Data Characteristics
Data for DTP pharmacy clinical trial pre-screening primarily originates from Pharmacy Management Systems (PMS), patient medication records, prescription information, and anonymized health data shared with patient consent. Data updates typically occur daily or in real-time, especially during patient medication purchases and prescription transfers. The document structure is mainly structured data, such as JSON or XML formatted patient profiles, drug batch information, and sales records. Key fields include patient_id, drug_code (e.g., ATC code), dosage, prescription_date, and pharmacy_id. Some data may exist as PDF physician diagnostic reports or scanned paper medical records, requiring additional OCR processing. Units commonly involve dosage (milligrams, milliliters), frequency (times per day), and course of treatment (days).
Constraints on Reference and Traceability
The highly structured and real-time nature of DTP pharmacy data places strict requirements on the accuracy and timeliness of references. Because data directly relates to patient medication, any reference error can affect the accuracy of pre-screening results. Real-time updates mean the knowledge base must capture the latest patient medication status when referencing, avoiding the use of outdated information. Unstructured data in PDF format requires robust parsing capabilities to ensure critical fields like diagnostic descriptions and medication contraindications are accurately extracted and included in the scope of reference. Data sources are distributed across multiple systems (PMS, electronic prescription platforms), requiring the referencing mechanism to trace across systems to specific data records and their original sources, such as a particular prescription ID or patient visit record.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
maxContext | 2000 characters | Ensures sufficient patient medication and prescription details are included within a limited context window. |
Recall Count | Top 5 | Balances recall efficiency with information noise, focusing on the most relevant medication or diagnostic records. |
Similarity Threshold | 0.75 | Filters out irrelevant patient information or drug descriptions, improving matching accuracy. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Accommodates OCR and parsing time for large PDF format physician diagnostic reports. |
Reranked Return Count | Top 3 | Further refines the most direct evidence supporting pre-screening decisions based on initial recall. |
EXTERNAL_DATA_REFRESH_INTERVAL | 60 minutes | Ensures the knowledge base references the latest patient medication and prescription data from DTP pharmacies. |
Common Pitfalls
- The medication dosage or frequency cited in pre-screening results does not match the patient's actual medication records. This occurs because the knowledge base synchronizes external data sources too infrequently, failing to update the patient's latest prescription in a timely manner.
- The system misses critical contraindication information when parsing handwritten or scanned diagnostic reports from doctors. This prevents the pre-screening model from referencing it. This occurs because the OCR engine lacks sufficient recognition capabilities for specific medical terminology or layouts.
- When calling external tools to upload file parameters, the tool cannot correctly reference variables, leading to file upload failure. This occurs because the tool interface only supports direct links or hardcoded values, not dynamic variable passing.
Validation
- Select a virtual patient profile with a known medication contraindication. Verify that the pre-screening result accurately references this contraindication and can be traced back to the specific electronic prescription ID.
- Upload a PDF diagnostic report containing complex medical terminology and charts. Check if key information from the report (e.g.,
diagnosis result,treatment plan) is correctly extracted and incorporated into the knowledge base. Also, verify that its reference source points to that PDF file. - Randomly sample 10 pre-screening results. Cross-check if the medication information cited (
drug_code,dosage,prescription_date) is completely consistent with the original records in the DTP pharmacy management system.
The values given 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.