HTTP Interface and External Systems for DTP Pharmacy

Data Characteristics for This Category

Data for DTP pharmacies in clinical trial pre-screening primarily comes from pharmacy management systems, patient recruitment platforms, and some offline registrations. Data updates frequently. Key fields such as patient basic information, medication records, disease diagnoses, and allergy history update in real-time or near real-time with daily DTP pharmacy operations. Data documentation typically comes as API interface specifications or database table structure definitions. It includes fields like patient ID, name, age, gender, primary diagnosis (ICD-10 code), co-morbidities, current medication (ATC code or generic drug name), past medication history, treatment plans, and contact information. Diagnosis and medication data often involve standardized international coding systems, ensuring data accuracy and interoperability.

Constraints from "HTTP Interface and External Systems"

High update frequency of DTP pharmacy data requires an efficient data synchronization mechanism. This ensures real-time pre-screening results. Standardized coding for diagnosis and medication data requires precise matching of ICD-10 and ATC codes during data mapping and cleaning. This avoids pre-screening errors due to inconsistent codes. Handling sensitive patient personal information demands strict security and encrypted data transmission for HTTP interfaces, such as mandatory HTTPS. DTP pharmacy data often distributes across different internal systems or external recruitment platforms. This means integrating multiple HTTP interfaces and handling varying data formats and authentication mechanisms. The complexity of this data makes HTTP request concurrency and response time critical considerations.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`HTTP_REQUEST_TIMEOUT_SECONDS`	`60 seconds`	DTP pharmacy interface response times typically range from seconds to tens of seconds; 60 seconds covers most cases.
`MAX_CONCURRENT_REQUESTS`	`Calibrate by actual measurement`	Determine based on DTP pharmacy interface concurrency limits and system load capacity.
`AUTH_TOKEN_EXPIRY_SECONDS`	`3600 seconds`	Usually consistent with DTP pharmacy interface authentication token validity, reducing frequent refreshes.
`DATA_PAGINATION_LIMIT`	`200 entries/Pages`	Common DTP pharmacy interface pagination limit, balancing single request data volume and response speed.
`RETRY_INTERVAL_SECONDS`	`5-10 seconds`	Handles occasional transient failures in DTP pharmacy interfaces, avoiding frequent retries that increase burden.
`CONTENT_TYPE_HEADER`	`application/json`	Most DTP pharmacy interfaces use JSON format for data transfer.

Common Pitfalls

An external system interface call returns a 200 status code, but data fields are empty. This happens due to a misunderstanding of the DTP pharmacy interface's returned data structure, leading to incorrect parsing of nested fields.
The system experiences interface timeouts during peak data hours in the early morning. This occurs because the load on DTP pharmacy systems during specific periods was not fully considered, and MAX_CONCURRENT_REQUESTS was set too high or too low.
Some patients' medication information is missing in the pre-screening results. This is because the DTP pharmacy interface's medication codes contain non-standard values or ambiguities, leading to data mapping failures.

How to Verify Configuration

Monitor HTTP request success rates and response time distribution to ensure stable DTP pharmacy interface calls.
Regularly compare pre-screened patient data in FastGPT with original DTP pharmacy data. Check the accuracy and completeness of key fields like diagnosis and medication.
Simulate different concurrency levels and data loads. Stress test parameters like MAX_CONCURRENT_REQUESTS and HTTP_REQUEST_TIMEOUT_SECONDS to confirm system operation during peak periods.

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.