What This Category of Data Looks Like
This category of data originates from the National Medical Security Information Platform, hospital HIS and medical insurance interfaces, medical insurance catalog coding database, and cross-provincial medical settlement platform. Data updates occur daily. Daily processed documents include medical insurance settlement lists, expense details, medical record homepages, prescriptions, rejection lists, and settlement statements. These documents contain fields such as diagnosis and treatment item codes, drug and consumable codes, expense amounts, visit dates, and insured person information. The platform supports single or batch expense audit services. Data structures are unified, and compliance verification requires matching against official coding databases.
Constraints Imposed on the Model Access and Configuration Link
Medical insurance expense settlement audit data has diverse sources and requires daily synchronization. This requires the model access link to support format compatibility for multi-interface data and scheduled updates. Documents include multiple types of structured and semi-structured materials. Single batch audits may generate large context lengths, so the model’s context carrying capacity must be adapted. Core links such as code matching and consistency verification require highly stable output results to avoid random deviations. Batch businesses such as rejection reconciliation require processing multiple associated documents, which places clear requirements on the model’s context integration capability. Compliance with medical insurance data access control specifications is also required.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the combined input length of multiple materials such as medical insurance settlement lists, details, and medical records, covering the context requirements of batch audits |
maxTokens | 4000–6000 token | Balances audit result output length and model inference speed, adapting to the result output requirements of single batch audits |
quoteMaxToken | 1500–2000 token | Retains complete core reference text information such as medical insurance catalog codes and expense details, ensuring matching accuracy |
temperature | 0.1–0.3 | Reduces model generation randomness, improves the accuracy of code matching and consistency audits, and avoids audit result deviations |
AIPROXY_API_ENDPOINT | Fill in the address of the locally deployed proxy service | Adapts to locally deployed model call links, ensuring data transfer complies with medical insurance data control requirements |
AIPROXY_API_TOKEN | Fill in the key generated by the proxy service | Ensures identity verification security for model calls, complying with medical insurance data access permission control specifications |
Three Common Misconfigurations
- Issue: Multiple uploaded documents such as medical insurance settlement lists and medical record homepages exceed the model’s context upper limit, triggering a context overflow error. Cause: The
maxContextparameter is not adjusted to adapt to the total input length of multiple medical documents. - Issue: The diagnosis and treatment item code matching results returned by the model do not match the medical insurance catalog database, with empty fields or matching errors. Cause: The
temperatureparameter is set too high, causing the model’s generated result randomness to exceed compliance limits. - Issue: A locally deployed DeepSeek model fails to call normally, returning 401 authentication failure or connection timeout errors. Cause: The
AIPROXY_API_TOKENorAIPROXY_API_ENDPOINTparameters are not configured correctly, and the proxy service’s key and address are not matched.
How to Verify Successful Configuration
Upload a single medical insurance settlement list and corresponding prescription, and verify that the code matching results output by the model match the fields in the medical insurance catalog database. Batch upload 3 to 5 settlement detail documents, verify that the maxContext parameter can carry the total input length without context overflow errors. Call the proxy service interface, and verify that the AIPROXY_API_ENDPOINT and AIPROXY_API_TOKEN configurations can normally return model inference results. Adjust the temperature parameter to 0.2, audit the same rejection list multiple times, and verify that the audit results remain stable.
The values provided are common starting points and 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 2026-09-28.