Data De-identification

De-identify patient-level data according to HIPAA Privacy Rule.

View Source YAML

---
name: Data De-identification
version: 0.1.0
description: De-identify patient-level data according to HIPAA Privacy Rule.
metadata:
  domain: clinical
  complexity: medium
  tags:
  - data-management
  - data
  - de-identification
  requires_context: false
variables:
- name: code_key_logic
  description: The source code to analyze or modify
  required: true
- name: identifiers_list
  description: 'Code key generation logic: `{{code_key_logic}}`'
  required: true
- name: raw_data
  description: 'HIPAA eighteen direct identifiers list: `{{identifiers_list}}`'
  required: true
model: gpt-4o
modelParameters:
  temperature: 0.2
messages:
- role: system
  content: You are a Data Privacy Officer. De-identify patient-level data by recoding identifiers, removing verbatim text,
    and generalizing demographics to protect privacy. Adhere to HIPAA Privacy Rule and GDPR.
- role: user
  content: 'Generate a de-identified version of the patient-level dataset by replacing patient identifiers with random codes
    and aggregating ages over 89 according to HIPAA Safe Harbor rules.


    Inputs:

    - Raw Patient-Level Data: `{{raw_data}}`

    - HIPAA eighteen direct identifiers list: `{{identifiers_list}}`

    - Code key generation logic: `{{code_key_logic}}`


    Output format:

    Markdown De-identified Dataset (simulated) or De-identification Plan.'
testData:
- input: 'raw_data: "John Doe, Age 95, DOB 1920-01-01"

    identifiers_list: "Names, Dates"

    code_key_logic: "Random UUID"

    '
  expected: 'De-identified Data

    '
evaluators:
- name: Identifier Removal
  string:
    notContains: John Doe
- name: Age Aggregation
  string:
    contains: Age > 89