Data Characteristics for this Category
Medical insurance access registration and declaration documents primarily include technical review reports for drugs/devices, clinical trial data, pharmacoeconomic evaluation reports, domestic and international market status, and applicant enterprise qualifications. Data sources are diverse: public databases from the National Healthcare Security Administration and the National Medical Products Administration, internal R&D and clinical systems, and third-party research institution reports. Document formats vary, including PDFs, Word documents, Excel files, and structured database records. Update frequency for medical insurance policies and drug catalogs is relatively fixed, typically once or twice a year, while market competition and pharmacoeconomic data may change dynamically. Fields and units are highly specialized, such as "ATC classification code," "generic name," "administration route," "indications," "payment scope," "reimbursement ratio," and "procurement price." Accuracy, consistency, and traceability requirements for this data are extremely high.
Constraints Imposed by these Characteristics on "Workflow Orchestration"
The diverse data sources and document types for medical insurance access materials require workflows with robust heterogeneous data processing capabilities. These capabilities must effectively parse and integrate structured and unstructured information. The low update frequency means data ingestion does not require frequent triggers. However, each update typically involves a large volume of data, demanding efficient file parsing and vectorization. Specialized fields and units emphasize the accuracy of information extraction and entity recognition within the workflow. This requires pre-configured or dynamic recognition of numerous specialized terms and measurement units from the biomedical domain. Furthermore, the accuracy of critical numerical values, such as reimbursement ratios and procurement prices, determines the correctness of downstream decisions. Therefore, strict data validation and cleaning are essential during data processing to ensure data quality. Complex document structures also necessitate flexible document segmentation and content association within the workflow to maintain contextual completeness.
Configuration Settings
| Configuration Item | Recommended Value | Rationale for Recommendation |
|---|---|---|
FILE_MAX_SIZE | 100 MB | Medical insurance access documents often include large PDF files; this size covers most documents. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing complex PDFs and Word documents can be time-consuming; this allows sufficient time to avoid parsing failures. |
Chunk size (Chunk Length) | 800–1200 characters | Balances semantic completeness and recall efficiency, ensuring critical information is not truncated. |
Recall count (Retrieval Count) | Top 8 entries | Medical insurance policies and drug catalogs are highly interconnected, requiring more contextual support. |
Similarity threshold (Similarity Threshold) | 0.75 | Ensures the relevance of retrieval results, filtering out loosely related information. |
Rerank result count (Reranked Return Count) | Top 3 entries | Further refines retrieval results, improving the accuracy of the final output. |
Three Common Mistakes
- Workflow execution timeouts or file parsing failures occur when
PARSE_FILE_TIMEOUT_SECONDSis set too low. This prevents processing large or structurally complex PDF documents. - Key fields in generated declaration documents are empty or missing. This usually happens because information extraction nodes in the workflow are not correctly configured with entity recognition rules, failing to identify specialized terminology specific to the medical insurance domain.
- API calls return "Key is error. You need to use the app key rather than the account key." This indicates that incorrect authentication credentials were used for the call. An application-level API key should be used for authentication.
How to Confirm Proper Configuration
- Upload typical medical insurance access declaration documents. Check the file parsing status to ensure all documents are successfully parsed and vectorized without errors.
- Conduct information extraction tests on key documents, such as medical insurance policies and drug instructions. Verify the extraction accuracy of core fields like "ATC classification code" and "payment scope." Adjust entity recognition rules or prompts based on the actual results.
- Simulate user query scenarios, such as asking "What is the reimbursement ratio for a certain drug in a specific province?" Verify the accuracy and completeness of the workflow's retrieval results. Manually assess the match between the results and expected answers to set an acceptable threshold.
The values provided above are common starting points. They should be measured against the reader's 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.