Forms and Interactions for Pharmacovigilance Products

Understanding Pharmacovigilance Data

Pharmacovigilance data originates from clinical trial reports, real-world studies, adverse event reporting systems (e.g., WHO VigiBase, FDA FAERS), and medical literature. This data typically exists in a mixed format, combining structured records (e.g., database entries) with unstructured content (e.g., free-text descriptions, PDF documents). The update frequency is high, especially for adverse event reports, which can arrive in real-time. Document structures are complex, encompassing patient information, drug details, event descriptions, medical terminology, and diagnostic codes. Attachments, such as medical images or lab reports, are common. Fields include drug batch numbers, dosages, administration routes, event timestamps, reporter professions, and outcomes. Medical units (e.g., mg/kg, mmol/L) and specialized terminology are used extensively.

Constraints Imposed by Data Characteristics on Forms and Interactions

The complexity of pharmacovigilance data necessitates form designs capable of capturing multi-dimensional information effectively. High update frequency demands system support for real-time or near real-time data entry and querying, along with the ability to handle a large volume of concurrent requests. Mixed data formats pose challenges for forms, requiring both rapid selection for structured fields and intelligent parsing and semantic understanding for unstructured text. The intensive use of specialized terminology and medical units requires input fields with intelligent suggestions, synonym matching, and automatic unit conversion features to minimize entry errors. Furthermore, managing multiple attachments and version control becomes a critical consideration in interaction design to ensure data integrity and traceability.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`maxContext`	`16384`	Pharmacovigilance reports often contain detailed descriptions and multiple indicators, requiring a longer context window to ensure semantic completeness.
`Chunk size` (Segment Length)	`500 characters` (characters)	Ensures each segment can contain a relatively complete medical event description while avoiding excessive length that could reduce processing efficiency.
`Recall count` (Recall Count)	`Top 10 entries` (top 10)	Improves the recall rate of relevant adverse event reports or drug information, covering more potential associations.
`Similarity threshold` (Similarity Threshold)	`0.75`	Balances recall precision and completeness, filtering out irrelevant results while retaining potentially important information.
`Form Cache Duration`	`600 seconds` (seconds)	Users may require extended time to complete complex forms; caching prevents accidental data loss and improves user experience.
`ATTACHMENT_MAX_SIZE`	`50 MB`	Pharmacovigilance reports often include images or detailed examination reports, requiring support for larger file uploads.

Common Pitfalls

Input fields clear after form submission, preventing users from reviewing or modifying entries. This usually occurs because the frontend fails to correctly save or repopulate form states, or the backend does not return original input after validation failure.
Dropdown lists for selecting drug names or adverse event types are empty or incomplete. This may be due to a disconnected data source, API response timeouts, or insufficient knowledge base synchronization frequency, leading to outdated data.
"File too large" or upload failure messages appear when uploading large medical image files. This indicates that the ATTACHMENT_MAX_SIZE configuration for file uploads is set too low, or server parameters like upload_max_filesize have not been adjusted accordingly.

Validation Steps

Simulate submitting a pharmacovigilance report containing complex medical terminology and multiple attachments. Verify that all fields are correctly parsed and stored, and that attachments can be previewed and downloaded.
Test whether form content is correctly cached and restored after a page refresh, especially after network fluctuations or prolonged inactivity. Evaluate the effectiveness of Form Cache Duration.
Use a query containing a specific drug batch number and event description to verify that the system returns comprehensive and accurate relevant information. Compare the recall results against expected manual associations to determine the reasonableness of Recall count and Similarity threshold.
Upload files of different sizes and formats to confirm that the ATTACHMENT_MAX_SIZE setting meets actual needs and that the upload process is stable.

Note: The values provided are common starting points and should be measured against specific 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.