Lab Result Extractor

Pull the patient details, ordering provider, specimen data, and every test result with its value, unit, reference range, and flag from a lab report PDF.

The full guide: Analyte values and reference ranges from a lab report

How should we start?

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Start with a document

Upload a file or pick a sample, and see the fields come back.

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Questions about Lab Result Extractor.

Which lab report fields does the extractor read?

The report number and date, patient name, identifier (MRN), birth date and gender, the ordering provider name and NPI, the performing lab, the report type and category, specimen type with collection and received dates, and the report status.

Are the individual test results returned as a table?

Yes. The test results table returns one row per analyte with the test name, result value, unit, reference range, status, and result date. Each observation also carries its low and high reference bounds and an interpretation flag such as low, normal, high, or critical.

Does it follow a clinical data standard?

The field set is modeled on HL7 FHIR R4 DiagnosticReport and Observation resources with LOINC codes, so panels from different laboratory information systems map to the same columns, including the observation code, effective date, and issued date.

Can it handle a report with more than one specimen?

Yes. The specimens table returns each specimen type, its collection and received dates, and the container used, so multi-specimen panels stay intact alongside the results.

Is it safe to upload a report that contains patient data?

The report is processed via the Talonic API to extract the fields, is not retained for training, and is not shared. Treat identified PHI with care and redact where you can; for workflows that require a BAA, ask about the Talonic platform rather than the free tool. Uploads are PDF only, up to 10MB and 100 pages.

Doing this to one file, or to ten thousand?

The tool reads a single document. The platform reads the whole estate once and keeps it queryable — the same engine, with a memory.

See document data extraction if you run this for clinical and billing teams, or the extraction API if you are building it in.