What this category of data looks like
Data sources include the national medical insurance information platform, hospital HIS and medical insurance interfaces, medical insurance catalog and coding database, and cross-regional medical settlement platform. The update frequency is daily. Commonly processed documents include medical insurance settlement lists, expense details, medical record homepages, prescriptions, rejection lists, and settlement reconciliation statements. These documents cover fields such as insured person information, diagnosis and treatment project codes, drug and consumable codes, expense amounts, and settlement time. Field units comply with general norms for medical expense settlement.
What constraints do these characteristics impose on document parsing and chunking
Diverse data sources have varying formats, including structured forms and batch tables. The parsing module must adapt to field extraction rules for different document formats. Single documents and batch data have large volume. The module must support parsing and chunking of long text and multi-row, multi-column data. The daily update business requirement demands timely parsing. Delays must be avoided to prevent task interruptions from timeouts. Structured fields such as coding fields require accurate extraction. Chunking must not break the association between fields and their corresponding business content. Broken associations will affect subsequent audit matching.
How to configure settings
This configuration uses FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the context length of codes and corresponding expenses in medical insurance documents. It prevents splitting of critical associated information. |
chunkSplitter | Chunk by paragraph + semantics | Matches structured paragraphs in medical insurance documents, such as settlement items and rejection explanations. It avoids splitting content across business logic. |
customPdfParse | Enable structured parsing | Adapts to fixed formats of medical record homepages and settlement lists. It accurately extracts structured fields such as codes and amounts. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Meets upload requirements for 15,000-row Excel batch data and Word documents with 100,000 Chinese characters. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Supports parsing time for large-volume documents and batch data. It prevents timeout interruptions during processing. |
chunkSettingMode | Manual configuration | Adjusts chunking rules based on the structured characteristics of medical insurance documents. It adapts to business-specific field association logic. |
Three common configuration errors
- Phenomenon: Large-volume Word documents fail parsing. The interface displays a timeout status. Cause: The
PARSE_FILE_TIMEOUT_SECONDSvalue was not adjusted to a range suitable for long documents. The default duration is insufficient to complete full parsing. - Phenomenon: After importing batch Excel data, only the header appears in chunking results. No detailed content is included. Cause: The
chunkSplitterwas not configured to adapt to semantic associations in table rows. Splitting only by character count causes detailed rows to be split independently. - Phenomenon: The diagnosis and treatment project code field is empty after parsing. Cause: Structured parsing via
customPdfParsewas not enabled. Plain text parsing cannot recognize fixed-format code fields, leading to loss of critical business information.
How to confirm the configuration is correct
- A single Word document with 100,000 Chinese characters is uploaded. The parsing task status and duration are checked to confirm no timeout is triggered.
- 15,000-row Excel expense details are imported. Each chunk after processing is verified to contain 3 to 5 consecutive detailed entries and their corresponding codes.
customPdfParseis enabled, then a medical record homepage is parsed. Fields such as diagnosis and treatment project codes and expense amounts are confirmed to be accurately extracted.chunkSizeis adjusted to the 800–1200 character range. Each chunk is verified to not split the association between codes and their corresponding expense amounts.
The values listed above are common starting points. Adjust them based on the reader's own specific samples and business requirements.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.