Patient Assistance Pharmacovigilance HTTP Interface and

Data Characteristics

Patient Assistance Program (PAP) pharmacovigilance data includes patient registration information, medication records, adverse drug reaction (ADR) reports, and follow-up details. Data sources are diverse, including medical institutions, patient self-reports, and program administrators. Update frequency is typically near real-time or daily batch updates, especially for adverse event reports, which require timely entry. Data documents are usually in structured formats like JSON, XML, or CSV, and may contain nested structures. Key fields include patient_id, drug_name, adverse_event_description, event_date, severity (e.g., mild, moderate, severe), and report_source. Time fields are typically precise to the day or to hours, minutes, and seconds, for example, 2023-10-27 14:30:00.

Constraints Imposed by "HTTP Interface and External Systems"

The diverse sources and real-time requirements of patient assistance data mean the HTTP interface must support parsing various data formats and handle high-concurrency write requests. The timeliness of adverse event reports requires sufficiently short interface response times to avoid safety risks from data delays. Structured data necessitates precise mapping of external system data fields to FastGPT knowledge base or Agent variables. This is particularly true for enumeration values like severity, which require standardization. Batch import and periodic updates of historical data require the HTTP interface to support efficient data synchronization mechanisms, such as incremental updates or full overwrites. Handling sensitive patient information means the interface must have strict authentication and authorization mechanisms and ensure data transmission encryption, for example, using HTTPS.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`HTTP Method`	`POST` or `PUT`	Suitable for creating or updating adverse event reports, supports batch data transfer.
`Content-Type`	`application/json`	Adapts to mainstream external system data formats, easy to parse and process.
`Timeout`	`3000–5000 ms`	Ensures timely response for real-time adverse event reports, avoids prolonged blocking.
`Authentication`	`Bearer Token` or `API Key`	Provides secure interface access control, protects patient data privacy.
`Request Body Size Limit`	`5-10 MB`	Accommodates data volume for single batch imports or multiple adverse event reports.
`Error Code Mapping`	`Custom`	Maps external system error codes to FastGPT-understandable error types for failure handling.

Common Pitfalls

FastGPT does not receive data or some fields are missing after an external system sends data to the FastGPT interface. This is due to incorrect Content-Type settings in the external system or a request body JSON structure that does not match FastGPT's expectations.
Frequent 401 Unauthorized or 403 Forbidden errors occur during interface calls. This usually means the Bearer Token in the Authorization header is expired, invalid, or the API Key is not configured correctly.
Database workflow execution fails, indicating SQL queries do not return data. This may be because query parameters from the external system (e.g., patient_id) do not match the actual field type or value stored in the database.

Verification Steps

Send a simulated adverse event report from the external system. Observe whether a corresponding document is added to the FastGPT knowledge base and verify the accuracy of key fields (e.g., adverse_event_description, severity).
Check FastGPT interface logs for 200 OK or 201 Created HTTP status codes and confirm that request processing time meets expectations.
Use FastGPT's Agent debugging feature. Simulate user questions to verify if the Agent can correctly retrieve and utilize adverse event data imported via the HTTP interface for responses, for example, querying a patient's historical adverse events.
When the external system sends a large volume of data, check if FastGPT's interface concurrency handling and error handling mechanisms function correctly. Pay close attention to the frequency of 5xx error codes.

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 2026-09-21.