Mixpeek for MDS Coordinators
Auto-populate MDS assessments from clinical documentation in minutes, not hours
MDS coordinators spend 3-4 hours per assessment manually abstracting charts — pulling data from EHR notes, scanned forms, wound photos, and therapy logs to populate 20+ MDS 3.0 sections. Mixpeek's multimodal pipeline ingests all clinical content, maps it to MDS section codes, and surfaces relevant documentation on demand — so coordinators review and finalize instead of hunting and transcribing.
What's Broken Today
1Manual chart abstraction
Each MDS assessment requires 3-4 hours of pulling data from EHR entries, scanned charts, photographs, and therapy notes to populate section codes — a repetitive, error-prone process.
2PDPM revenue loss from under-documentation
Clinical severity scattered across unstructured documents goes uncaptured in MDS coding, leaving an average of $2,840/day per patient in PDPM reimbursement on the table.
3CMS survey anxiety
Preparing evidence packages for CMS surveys means weeks of manual chart review across hundreds of residents, with F-tag citations on the line for documentation gaps.
4Cross-system data silos
Clinical data lives in EHR structured fields, scanned PDFs, wound photographs, therapy logs, and handwritten notes — no single system provides a unified view for MDS coding.
How Mixpeek Helps
Automated MDS section mapping
A taxonomy classifier maps extracted clinical data to specific MDS 3.0 sections (G, J, K, M, N, O, Q) and item codes, auto-populating assessments for coordinator review.
Multimodal clinical extraction
OCR for scanned charts, image analysis for wound photographs, text extraction for therapy notes, and FHIR integration for EHR data — all processed through a single pipeline.
On-demand audit evidence packages
Retrieve all supporting documentation for any MDS section, resident, or date range in seconds — generating audit-ready evidence packages for CMS surveys.
FHIR-native EHR integration
The FHIR R4 connector pulls clinical resources directly from Epic, Cerner, PointClickCare, and other FHIR-compliant EHRs into the extraction pipeline.
How It Works for MDS Coordinators
Ingest clinical content
Connect your EHR via FHIR or upload scanned charts, photographs, and therapy notes to a Mixpeek bucket. The pipeline accepts PDFs, images, and structured FHIR resources.
Extract and structure
Feature extractors perform OCR on scanned documents, analyze wound photographs, parse clinical terminology, and generate semantic embeddings for each piece of content.
Map to MDS sections
A taxonomy classifier maps each extracted data element to the appropriate MDS 3.0 section and item code, building a structured assessment draft for each resident.
Review and finalize
MDS coordinators review auto-populated sections, verify clinical accuracy, and sign off. Supporting documentation is linked for audit traceability.
Relevant Features
- Feature Extractors (OCR, NER, image captioning)
- Taxonomies (MDS 3.0 section mapping)
- Retrievers (hybrid search with attribute filtering)
- Collections (batch clinical document processing)
- FHIR R4 Connector
Integrations
- FHIR R4 (Epic, Cerner, PointClickCare)
- S3-compatible storage for document ingestion
- MDS software (import via structured output)
"I went from spending my entire day in charts to reviewing pre-populated assessments. I can actually focus on clinical accuracy instead of data entry."
Sarah Chen
Lead MDS Coordinator, MeadowCare
Frequently Asked Questions
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