This workflow corresponds to n8n.io template #5083 — we link there as the canonical source.
This workflow follows the Form Trigger → Google Sheets recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "rLpjED4GqjXQcQvP",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Medical Records OCR Automation V1",
"tags": [],
"nodes": [
{
"id": "b3717627-b305-46f3-9a5a-e818738743da",
"name": "On form submission",
"type": "n8n-nodes-base.formTrigger",
"position": [
-740,
140
],
"parameters": {
"options": {},
"formTitle": "Document OCR",
"formFields": {
"values": [
{
"fieldType": "file",
"fieldLabel": "Document",
"multipleFiles": false,
"requiredField": true
}
]
},
"formDescription": "Please upload your document for processing."
},
"typeVersion": 2.2
},
{
"id": "b3605b38-3157-4ffe-9064-72b29dcb6df8",
"name": "Upload to Mistral",
"type": "n8n-nodes-base.httpRequest",
"position": [
-500,
140
],
"parameters": {
"url": "https://api.mistral.ai/v1/files",
"method": "POST",
"options": {},
"sendBody": true,
"contentType": "multipart-form-data",
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "purpose",
"value": "ocr"
},
{
"name": "file",
"parameterType": "formBinaryData",
"inputDataFieldName": "Document"
}
]
},
"genericAuthType": "httpHeaderAuth"
},
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "ff551a26-b470-45e7-87e4-7165994783aa",
"name": "Get Signed URL",
"type": "n8n-nodes-base.httpRequest",
"position": [
-340,
140
],
"parameters": {
"url": "=https://api.mistral.ai/v1/files/{{ $json.id }}/url",
"options": {},
"sendQuery": true,
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"queryParameters": {
"parameters": [
{
"name": "expiry",
"value": "24"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "95ca0fc3-1430-4196-809a-a1de7fa28b86",
"name": "Get OCR Results",
"type": "n8n-nodes-base.httpRequest",
"position": [
-180,
140
],
"parameters": {
"url": "https://api.mistral.ai/v1/ocr",
"method": "POST",
"options": {},
"jsonBody": "={\n \"model\": \"mistral-ocr-latest\",\n \"document\": {\n \"type\": \"document_url\",\n \"document_url\": \"{{ $json.url }}\"\n },\n \"include_image_base64\": true\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "99f6bf3f-365f-4119-a71a-0b46a8b1fa90",
"name": "Google Sheets",
"type": "n8n-nodes-base.googleSheets",
"position": [
180,
140
],
"parameters": {
"columns": {
"value": {
"Name": "={{ $('Data cleaning').item.json.Name }}",
"Notes": "={{ $('Data cleaning').item.json.Notes }}"
},
"schema": [
{
"id": "Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Date of Birth",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Date of Birth",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Patient ID",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Patient ID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Date of Visit",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Date of Visit",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Referring Physician",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Referring Physician",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Department",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Department",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Symptoms",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Symptoms",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Blood Pressure",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Blood Pressure",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Heart Rate",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Heart Rate",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Temperature",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Temperature",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Lab Results",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Lab Results",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Diagnosis",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Diagnosis",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Medications",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Medications",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Next Appointment",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Next Appointment",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Notes",
"type": "string",
"display": true,
"required": false,
