Lab / Clinic Admin: Extract Referral Forms into Google Sheets for Faster Processing

Referral forms are the “front door” to a lot of lab and clinic workflows—new patients, tests requested, provider details, insurance info, priority flags, notes… and then the busy part: copying everything into a spreadsheet (or multiple systems) so the team can triage, schedule, and follow up.

If you’re still doing manual data entry from scanned referrals or photos, you already know the problems:

  • Slow intake when volume spikes
  • Typos in patient or provider details
  • Inconsistent formatting across clinics and doctors
  • “Where is that referral?” chaos when emails and uploads pile up

Here’s a faster way: use AI extraction (not just OCR) to turn each referral form into a clean row in Google Sheets, using your exact column structure.

Why AI extraction beats “OCR-only” for referral forms

Traditional OCR mostly gives you raw text. Referral forms need more than that:

  • Find the right fields (e.g., referring physician vs. attending physician)
  • Understand context (e.g., “urgent” checkbox, test panels, diagnosis notes)
  • Handle variations (different form layouts, stamps, handwriting, partial scans)

With AI extraction, you define what you need once, and the system fills it consistently—even if the layout changes.

The workflow: Define your structure → Upload → Get structured rows in Sheets

With img2sheet, the process is intentionally simple:

1) Create your referral “structure” (your column blueprint)

You define columns with:

  • Label (what you want in the sheet)
  • Type (text or number)
  • Prompt (what data to extract exactly, in plain language)

Think of it as telling the AI: “For every referral, extract these specific fields and put them into these columns.”

2) Upload a referral image (scan/photo/PDF-as-image)

The user uploads the referral for that structure.

3) The extracted data is inserted into Google Sheets in the same manner as your structure

Every upload becomes a new row, aligned perfectly with your predefined columns—so your team can filter, assign, and process immediately.

Example: A practical referral structure for labs/clinics

Here’s a strong starter structure you can copy into your setup (adapt as needed):

  1. Patient Full Name (text)

    Prompt: “Extract patient full name.”

  2. Date of Birth (text)

    Prompt: “Extract patient date of birth (DOB). Return in YYYY-MM-DD if possible.”

  3. Phone Number (text)

    Prompt: “Extract patient phone number.”

  4. Email (text)

    Prompt: “Extract patient email address if present.”

  5. Referring Provider Name (text)

    Prompt: “Extract referring physician/provider full name.”

  6. Clinic / Practice Name (text)

    Prompt: “Extract clinic/practice name.”

  7. Provider Phone (text)

    Prompt: “Extract provider contact phone number.”

  8. Requested Tests (text)

    Prompt: “Extract requested tests or panels. If multiple, list separated by commas.”

  9. Priority (text)

    Prompt: “Determine priority: urgent/stat/routine based on checkboxes or keywords.”

  10. Diagnosis / Notes (text)

    Prompt: “Extract clinical notes or diagnosis/reason for referral.”

  11. Insurance Provider (text)

    Prompt: “Extract insurance provider name if present.”

  12. Policy Number (text)

    Prompt: “Extract policy/member ID if present.”

  13. Referral Date (text)

    Prompt: “Extract referral date.”

  14. Internal Status (text)

    Prompt: “Return blank (for internal workflow use).”

This gives you a clean intake table that your team can sort by priority, filter by test type, track missing fields, and assign follow-ups.

What you gain immediately (even with the first 50 referrals)

Faster processing

  • Upload → row in Sheets in seconds
  • Intake doesn’t stall when staff are busy

Fewer mistakes

  • No manual typing of names, phone numbers, IDs
  • Less risk of copy/paste errors

Standardized data

  • Same columns every time, regardless of which clinic sent the form
  • Makes downstream automation possible (status columns, notifications, dashboards)

A “single source of truth”

  • One spreadsheet view for triage, scheduling, lab processing, and follow-up

Privacy note: no file links, no storage

To keep the workflow clean and reduce risk:

  • We don’t generate file links
  • All files are removed immediately after extraction

So your Google Sheet stores the structured values you need—without keeping the original uploads around.

(As always, confirm your internal policies and compliance requirements for handling PHI/PII. This isn’t legal advice.)

Best practices to make it even smoother

  • Add a “Missing Fields” column (text)

Prompt: “List any of these fields that are missing: DOB, phone, requested tests, provider name.”

  • Normalize phone numbers and dates via prompts

Ask for consistent formatting so Sheets stays clean.

  • Use a “Status” column for your team

Examples: New, Needs Info, Scheduled, Sent to Lab, Completed

  • Create a second structure for specific referrals

Example: “Genetics referral” vs “Routine bloodwork referral” so your prompts stay laser-focused.

Wrap-up

If referral intake is eating hours every week, you don’t need another generic OCR tool that dumps unstructured text. You need a system that extracts exactly what your team cares about—and inserts it into Google Sheets in a consistent format, every time.