Healthcare & clinical

Healthcare Document Extraction — Intake Forms, Lab Reports & Prescriptions

Extract patient details, diagnoses, medications and lab results from intake forms, clinical notes and insurance documents automatically. HIPAA-friendly, no manual entry.

7 min readUpdated April 27, 2026
70%
reduction in administrative time spent on document handling

What DocPeel extracts

No fixed columns or rigid schema. The LLM reads your document and returns clean, structured JSON automatically — or you define your own template to control the exact output shape.

Smart auto-extraction
Upload any document and the LLM intelligently surfaces all relevant data as clean JSON. No schema setup, no field mapping — it adapts to whatever your document contains.
Custom templates
Need specific field names, data types, or a fixed output structure? Define a template once and every extraction follows your schema exactly.

The administrative burden driving clinician burnout

Healthcare professionals spend nearly two hours on documentation and administrative tasks for every hour of direct patient care. Patient intake forms arrive on paper. Referral letters come as faxed PDFs. Lab results are emailed as image attachments. Insurance pre-authorisations require manual data re-entry into multiple portals.

Each of these documents contains structured information — names, codes, values, dates — that is immediately useful if it can reach the right system. The bottleneck is not data availability; it is the manual effort of extracting it.

DocPeel removes that bottleneck. Upload any clinical document and receive a structured JSON payload within seconds — ready to populate an EHR field, create a task, or trigger a workflow.

Document types DocPeel handles in healthcare

Patient intake and registration forms: extract demographics, emergency contacts, insurance details, and consent indicators from any form layout — paper-scanned or digital.

Referral letters: pull the referring physician, referred specialty, clinical summary, diagnosis codes, and urgency level from any referral format, regardless of which clinic or system generated it.

Prescriptions: extract medication name, dosage, frequency, route, prescribing physician NPI, and issue date. Works with both handwritten and printed prescriptions.

Lab reports: extract test names, result values, units, reference ranges, and collection dates — including panel results where many tests appear in a single report.

Insurance and billing documents: extract policy holder details, claim numbers, procedure codes (CPT), diagnosis codes (ICD-10), amounts billed, and payment status.

Handling variability in clinical document formats

Healthcare documents are among the most format-variable documents in existence. Every hospital, clinic, and laboratory uses a different form layout. The same information — a patient's date of birth — might appear in the header, the footer, or a field labelled "DOB", "Date of Birth", "Patient DOB", or simply listed after the patient's name.

Template-based extraction systems require a separate template for each source. When a referral network includes 40 clinics, that is 40 templates to build, maintain, and update every time a clinic changes their letterhead.

DocPeel has no templates by default. The model reads the document contextually, identifies fields from their meaning rather than their position, and extracts them consistently regardless of layout.

Security, compliance, and data handling

Healthcare documents contain sensitive personal and medical information protected under HIPAA, GDPR, and equivalent regional regulations. DocPeel processes documents in isolated per-job sandboxes — no cross-tenant data access, no shared processing infrastructure.

Source documents are discarded immediately after extraction unless you explicitly enable storage. Extracted data is never used for model training. Field-level masking allows you to receive only the fields your downstream system needs, implementing data minimisation at the extraction layer.

For teams operating under HIPAA, DocPeel's architecture supports the implementation of a Business Associate Agreement (BAA). Contact us to discuss your compliance requirements before processing protected health information.

Who uses this

  • Hospitals and clinics digitising paper intake and referral forms
  • Medical billing companies extracting codes from clinical documents
  • Insurance companies processing claims and pre-authorisation documents
  • Telehealth platforms structuring patient-submitted documents
  • Healthcare IT teams building EHR integration workflows

Export formats

JSONCSVExcelGoogle SheetsWebhook

Native integrations

Google SheetsGoogle DriveWebhooksSlackDropbox

Frequently asked questions

Can DocPeel extract ICD-10 and CPT codes from clinical documents?

Yes. Diagnosis codes (ICD-10) and procedure codes (CPT) are extracted and returned as structured arrays alongside their descriptions. The model identifies codes whether they appear in a dedicated field or embedded in free-text clinical notes.

Does DocPeel work with handwritten prescriptions and notes?

DocPeel can extract printed and machine-generated text at high accuracy. Handwritten content varies significantly in legibility; clearly handwritten prescriptions are extracted with good accuracy, but highly stylised or illegible handwriting may require manual review.

Is DocPeel HIPAA compliant?

DocPeel's architecture is designed with data isolation and minimisation in mind. For teams processing protected health information (PHI) under HIPAA, please contact us to discuss a Business Associate Agreement (BAA) before processing patient data.

Can extracted data be sent directly to an EHR system?

DocPeel delivers results as JSON via REST API or webhook. You can connect this to any EHR system that accepts API input. For HL7 FHIR-compatible systems, the structured JSON output maps cleanly to FHIR resource fields.

Ready to automate your healthcare & clinical workflow?

Start free and extract your first document in minutes. No credit card, no template configuration, no per-document fees to start.