🛡️ Clinical Data Anonymizer

A Python tool for pseudonymizing patient data for Clinical Trials. Ensures privacy compliance by hashing PII (Personally Identifiable Information) while preserving data utility.

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🏥 Context

In Clinical Trials, sharing raw patient data (Names, National IDs/PESEL) with Sponsors or CRA is strictly prohibited by GDPR (RODO). However, data consistency is key – if "Patient A" returns for a follow-up visit, they must be identified as the same entity without revealing their real identity.

This tool solves that problem.

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⚙️ How It Works

The script processes raw CSV files containing sensitive medical data and transforms them into a "Safe Copy" for export.

Key Algorithms:

1. Deterministic Hashing (SHA-256):
   • Converts Name + Surname + ID into a unique alphanumeric string (e.g., SUBJ-8A2F...).
   • Benefit: The same patient always gets the same code (allowing follow-up tracking) but cannot be reverse-engineered to reveal their identity.
2. Smart Age Extraction:
   • Removes the PESEL/National ID number entirely.
   • Extracts the birth year from the ID and calculates the current Age.
   • Fixes Data Quality: Automatically repairs malformed IDs (e.g., missing leading zeros in Excel exports).

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🚀 Usage

1. Input Data (pacjenci_raw.csv)

Prepare a CSV file with sensitive data:

Imie,Nazwisko,PESEL,Wynik_HGB
Jan,Kowalski,85021012345,14.5
Piotr,Wiśniewski,01231205555,15.2

2. Run the Anonymizer

python main.py

3. Output Data (dane_dla_sponsora.csv)

​The script generates a safe file ready for transmission (Clean UTF-8, no BOM): PATIENT_ID,WIEK,WYNIK SUBJ-8C50D64...,40,14.5 SUBJ-8D8093F...,24,15.2

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👨‍🔬 About the Author

Mateusz Jakubowski Medical Analyst (15y exp) ➡️ Aspiring AI Engineer & Python Developer.

I am building tools that bridge the gap between Medical Diagnostics and IT. This project was developed entirely on a mobile environment (Samsung DeX + Pydroid 3).

• Connect with me: LinkedIn
• Portfolio: #FromPipetteToPython

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⚠️ Disclaimer & Legal Notice

• Educational Purpose Only: This software is developed as part of a programming portfolio (#FromPipetteToPython) and is intended for educational and demonstration purposes only.
• Not a Medical Device: This tool is not a validated Laboratory Information System (LIS) or a medical device under MDR/FDA regulations. It has not undergone formal GAMP5 validation for use in GxP environments.
• GDPR/RODO Responsibility: While this tool implements standard hashing algorithms (SHA-256), the final responsibility for data privacy and compliance lies with the user. The author is not liable for any data breaches or misuse of this software.
• Synthetic Data: All data presented in examples (e.g., in pacjenci_raw.csv) is synthetic (fake) and generated for testing purposes. Never upload real patient data to a public GitHub repository.