The problem
Administrative burnout from manual data entry, transcription errors on external records, and legacy systems that cannot ingest image-based or unstructured documentation.
Turn faxed records, scanned PDFs, and phone snapshots of lab reports into structured, EHR-ready data, without manual transcription.
30-minute call. No system replacement.
For a multi-specialty outpatient network, the team deployed an OCR and computer-vision pipeline that ingested non-standard PDF lab sheets and phone snapshots. The system classified lab panels, extracted numeric and text results, checked them against reference ranges, and mapped them into structured clinical fields so staff did not re-key the transcription backlog.
Capabilities usedLaboratory results, PDF and snapshot parsing engines.
The same parsing layer classified diagnostic documents, pathology reports and discharge summaries among them, by matching page layout to known document templates. Text blocks were extracted, the document type was assigned, and the structured result waited for a person before it reached the chart.
Capabilities usedDiagnostic reports, document templates.
Faxed records, scanned PDFs, and phone snapshots of lab reports arrive as images. This pipeline reads those pages with optical character recognition and natural language processing, then writes structured fields the EHR can store.
Staff and patients submit PDFs, TIFFs, and camera snapshots through a secure portal or a mobile upload. The pipeline finds the page boundary, corrects skew, and classifies the document: a lipid panel, a pathology report, a discharge summary, or another known type. It then extracts the text blocks and the results.
Lab values map to LOINC. Conditions map to SNOMED or ICD-10. A result outside the reference range, or one that does not match a code, is held for a person. Confirmed fields move into the EHR through FHIR or HL7, including platforms such as athenahealth and eClinicalWorks, in the places staff used to type by hand.
Administrative burnout from manual data entry, transcription errors on external records, and legacy systems that cannot ingest image-based or unstructured documentation.
Chief information officers, practice managers, and lead physicians at mid-size clinics and multi-specialty outpatient networks.
Multi-channel gateways for PDFs, TIFFs, and camera snapshots through a secure web portal or mobile app extension.
Computer-vision and NLP pipelines that detect page boundaries, correct skew, extract text, and classify document types such as lipid panels, pathology reports, and discharge summaries.
Extracted values are mapped to LOINC for labs and SNOMED or ICD-10 for conditions. Out-of-range or unmatched values are flagged for human review.
FHIR and HL7 connectors deposit structured fields into the target EHR, including platforms such as athenahealth or eClinicalWorks, without re-keying.
Faxed records, scanned PDFs, TIFFs, and phone snapshots of lab reports come in through one secure portal or mobile upload. The pipeline classifies the page before anything is extracted.
Numeric and text results map to LOINC. Conditions map to SNOMED or ICD-10. A value that does not match a code is held back instead of being guessed.
Out-of-range and unmatched values are flagged for a person. Mapped results can write into the EHR only after that check.
The integration writes through FHIR or HL7 into the EHR you already run, including platforms such as athenahealth or eClinicalWorks. It does not replace that system.
One document flow (faxed records, scanned PDFs, or phone snapshots of lab reports) and one EHR connection.
We start with one workflow, measure it, then expand. Book a 30-minute discovery call.
30-minute call. No system replacement.