Data Characteristics
Medical insurance access regulation data primarily originates from official documents released by national and local medical security bureaus. These include national medical insurance drug catalogs, treatment item catalogs, payment standards, negotiation outcome announcements, and various policy interpretations and implementation rules. Documents typically update annually or on an irregular basis. Updates are frequent during critical periods such as drug negotiations and catalog adjustments. Documents are predominantly in PDF format and often contain chapter headings, tables (drug information, coverage scope), clause descriptions, and appendices. Fields and units are highly specialized. Examples include drug name, generic name, dosage form, specifications, medical insurance payment standard (yuan/unit), indications, restricted payment scope, and effective date. Units are precise, down to milligrams, milliliters, tablets, or injections.
Constraints from Document Characteristics on Parsing and Chunking
The official source and fixed release cycle of medical insurance access documents mean that document parsing requires timeliness and accuracy. This is especially true when policies are updated, requiring a rapid response. PDF documents contain many complex tables. The parser needs high-precision table recognition and structured extraction capabilities to avoid losing critical payment standards or restricted condition information. Specialized fields, such as generic drug names, indications, and payment scopes, require effective identification during chunking to maintain information integrity. This prevents semantic ambiguity caused by fragmentation. Regional policy differences mean that knowledge base construction needs effective tagging and management of regional attributes to ensure the geographical relevance of question-answering results. Legal and cross-references, common in these documents, also demand logical coherence in chunking.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
Chunk size (Chunk Length) | 800–1200 characters | Balances information completeness and retrieval efficiency, avoiding excessive fragmentation. |
Overlap Length | 150–250 characters | Ensures contextual continuity and handles semantic dependencies across paragraphs. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Accommodates the parsing time for large PDF files, which can be hundreds of pages. |
pdf_parse_method | table_and_text | Medical insurance documents contain many tables, requiring both text and table parsing. |
maxContext | 4000 characters | Adapts to the complex descriptions in medical insurance policies, ensuring question-answering context. |
Common Pitfalls
- Parsing multi-hundred-page documents fails or times out, while parsing multi-dozen-page PDFs works normally. The file parsing service returns an error code or times out. This can occur if
PARSE_FILE_TIMEOUT_SECONDSis set too low, and large document processing exceeds the preset limit. - Critical data, such as medical insurance payment standards, are missing or inaccurate in question-answering. The answer does not mention specific values or contains incorrect units. This happens when document parsing fails to accurately recognize complex table structures in PDFs, leading to incomplete data extraction or incorrect formatting.
- An error occurs when parsing JSON data from network searches, or the file parsing function fails after local deployment. This can be due to incompatible versions of external libraries that the parsing service depends on, or network proxies/firewalls blocking the parsing service's access to external resources.
Verification Steps
- Upload a medical insurance policy PDF file containing complex tables and multi-level headings. Check if the parsed chunks fully retain table data and key fields.
- Randomly select specific medical insurance drugs from the document. Query their payment standards, indications, and other information. Verify if the question-answering results match the original document.
- Parse a long document. Monitor the parsing service's status to ensure parsing completes within the expected time and generates valid chunks, without timeouts or error messages.
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.