Go Beyond Clinical Notes
Convert text to structured data and codes
Recorded visits become text. Quippe reads that text and returns coded data points — conditions, symptoms, meds, orders and more — ready for your downstream systems.
The Problem
The note is written. The data never arrives.
Most clinical text is locked
Unsearchable. Uncodable. Unusable downstream.
Fluent, but unstructured
LLM-generated notes read beautifully and still carry no clinical structure a system can act on.
Costs land downstream
Billing errors, interoperability failures, and clinicians re-entering what they already said.
Text to Structured Data
Same note. Now it’s queryable.
SOAP note is codified into structured data with the diagnosis highlighted. Hover a highlight to see extracted codes
How It Works
Any source of text or data in. All domains of medicine.
01 / Ingest
Accept text from any source:
- Ambient dictation - recorded visit
- Typed notes - written in your EHR
- PDF / Scan - uploaded documents
- Free Text - narrative from system
- FHIR, CDA, USCDI - frameworks
02 / Match to MEDCIN
Extract → Normalize → Code
- Synonymy & code-pattern mapping
- Entity recognition & extraction
- 20+ clinical data standards
- Most granular clinical specificity
- Coded clinical source of truth
03 / Output to any standard
Traversing the coding rosetta stone
- Billing & RCM - Coded, claim-ready
- EHR chart - discrete fields, no blobs
- Diagnosis - clinically specific
- Orders - meds, labs, procedures
- FHIR, CDA, USCDI - frameworks
Who It Is For
Extract medical codes from clinical text
EHRs
Deliver reliable data to your providers
- Offer reliable, specific billable ICD-10 and CPT coding for RCM
- Extract structured data in every domain: symptoms, history, tests, diagnoses, treatments, genomics
- Validate against logical inconsistency from LLMs
- Output to all standards for quality reporting, analytics, interoperability, care coordination
Accuracy Comparison
Diagnostic coding accuracy ranked
Selected general-purpose models on the vals.ai MedCode benchmark, with Quippe/Alchemy for comparison. Benchmark snapshot: August 1, 2026.
Quippe / Alchemy
Explore our ICD-10-CM diagnostic coding accuracy
Best general-purpose LLM
GEMINI 3.1 Pro Preview – top scorer on vals.ai MedCode
For Product and Developers
Call it directly from your stack
Send free-text clinical notes to Quippe, get back structured medical concepts – mapped to ICD-10, CPT, SNOMED CT, and more.
curl -X POST "https://quippe.medicomp.com/api/Quippe
/TextRecognition/Recognize?DataFormat=JSON" \
-H "Content-Type: application/x-www-form-urlencoded" \
-u "<username>:<password>" \
-d "Text=string"
Frequently asked questions
What teams ask before they integrate.
Quippe converts free-text clinical documentation into structured, coded data using MEDCIN clinical terminology, which is purpose-built to match clinical language rather than generic text. Because MEDCIN reflects the way clinicians actually speak and document — with extensive built-in synonymy — Quippe captures clinical nuance that general-purpose LLMs, which aren’t designed for coding, typically miss.
No. Quippe’s mappings and diagnostic links are deterministic, not probabilistic, grounded in the expert-curated Quippe Clinical Knowledge Graph and 45+ years of clinical knowledge engineering. Every mapping traces to validated logic developed by medical experts and informaticists, producing a consistent, reproducible result every time.
General-purpose LLMs aren’t built for medical coding. They lack coding-rule logic and clinical selectivity, and they hallucinate or miss codes because standard code systems and their descriptions are not written the way clinicians think or speak. Most code systems are poor matching targets for raw clinical narrative. Quippe addresses this using MEDCIN as a natural language, clinically specific intermediary between free text and code systems, which drives higher specificity and accuracy than an LLM can achieve working alone.
Quippe supports more than 20 globally-accepted standard terminologies and vocabularies, including ICD-10-CM, ICD-10-PCS, ICD-11-WHO, SNOMED-CT, CPT, CDT, DSM-5, LOINC, RxNorm, HCPCS, and more — all mapped through MEDCIN. Because MEDCIN sits at the hinge point between vocabularies, Quippe can map between any two vocabularies (e.g., SNOMED to ICD-10, CPT to HCPCS) in a single call, not only to and from MEDCIN.
No. It spans any meaningful clinical concept entered into a patient chart, across every domain of medicine, including diagnoses, procedures, medications, symptoms, physical exam findings, history, nursing documentation, labs, and genomics — mapped across 20+ code systems.
Quippe’s text-to-medical-coding capability is built on MEDCIN, a terminology written the way clinicians actually think and speak, with extensive synonymy built in. It’s grounded in the Quippe Clinical Knowledge Graph, which connects millions of diagnostic links and external codes to those granular data points.
A clinical data foundation you can build on
Deterministic, SME-curated, and grounded in a clinical data source of truth. Every domain, every code system you use, zero hallucinations.