API

​

Overview

​

New Endpoints

• POST /lab_report/v1/parser/job – Upload a lab report to create a parsing job
• GET /lab_report/v1/parser/job/ – Retrieve job status and extracted results

​

Key Features

• Multi-format support – Parse PDF, JPEG, and PNG lab reports up to 10 MB
• LOINC matching – Extracted biomarkers are matched to standardized LOINC codes for cross-lab comparability
• Human review option – Flag jobs for manual verification before completion
• Structured output – Get biomarker name, value, unit, reference range, and interpretation

​

Webhook Events

• lab_report.parsing_job.created – Triggered when a new parsing job is submitted
• lab_report.parsing_job.updated – Triggered when a parsing job status changes (completed, failed, pending review)

​

Use Cases

• Patient uploads – Allow patients to submit lab reports from other providers
• Historical data import – Digitize paper records and legacy PDFs
• Multi-source aggregation – Combine results from various labs using LOINC standardization

​

New Endpoint

• GET /v3/lab_test/lab_account – List lab accounts accessible to your team. Supports optional lab_account_id and status query parameters.

​

Updated Endpoints

• POST /v3/order/create – New optional lab_account_id parameter to specify which lab account to use. If omitted, the backend resolves the appropriate account automatically.
• POST /v3/order/import – Now accepts lab accounts in PENDING status, enabling order imports while accounts are still being set up.
• GET /v3/lab_tests/markers – New optional lab_slug query parameter to filter markers by lab. When a lab account is selected, you can use this to retrieve only the markers available under that lab.

​

Behavior

• When lab_account_id is provided, available panels and markers are filtered to those supported by the selected account’s lab.
• When recreating an order with update_reason=INCORRECT_LAB, the backend now resolves a fresh lab account rather than carrying forward the incorrect one.

​

What’s New

• Interpretation Filter – Filter orders by clinical result interpretation using the new “Interpretation” dropdown filter
• Critical Value Indicators – The orders table now displays visual indicators for orders with critical results
• Enhanced Order Details – Order detail views now include interpretation badges highlighting critical findings

​

Filter Options

• Normal – Orders with results within normal reference ranges
• Abnormal – Orders with results outside normal ranges but not critically urgent
• Critical – Orders with results requiring immediate clinical attention

​

Visual Enhancements

​

Orders Table

• Critical value indicators help you quickly spot high-priority results that need immediate attention
• Clear visual distinction between normal, abnormal, and critical interpretations

​

Order Details View

• Prominent badges display the interpretation status for easy identification
• Critical results are highlighted with distinctive styling to ensure they don’t go unnoticed

• Rename panel names
• Archive outdated or unused panels to keep things clean
• View archived panels using the “Status” filter and “unarchive” to make panels active again

1. Look for areas in your code where you take an action based on the values of a Junction-defined enum. For example, you might have Python code like this:

match status:
    case OrderStatus.TESTKIT_ORDERED:
        handle_ordered()
    case OrderStatus.TESTKIT_AWAITING_REGISTRATION:
        handle_awaiting_registration()
        # other cases...

2. Check unknown values in your code paths are handled gracefully—for example, by using default cases. Logging unknown values can help you stay informed.

match status:
    # previous cases...
    case unknown_status:
        logger.warning(f"Unknown status received: {repr(unknown_status)}")

3. Make sure you’re running the latest version of our SDK.
4. You’re good to go. Once you’ve checked the code paths won’t break if Junction-defined enums start including new values, no further action is needed.