Data Characteristics
Medical insurance claims data originates from hospital information systems (HIS) and medical insurance administration systems. This data updates frequently, typically monthly or quarterly in batches. Policy adjustments can trigger unscheduled updates. Documents come in various formats: structured XML or JSON for settlement manifests, semi-structured PDFs for reimbursement vouchers, and unstructured Word or Excel files for policy interpretations. Key fields include patient ID, diagnosis codes (e.g., ICD-10), treatment item codes (e.g., C-DRG/DIP), expense details, drug names, approval status, and settlement amounts. Units typically include RMB yuan, counts, milligrams, or milliliters.
Constraints Imposed by These Characteristics on Document Parsing and Chunking
The high update frequency of medical insurance claims data requires highly automated processing in the document parsing pipeline to handle policy changes and batch data updates. Diverse document formats necessitate multi-modal parsing support, especially for accurate extraction from PDFs and structured data. The standardized nature of diagnosis and treatment item codes demands precise identification and preservation of these codes in parsing results, preventing semantic loss due to chunking. Fields like expense details and drug names require extremely high accuracy; any parsing error can impact subsequent clinical trial pre-screening results. Therefore, document chunking must balance fine-grained information extraction with contextual completeness, and effectively process tabular data and complex text passages.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Medical insurance claim documents can contain extensive detailed data or multi-page PDFs, requiring a larger file upload limit. |
Chunk size (Chunk Length) | 800–1200 characters (characters) | Balances fine-grained information extraction with contextual completeness, preventing key codes or expense details from being truncated. |
Chunk Overlap Length (Chunk Overlap Length) | 100 characters (characters) | Ensures continuity of context at chunk boundaries, improving recall. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds (seconds) | Parsing large files and OCR processing can be time-consuming, requiring a longer timeout. |
pdf_ocr_accuracy | high | Ensures high-accuracy recognition of text in PDF-formatted medical insurance vouchers and policy documents. |
table_parsing_strategy | auto_detect | Medical insurance data often appears in tables; automatic detection improves the accuracy of table data parsing. |
Common Pitfalls
- "OCR Error" when uploading large PDF files: This occurs because
PARSE_FILE_TIMEOUT_SECONDSis set too short, preventing OCR processing from completing. - Inability to recall specific key clauses from medical insurance policies during search: This happens when
Chunk size(Chunk Length) is too long, or the chunking strategy fails to effectively identify policy clause boundaries, diluting important information within overly large chunks. - Expense detail fields in medical insurance settlement manifests are empty: This is due to an improper or disabled
table_parsing_strategyconfiguration, failing to correctly parse the table structure.
Verification Steps
- Upload typical medical insurance settlement PDFs and Word files. Examine the parsed chunk content to ensure key codes, expense details, and other fields are complete and accurate.
- Perform search tests for specific clauses within medical insurance policy documents. Verify that recall results are accurate and include complete context.
- Check parsed medical insurance settlement manifests in the knowledge base. Ensure that all table data fields (e.g., drug costs, treatment items) are correctly extracted and populated.
The values provided are common starting points and should be measured against your own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.