Automated Medical Record processing
Medical Records requande extracting diagnosis codes and patient history. Parsit does this automatically — faster, more accurately, and without errors.
Medical Records: before and after Parsit
Medical staff or insurance adjusters manually read through complex, unstructured patient histories to find specific ICD codes, treatments, or pre-existing conditions.
Nusiskundimai: Patient skundžiasi stipriu skausmu dešiniajame kelio sąnaryje, atsandadusiu po traumos sportuojant.
Objektyvi būklė: Kelio sąnarys patinęs, judesiai riboti. Atliktas MRT tyrimas rodo vidinio menisko plyšimą.
Clinical diagnosis: Dešinio kelio vidinio menisko plyšimas (S83.2). Paskandta artroskopinė operacija.
Parsit comprehends medical terminology, accurately extracting diagnoses, dates, and procedures from unstructured text into structured formats.
| A | B | C | D | E | |
|---|---|---|---|---|---|
| 1 | Patient | Gim. data | Diagnosis (Tekstas) | TLK-10 Kodas | Paskandta procedūra |
| 2 | Vardenis Pavardenis | 1980-01-01 | Dešinio kelio vidinio menisko plyšimas | S83.2 | Artroskopinė operacija |
| 3 |
How Parsit processes medical records
Date extraction
Patient details, dates of visit, ICD-10 diagnosis codes, prescribed medications, procedures performed, and physician notes.
Validation and checking
Validates extracted ICD codes against official medical registries and ensures chronological consistency of patient history.
Delivering results
HL7/FHIR compatible JSON or direct API integration with Electronic Health Record (EHR) systems.
Where are they used: medical records
Healthcare
Clinics and hospitals need to digitize legacy records. Parsit automates the structuring of historical patient data.
Insurance
Health and life insurers review medical records for underwriting and claims. Parsit instantly highlights relevant medical history and codes.
Try automating medical records with your own files
Register for an intro call. We will discuss your processes and prepare a custom demo that you can try yourself.
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