"displayName": "Notes",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "pages",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "pages",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "model",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "model",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "usage_info",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "usage_info",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "myNewField",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "myNewField",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "markdown",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "markdown",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "autoMapInputData",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1417843853,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1jRNGNrHAFnvNAAnCHW0vM2784GxIPolzT4x_rFWZRvU/edit#gid=1417843853",
"cachedResultName": "Patients"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1jRNGNrHAFnvNAAnCHW0vM2784GxIPolzT4x_rFWZRvU",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1jRNGNrHAFnvNAAnCHW0vM2784GxIPolzT4x_rFWZRvU/edit?usp=drivesdk",
"cachedResultName": "Medical Records - Extracted"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.5
},
{
"id": "1e38c3a0-d0d8-457c-93e9-f038df571790",
"name": "Data cleaning",
"type": "n8n-nodes-base.code",
"position": [
-20,
140
],
"parameters": {
"jsCode": "// Get OCR results from the input\nconst ocrResults = $input.all().map((item) => item.json);\n\n// Define fields to extract\nconst fields = [\n \"Name\",\n \"Date of Birth\",\n \"Patient ID\",\n \"Date of Visit\",\n \"Referring Physician\",\n \"Department\",\n \"Symptoms\",\n \"Blood Pressure\",\n \"Heart Rate\",\n \"Temperature\",\n \"Lab Results\",\n \"Diagnosis\",\n \"Medications\",\n \"Next Appointment\",\n \"Notes\",\n];\n\nconst allPatientRecords = [];\n\n// Process each OCR result\nocrResults.forEach((result) => {\n // Combine all pages into a single text for processing\n let allText = \"\";\n if (result.pages && Array.isArray(result.pages)) {\n result.pages.forEach((page) => {\n if (page.markdown) {\n allText += page.markdown + \"\\n\";\n }\n });\n }\n \n // Split the text into patient record sections\n // Look for patterns like \"Patient Record 1\", \"\ud83e\uddfe Patient Record 2\", etc.\n const recordSections = allText.split(/(?:\ud83e\uddfe\\s*)?Patient Record\\s*\\d+/g).filter(section => section.trim().length > 0);\n console.log(`Found ${recordSections.length} potential patient record sections`);\n \n // Process each patient record section\n recordSections.forEach((section, index) => {\n // Create a new patient record object\n const patientRecord = {};\n \n // Add Patient Name which has a different pattern than other fields\n const nameMatch = section.match(/Patient Name:\\s*([^\\n]+)/);\n if (nameMatch) {\n patientRecord[\"Name\"] = nameMatch[1].trim();\n }\n \n // Extract all other fields\n fields.forEach((field) => {\n if (field === \"Name\") return; // Already handled above\n \n // Create a regex pattern for the field\n const pattern = new RegExp(`${field}:\\\\s*([^\\\\n]+)`, 'i');\n const match = section.match(pattern);\n \n if (match) {\n patientRecord[field] = match[1].trim();\n }\n \n // Special handling for Lab Results which might span multiple lines\n if (field === \"Lab Results\" && !patientRecord[field]) {\n const labStartIndex = section.indexOf(\"Lab Results:\");\n if (labStartIndex !== -1) {\n let labEndIndex = -1;\n \n // Find where lab results end (before Diagnosis or next field)\n for (const nextField of [\"Diagnosis\", \"Medications\", \"Next Appointment\"]) {\n const nextFieldIndex = section.indexOf(`${nextField}:`, labStartIndex);\n if (nextFieldIndex !== -1 && (labEndIndex === -1 || nextFieldIndex < labEndIndex)) {\n labEndIndex = nextFieldIndex;\n }\n }\n \n if (labEndIndex !== -1) {\n let labResults = section.substring(labStartIndex + \"Lab Results:\".length, labEndIndex).trim();\n // Clean up lab results\n labResults = labResults.replace(/\u25cf/g, '').replace(/\\n\\s*/g, ', ').trim();\n patientRecord[field] = labResults;\n }\n }\n }\n });\n \n // Only add records that have at least a name or patient ID\n if (patientRecord[\"Name\"] || patientRecord[\"Patient ID\"]) {\n console.log(`Extracted data for patient ${index + 1}: ${patientRecord[\"Name\"] || patientRecord[\"Patient ID\"]}`);\n allPatientRecords.push(patientRecord);\n }\n });\n});\n\nconsole.log(`Total patient records extracted: ${allPatientRecords.length}`);\n\n// Return all extracted patient records\nreturn allPatientRecords;"
