Form and Interaction for Medical Insurance Settlement

Data Characteristics for This Category

Medical insurance settlement product data is highly structured. It primarily comes from policy documents, payment standards, drug catalogs, and treatment catalogs published by national and local medical insurance bureaus. This data updates frequently. During policy adjustment periods, some fields may update monthly. Documents are typically released as PDFs, Excel files, or structured databases. Content includes fields such as generic drug names, medical insurance payment categories, reimbursement ratios, price limits, indications, and payment scopes. Units include currency (Yuan), percentages (%), and dates (Year/Month/Day). Numerical precision is critical; for example, reimbursement ratios may be precise to two decimal places. Field naming conventions vary, with abbreviations and aliases present, requiring standardization.

Constraints Imposed by These Characteristics on "Form and Interaction"

The highly structured nature and frequent updates of medical insurance settlement data directly influence product form design and interaction logic. Due to the complexity of medical insurance policies, users may need to provide multiple key pieces of information to get accurate results when consulting. This includes patient age, region, diagnosis, drug name, and treatment item. These details must be precisely collected via forms. Frequent data updates require the knowledge base to support rapid synchronization and indexing, ensuring real-time and accurate query results for users. Form field naming and validation rules must strictly adhere to medical insurance policy terminology to avoid ambiguity. For instance, the reimbursement ratio field needs to support floating-point input and range validation. Additionally, due to the large volume and strong interconnectedness of data, clear guidance and multi-level filtering functions are necessary in interactions to help users quickly locate needed information, such as filtering drug catalogs by disease classification.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`Chunk size`	`300–500 characters`	Medical insurance policy articles are usually short. This maintains semantic completeness and reduces information fragmentation.
`Recall count`	`Top 5–8 entries`	This improves relevance, avoids introducing excessive irrelevant information, and covers multi-faceted policy interpretations.
`Similarity threshold`	`0.75–0.85`	Medical insurance terminology demands high precision. A low threshold may lead to mismatches, while a high one may miss relevant information.
`Rerank result count`	`Top 3 entries`	This focuses on the most core and critical policy terms, improving user efficiency in obtaining information.
`maxContext`	`3000–4000 token`	This ensures the ability to carry context information for complex medical insurance policies, supporting multi-turn conversations.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Medical insurance policy files may contain many tables and complex structures, requiring ample parsing time.

Three Common Pitfalls

During chat conversations, the system prompts that no knowledge base is selected, but the debug preview works normally: This typically occurs because the knowledge base node in the workflow is not correctly configured with a Knowledge base ID, or the corresponding knowledge base version is not deployed in the production environment.
The AI model dropdown list for problem classification in the workflow is empty: This usually means the AI_MODEL_LIST configuration item is not set correctly, or the selected model is unavailable in the current deployment environment.
The global variable "Select Knowledge Base" cannot be dynamically assigned: This is because the Knowledge Base Selection field in some versions does not support dynamic binding at runtime. This requires modifying the workflow logic or upgrading to a version that supports this feature.

How to Verify Correct Configuration

Build test cases with complex conditions and specialized terminology for typical query scenarios in medical insurance settlement. Verify that the system accurately retrieves relevant policy terms.
Simulate medical insurance policy updates by uploading new policy documents. Check the knowledge base index update speed and the real-time nature of query results.
Enter edge case data into forms (e.g., amounts exceeding reimbursement scope, ineligible ages). Verify that the system provides correct prompts or rejection messages.

Note: The values provided are common starting points. Measure them 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.