Extract patient demographics, diagnosis codes, procedure details, and billing data from medical records, EOBs, and patient forms—without templates or manual data entry.
Upload any document — PDF, scan, or photo — and get structured data back immediately. No setup, no templates, no waiting.
“We process over 4,000 EOBs per month from dozens of insurance carriers. Automating extraction eliminated two full-time data entry positions and reduced our denial rate from miskeyed codes by 60 percent.”
“Patient intake forms were our biggest bottleneck. Now patients fill out paper forms and the data flows into our EHR within minutes instead of being keyed in by front desk staff.”
“The HIPAA compliance was the deciding factor. We evaluated three vendors and this was the only one with SOC 2 Type 2 and a clear BAA process.”
Audited controls over a sustained period, not a point-in-time check.
Bank-grade encryption at rest and TLS 1.2+ in transit.
Documents deleted within 24 hours. No copies retained.
Drag and drop files, connect a cloud drive, or set up email auto-forwarding. Any file format works—PDF, JPEG, PNG, TIFF, or digital documents.
The AI identifies fields by context and meaning, not fixed coordinates. Names, dates, amounts, and custom fields are extracted automatically.
Get structured output in Excel, Google Sheets, CSV, or JSON. Use the REST API for direct integration into your systems.
Healthcare generates more paper than almost any other industry. Between patient intake forms, explanation of benefits statements, medical records, lab reports, and insurance correspondence, a typical hospital or clinic processes thousands of documents per week. Healthcare OCR converts these paper-based and scanned documents into structured digital data that can flow directly into EHR systems, billing platforms, and analytics tools.
The challenge specific to healthcare OCR is the diversity of document formats combined with strict accuracy requirements. A misread patient ID or diagnosis code can trigger claim denials, compliance violations, or clinical errors. Traditional OCR tools that produce raw text leave the burden of field identification and validation on human operators, which defeats the purpose of automation. AI-powered healthcare OCR identifies fields by their clinical and administrative context, mapping patient names, dates of service, CPT codes, and ICD-10 codes to structured columns automatically.
Regulatory compliance adds another layer of complexity. Any system that processes protected health information must meet HIPAA requirements for data handling, encryption, and access controls. Lido provides SOC 2 Type 2 compliance and HIPAA eligibility, with AES-256 encryption at rest and automatic document deletion within 24 hours of processing. This means healthcare organizations can automate document processing without creating new compliance risks.
Organizations evaluating healthcare OCR solutions should assess accuracy on real-world document quality, support for the full range of healthcare document types, integration with existing EHR and billing systems, and compliance certifications. Lido handles medical records, EOBs, patient forms, lab reports, and insurance correspondence from any source without per-document configuration.
Healthcare OCR handles a wide range of document types including medical records, explanation of benefits (EOB) statements, patient intake forms, lab reports, insurance correspondence, referral letters, discharge summaries, and clinical notes. The AI identifies document type automatically and extracts the relevant fields for each.
Lido provides SOC 2 Type 2 compliance and is HIPAA-eligible, meaning it meets the security and privacy requirements for processing protected health information. Data is encrypted with AES-256 at rest and TLS 1.2+ in transit, and documents are automatically deleted within 24 hours of processing.
AI-powered healthcare OCR typically achieves 95 to 99 percent accuracy on printed documents and 90 to 95 percent on legible handwritten entries. Field-level confidence scoring flags uncertain extractions for human review, which is essential for clinical data where accuracy is non-negotiable.
Yes. The AI engine recognizes standard medical coding formats including ICD-10 diagnosis codes and CPT procedure codes, extracting them as structured data fields. This is particularly useful for automating claims processing and medical billing workflows.
Extracted healthcare data can be exported to Excel, Google Sheets, CSV, or JSON. The REST API enables direct integration with EHR systems, practice management software, and billing platforms.
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Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine
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