HTTP Interface and External Systems for Pharmacoeconomics

Pharmacoeconomics Data Characteristics

Pharmacoeconomics data originates from multiple sources. These include clinical trial reports, real-world evidence (RWE) studies, healthcare cost databases, drug pricing policy documents, and health technology assessment (HTA) agency reports. Data update frequencies vary. Clinical trial data might update every few years. Drug prices or insurance payment policies might adjust annually or quarterly. Document structures are diverse. Common formats include PDF reports, Excel spreadsheets for cost-effectiveness model input data, and structured databases for drug usage and cost details. Specific metrics include Quality-Adjusted Life Years (QALY), Incremental Cost-Effectiveness Ratio (ICER), and Defined Daily Dose (DDD). Units involve currency (e.g., USD, EUR), life-years, and various clinical indicators.

Constraints on "HTTP Interface and External Systems"

The complexity and diversity of pharmacoeconomics data sources require HTTP interfaces to handle multiple data formats and authentication mechanisms. For example, accessing HTA agency APIs might need specific API keys or OAuth authentication. Inconsistent data update frequencies mean external system integration needs flexible caching strategies and data synchronization mechanisms. This avoids frequent fetching of static data while ensuring the timeliness of critical dynamic data (e.g., latest drug prices). The diversity of document structures, especially the large number of unstructured PDF reports, makes parsing HTTP interface responses challenging. This might require combining OCR or document parsing services. The presence of unique fields and units requires interfaces to clearly define data types and units during data transmission. This prevents parsing errors in downstream systems, for example, explicit currency codes (currency_code) and floating-point precision for QALY values.

Configuration Guidelines

Configuration Item	Suggested Value	Rationale
`requestTimeout`	`60 seconds`	Pharmacoeconomics data queries might involve complex calculations or multi-source data aggregation. Extend the timeout to handle potential delays.
`maxRetries`	`3 times`	External data sources experience occasional network fluctuations or service instability. Retries improve success rates.
`contentType`	`application/json` or `application/xml`	Ensure consistency with the data exchange format agreed upon with the external API, typically JSON or XML.
`headers`	Include `Authorization` field	Many pharmacoeconomics data APIs require an API Key or Bearer Token for authentication.
`cacheTTL`	`24 hours`	For static data with low update frequency, such as historical ICER values, caching reduces API call burden.
`responseSchema`	Defined by external API documentation	Clearly define the response data structure for subsequent data extraction and validation, for example, including `ic_value` and `currency_unit` fields.

Common Pitfalls

Calling an external API returns HTTP 401 Unauthorized or 403 Forbidden. The Authorization request header's API key or token is incorrectly configured or passed.
The HTTP request succeeds, but key fields in the response (e.g., QALY_value or cost_per_patient) are empty. Request parameters might be incorrect, or the external API does not return that field under specific conditions.
A returned PPTX file cannot be directly stored and provided to the user. The HTTP client defaults to processing the response body as text. Configure it as a binary stream and write it correctly to the file system.

Verification Steps

Simulate a request using an API debugging tool (e.g., Postman). Verify the HTTP status code is 200 OK. Check if the response body contains the expected pharmacoeconomics key fields (e.g., ICER, QALY).
Invoke the HTTP interface within FastGPT. Observe log output. Confirm no connection timeouts or parsing failures.
For specific queries, compare data returned directly by the external system with data obtained and processed by FastGPT via the HTTP interface. Verify numerical precision and unit consistency, especially for currency and time units.

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.