},
"typeVersion": 2
},
{
"id": "c02eba73-56cc-4757-b010-cba7d7f34e04",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1320,
-360
],
"parameters": {
"width": 1820,
"height": 1060,
"content": "## \ud83c\udfe5 Medical Records OCR Automation (n8n)\n**\ud83e\udde0 Sticky Node Setup Guide**\n\n## Author : [David Olusola](https://www.daexai.com)\n\n\n1. \ud83d\udce5 On form submission\nType: Form Trigger\nPurpose: Captures uploaded documents from users.\nLabel: \u201cDocument OCR\u201d\nWhat to Stick:\n\n\u201cReceives uploaded document from user to begin OCR processing.\u201d\n2. \u2b06\ufe0f Upload to Mistral\nType: HTTP Request\nMethod: POST to https://api.mistral.ai/v1/files\nAuth: HTTP Header Auth\nWhat to Stick:\n\n\u201cSends uploaded document to Mistral for OCR file hosting.\u201d\n3. \ud83d\udd17 Get Signed URL\nType: HTTP Request\nPurpose: Retrieves a temporary signed URL from Mistral to access the uploaded file.\nWhat to Stick:\n\n\u201cGets secure download URL from Mistral for the uploaded document.\u201d\n4. \ud83e\udde0 Get OCR Results\nType: HTTP Request\nPurpose: Sends signed URL to Mistral OCR API to extract text content.\nWhat to Stick:\n\n\u201cCalls Mistral OCR with signed document URL to extract data.\u201d\n5. \ud83e\uddf9 Data cleaning\nType: Code Node (JavaScript)\nPurpose:\n\nParses OCR text\nExtracts structured fields like Patient Name, Diagnosis, Medications, etc.\nHandles multi-record documents.\nWhat to Stick:\n\u201cProcesses raw OCR text into structured patient records for sheet entry.\u201d\n6. \ud83d\udcc4 Google Sheets\nType: Google Sheets Append\nTarget: Medical Records \u2192 \u201cPatients\u201d sheet\nPurpose: Writes cleaned data into the spreadsheet.\nWhat to Stick:\nMake a copy [Google sheet](https://docs.google.com/spreadsheets/d/1jRNGNrHAFnvNAAnCHW0vM2784GxIPolzT4x_rFWZRvU/edit?usp=sharing)\n\n\u201cAppends cleaned patient data to the Google Sheet.\u201d\n\u2705 General Notes:\n\nWebhook ID: f9d60b5f-0a09-4654-a840-84a0f745321e (for testing or routing webhooks)\nFile Field: Named Document in form\nImportant Fields Extracted:\nName, DOB, Patient ID, Diagnosis, Medications, Lab Results, Notes, etc."
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "63643d00-01e0-4533-8ddc-0537590f8408",
"connections": {
"Data cleaning": {
"main": [
[
{
"node": "Google Sheets",
"type": "main",
"index": 0
}
]
]
},
"Get Signed URL": {
"main": [
[
{
"node": "Get OCR Results",
"type": "main",
"index": 0
}
]
]
},
"Get OCR Results": {
"main": [
[
{
"node": "Data cleaning",
"type": "main",
"index": 0
}
]
]
},
"Upload to Mistral": {
"main": [
[
{
"node": "Get Signed URL",
"type": "main",
"index": 0
}
]
]
},
"On form submission": {
"main": [
[
{
"node": "Upload to Mistral",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googleSheetsOAuth2ApihttpHeaderAuth
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
This plug-and-play n8n workflow automates medical record digitization using Mistral’s OCR API and stores clean, structured data in Google Sheets. Whether you run a clinic or healthtech product, this no-code solution simplifies data entry from scanned or uploaded medical…
Source: https://n8n.io/workflows/5083/ — original creator credit. Request a take-down →
Related workflows
Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
Generate realistic, high-quality images from text prompts using the Flux AI Text-to-Image Generator API via RapidAPI, and seamlessly store the results in Google Drive and log them in Google Sheets — a
Note: Now includes an Apify alternative for Rapid API (Some users can't create new accounts on Rapid API, so I have added an alternative for you. But immediately you are able to get access to Rapid AP
This system automates LinkedIn lead generation and enrichment in six clear stages: Lead Collection (via Apollo.io) Automatically pulls leads based on keywords, roles, or industries using Apollo’s API.
Understand your customers before you build for them. This workflow, Market Segmentation: Buyer Persona Pain Point Report, automates the grueling process of primary market research. By scraping real-wo
The competitive edge, delivered. This Customer Intelligence Engine simultaneously analyzes the web, Reddit, and X/Twitter to generate a professional, actionable executive briefing.