X Timeout
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Did the EHR reject the request?

Or did it process the request but the response never reach your application?

Retrying blindly could create a duplicate.

This is where idempotency and transaction tracking matter.

5. Failure Handling

External healthcare systems can fail.

Your integration layer should have a defined strategy for:

  • Timeouts
  • Rate limits
  • Authentication failures
  • Validation failures
  • Temporary outages
  • Partial failures

Queues can help decouple patient-facing workflows from slower external operations where the workflow allows it.

Read vs Write

A basic integration might only retrieve:

EHR → Telehealth
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A mature workflow may require:

EHR → Telehealth
Telehealth → EHR
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For example:

Patient
   |
   v
Telehealth consultation
   |
   v
Clinical documentation
   |
   v
Integration Layer
   |
   v
EHR
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The second direction is often where integration requirements become more complicated.

Test the workflow, not just the endpoint

A successful API response isn't enough.

Test:

  • Existing patients
  • New patients
  • Duplicate patients
  • Failed requests
  • Retry scenarios
  • Missing data
  • EHR downtime
  • Duplicate submissions
  • Write-back failures

An EHR integration is production-ready when the surrounding workflow has predictable behavior, including failure scenarios.

Final thought

The integration layer is not just plumbing between two APIs.

It is a boundary between two systems with different data models, identifiers, failure modes and workflows.

Design that boundary carefully, and future EHR integrations become much easier to manage.

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