MedXtractSay goodbye to manual data entry.
Spend time on patients, not data entry. MedXtract converts intake forms, referrals, and records into EHR-ready data with a built-in review step for accuracy.
- HIPAA Compliant
- End-to-End Encryption
- BAA Available
60% reduction in paperwork time on average
Healthcare is drowning in paperwork
- Manual data entry from faxes, scans, and mixed PDFs eats time and introduces errors.
- Clinicians spend large parts of the workday on clerical tasks and inbox triage.
- Manual data abstraction averages ~6.6% errors in published reviews.
- The result: higher costs, slower intake, uneven data quality.
Traditional Data Entry
Fax → manual typing
Errors → delays
MedXtract way
Fax → MedXtract
Structured data → instant EHR entry
Why clinics choose MedXtract
Built to reduce re-typing and improve data quality the first time.
98%+ verified accuracy
Field-level, patient demographics/IDs
98%+ field-level accuracy on patient demographics and identifiers. Fewer downstream corrections.
Plug into your EHR
HL7 | FHIR | REST
HL7 and FHIR/REST APIs for direct EHR integration. Full audit logs on every field.
HIPAA-ready. Enterprise-grade.
PHI in AWS | Audit trail
HIPAA-ready architecture. PHI stays in AWS. Secure, auditable, enterprise-grade.
How MedXtract fits your workflow
From upload to EHR in four steps—no process change required.
- 1
Upload any source
Intake faxes, scans, PDFs, and mixed packets. HIPAA-ready pipeline from day one.
- 2
AI-powered extraction
OCR + clinical reasoning captures structured fields: demographics, insurance, ICD-10, meds, allergies.
- 3
Review only what matters
Optional human check for flagged low-confidence fields. Everything else bypasses manual re-typing.
- 4
Export and integrate
Push clean data to Epic, Cerner, Athena, and more via HL7 or REST APIs with full traceability.
The scale of the problem is striking
Research shows the true cost of manual data entry in healthcare
Clerical work per 1 hour of patient care
Time-motion and EHR log studies show physicians spend more time documenting than face-to-face.
Manual data abstraction error rate
Single-entry manual abstraction shows preventable errors that impact quality and billing.
Manually transcribed lab results with discrepancies
Outpatient POC testing showed frequent discrepancies in manual transcription.
Case Study: Upward Health
Streamlining Medical Document Data Extraction with AI
The Challenge
Upward Health was struggling with manual data entry from medical documents, leading to significant time costs and error rates. Their team was spending hours each day processing faxes, scans, and mixed PDFs, with manual data abstraction averaging unacceptable error rates on first pass.
Our Solution
MedXtract integrated with Upward Health's existing workflow, providing HIPAA-ready AI extraction for their scanned PDFs, typed and handwritten forms.
Results
The implementation delivered immediate and measurable improvements across all document processing workflows. Scanned documents saw dramatic accuracy improvements. Particularly impressive was the ability to not miss detailed buried pages deep.
Impact
Upward Health's clinical staff can now focus entirely on edge case documents. The reduction in manual data entry has reduced transcription errors and improved operational efficiency.
Key Outcomes
“MedXtract has transformed our operations. Data entry is always a serious headache in the industry, for the first time, it is not.”
Built for security & compliance
Enterprise-grade controls from day one
- HIPAA-aligned architecture; BAA available
- Encryption in transit & at rest (TLS 1.2+, AWS KMS)
- Private networking (VPC, security groups), RBAC & MFA
- Audit logging & retention (CloudTrail, S3 Object Lock)
- AWS WAF protection
- Isolated environments; least-privilege IAM
See MedXtract in action
Patient Intake Form
Demo uses sample data only. No real patient information displayed.
Frequently asked questions
Ready to eliminate manual data entry?
We will process a handful of your documents and show exact savings.