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reidentifying-text

Pseudonymize clinical text and restore protected health information via OpenMed's reidentify workflow.

5.0k|615|Updated Oct 4, 2025
Search Tags:#gdpr#hipaa#phi#de-identification#pseudonymization#clinical text#reidentification
One-click install
npx skills add https://github.com/maziyarpanahi/openmed --skill reidentifying-text
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reidentifying-text
Source: https://github.com/maziyarpanahi/openmed/tree/main/skills/reidentifying-text
Command: npx skills add https://github.com/maziyarpanahi/openmed --skill reidentifying-text

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables authorized teams to remove protected health information from clinical text while preserving the ability to restore the original content later. It helps distinguish reversible GDPR pseudonymization from irreversible HIPAA Safe Harbor anonymization and prevents sensitive re-identification mappings from being mishandled.

Core Features & Use Cases

  • Reversible de-identification: De-identify clinical text with a saved mapping and restore the original text through OpenMed's reidentify workflow.
  • Consistent pseudonyms: Use replacement surrogates with consistency controls and seeds so repeated identifiers remain analytically coherent.
  • Secure mapping guidance: Keep mappings separate from de-identified text, encrypt them at rest, restrict access, and audit authorized reversals.
  • Use Cases: Support patient recontact, clinical adjudication, record linkage, GDPR pseudonymization, reviewer spot-checking, and downstream analysis without sending data to the cloud.

Quick Start

Use the reidentifying-text skill to pseudonymize the supplied clinical note with a protected mapping and restore the original text only after authorized review.

Frequently Asked Questions about reidentifying-text

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reversibly pseudonymize clinical text while keeping protected health information secure?▼

Reversible pseudonymization of clinical text removes protected health information and stores it in a separate, encrypted mapping, allowing authorized users to restore the original content later for clinical adjudication or patient recontact.

What is the difference between GDPR pseudonymization and HIPAA Safe Harbor anonymization for de-identifying clinical text?▼

GDPR pseudonymization replaces identifiers with consistent surrogates while retaining a secure mapping for restoration, whereas HIPAA Safe Harbor anonymization irreversibly removes protected health information without any option to restore the original clinical text.

How do I restore de-identified clinical text after running a pseudonymization workflow?▼

To restore de-identified clinical text, authorized users apply a reidentify workflow using the securely stored mapping, which reverses the pseudonymization and reinserts the original protected health information into the clinical record.

Do I need OpenMed de-identification to use consistent replacement surrogates for clinical record linkage?▼

Yes, generating consistent pseudonyms for clinical record linkage requires OpenMed de-identification with mapping retention, applying consistency controls and seeds so repeated identifiers remain analytically coherent across downstream workflows.

What are the limitations of reversible de-identification for processing clinical text?▼

Reversible de-identification requires explicit separation from irreversible anonymization and demands secure mapping storage with restricted access and auditing, meaning mishandled mappings can compromise protected health information and fail compliance.

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