Use Case Healthcare
Clinical Data
Extraction
Structured data automatically extracted from unstructured clinical documents: discharge letters, lab results, pathology reports. Integration into HIS, tumour boards, registries and research databases.
Why Clinical Data Extraction Is a Lever
80% of clinical data is trapped in free text, and therefore usable by nobody
Hospitals generate enormous volumes of data: discharge letters, surgical reports, lab results, pathology reports, radiology findings, nursing documentation.
But 80% of this data exists as unstructured free text, in PDFs, dictations and scanned documents. For the HIS, for clinical registries, for research databases, for quality assurance, it is not usable.
In practice, a research nurse reads through 200 discharge letters to extract TNM staging, lines of therapy and survival times for a cancer registry. A quality manager searches surgical reports for complication rates. A researcher needs lab value trends for 500 patients. Per patient: 30-90 minutes of manual data extraction. For clinical studies with 500+ patients, that means months.
The result: clinical registries are incomplete. Quality indicators are estimated rather than measured. Research projects fail at the data preparation stage. And the national quality assurance body increasingly requires structured quality data, data that until now could only be obtained through manual extraction.
How the Process Changes
Before / After
Data extraction for 500 patients (clinical registry / study)
The Solution in Detail
How We Automate Clinical Data Extraction
01
Clinical NLP: Free Text to Structured Data
AI reads unstructured clinical documents and extracts defined variables: ICD-10 diagnoses, TNM staging, therapies, medication with dosages, lab values, vital signs, procedures. Medical terminology understood, including abbreviations, synonyms and negations (“no evidence of…”).
Specialised medical NLP models. Recognition of negation, temporality, uncertainty. SNOMED CT, LOINC, ATC classification. Configurable extraction variables per use case. Multi-stage validation.
02
Confidence-Based Validation
Every extraction receives a confidence score. High-confidence extractions are accepted automatically. Uncertain cases are presented to an expert for review, with the source text highlighted. Only 10-15% require manual review.
03
Integration: Registries, HIS, Research
Extracted data exported to the target system: clinical cancer registry, quality assurance database, FHIR server, research database, HIS fields. Automatic patient matching. Data-protection compliant: pseudonymised for research, identified for care.
FHIR R4 export. HL7 v2 integration. CSV/Excel for registries. Pseudonymisation to recognised standards. Integration with cancer registries, national quality assurance bodies and research databases. GDPR-compliant processing.
04
Extraction Dashboard & Data Quality
Dashboard: documents processed, extraction rate, confidence distribution, open reviews. Data quality KPIs: completeness per variable, consistency checks. Basis for continuous improvement of extraction models.
Power BI dashboard. KPIs: extraction rate per variable, average confidence, review effort, document processing time. Data quality trends. Model performance monitoring.
Results
What Clinical Data Extraction Typically Delivers
−90%
Manual data
extraction
1–2 Days
Instead of 3-6 months
(500 patients)
95%
accuracy
100%
& audit-proof
The greatest lever is scalability. Manual extraction scales linearly: 10 times as many patients requires 10 times the effort. AI extraction scales logarithmically: configuration is a one-off, processing is then near-constant.
You May Also Be Interested In
Related Use Cases
Clinical Documentation
Better documentation = better coding. The foundation for complete codes
Patient Admission
Admission data as the basis for coding. Diagnoses correctly captured from day one.
Clinical Data Extraction
Structured data from unstructured clinical documents is extracted automatically.
Ready?
How many hours does your team spend on manual data extraction?
Let us look in 30 minutes at which clinical data can be extracted automatically, and how your registries, studies and quality reports can be completed in days rather than months.
No sales pitch. Just an honest assessment.
120+ Clients. 100% Satisfaction. 7 months to Profitability.
WHAT YOU GET IN THE DISCOVERY CALL
Identify your best use cases
Based on your industry and process landscape
Calculate concrete ROI
In Euros, FTE equivalents and time savings
Show examples from your industry
Real results of comparable companies
Define timeline and next steps
Concrete roadmap, no vague promises