ccd-deidentification 0.2.1

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CCD Deidentification

This Python project is designed to de-identify Continuity of Care Documents (CCDs), which are XML files used in healthcare to encode patient information.

Features

• Masks sensitive information in various parts of the CCD, such as names, IDs, birth times, addresses, and telecom values.
• Uses spaCy for natural language processing to mask free-text sections.
• Consistently masks the same original text with the same masked value.
• Logs details about masked items.
• Can convert the log of masked items into a Spark DataFrame.
• Can parse a CCD XML string, de-identify sensitive info, and return modified XML.

Dependencies

This project depends on several Python packages, including:

• lxml
• spacy
• pydantic
• jinja2
• markupsafe2

These can be installed using pip:

pip install -r requirements.txt

Usage

First, create an instance of CCDDeidentifier:

from ccd_deidentification.deidentifier import CCDDeidentifier

deidentifier = CCDDeidentifier()

Then, you can use the deidentify_ccd_xml method to de-identify a CCD XML string:

deidentified_xml = deidentifier.deidentify_ccd_xml(original_xml)

The deidentify_ccd_xml method returns a new XML string with sensitive information masked.

You can also use the mask_map_to_data_frame method to convert the log of masked items into a Spark DataFrame:

df = deidentifier.mask_map_to_data_frame()

Note

This project is designed for production use in Health Information Exchanges or similar environments. As with any software that handles sensitive data, it should be thoroughly reviewed and tested to ensure it meets all relevant legal and ethical standards for data handling and privacy.