PHI Redaction: Protecting Sensitive Health Information for Compliance and Security

TL;DR:

• Protecting Protected Health Information (PHI) is crucial for compliance and preventing data breaches.
• Automated redaction tools like Strac detect and redact sensitive information across various platforms.
• Examples of PHI that may need redaction include personal identifiers, medical identifiers, dates, and other identifiers.
• Real-world examples of PHI redaction across platforms like customer support, collaboration tools, email systems, and cloud storage are provided.
• Strac integrates with platforms to detect and redact PHI in real-time, ensuring compliance and enhancing security.

Protecting Protected Health Information (PHI) is critical for ensuring compliance and preventing data breaches. With the proliferation of communication and collaboration platforms like Zendesk, Slack, Teams, Google workspace, O365, AWS, Azure, Salesforce, Jira/Confluence and email systems, PHI is often inadvertently shared in various channels. To address this challenge, automated redaction tools such as Strac ensure that sensitive information is detected, redacted, and securely managed.

In this blog, we focus on how PHI redaction applies to cloud storages, customer support platforms, communication tools, and email systems, providing real-world examples and solutions

What is PHI Redaction?

PHI redaction refers to the process of identifying and removing or obscuring sensitive information in a document to ensure it cannot be used to identify an individual. Redaction ensures that sensitive data remains secure when shared, stored, or archived.

Examples of PHI That May Need Redaction:

• Personal Identifiers: Names, addresses, Social Security Numbers (SSNs), and phone numbers.
• Medical Identifiers: Medical record numbers, health plan beneficiary numbers, and account numbers.
• Dates: Birthdates, admission/discharge dates, and treatment dates.
• Other Identifiers: Photos, biometric identifiers, and full-face images.

The PHI Deidentification Challenge

The challenge with PHI lies in the need to balance privacy and utility. While it is critical to protect patient privacy by deidentifying their health information, the deidentified data must still retain enough utility for essential tasks such as health research, quality assurance, and clinical studies. This challenge is amplified by the increasing volume and complexity of health data being collected, and the growing number of services that touch this data.

Real-World Examples of PHI Redaction Across Platforms

1. Customer Support Platforms Like Zendesk, Salesforce, Intercom, HubSpot

Scenario:

A patient submits a support ticket containing PHI, such as their name, medical record number, or treatment details.

Challenges:

• Support agents handling the ticket can inadvertently access sensitive data.
• Sharing or storing the ticket may expose PHI.

Solution:

Strac integrates with customer support tools to automatically scan support tickets for PHI and redact it before agents access the ticket. Sensitive information such as patient names and medical record numbers is replaced with placeholders (e.g., "Patient [REDACTED]").

Result:

• Agents can focus on resolving the issue without exposure to PHI.
• Tickets remain compliant with HIPAA regulations.

2. Collaboration Tools Like Slack, Teams

Scenario:

A healthcare provider's team discusses patient cases in Slack channels, where PHI like diagnosis details or appointment dates may be shared.

Challenges:

• Slack messages are not inherently secure for PHI.
• Sensitive data can persist in message history, increasing the risk of breaches.

Solution:

Strac integrates with Slack to detect and redact PHI in real-time. If a message contains sensitive information, it is immediately flagged and redacted. For example, a message like:

"John Doe's MRI results show a positive diagnosis"

is automatically transformed into:

"Patient [REDACTED]'s MRI results show a positive diagnosis."

Result:

• Teams can collaborate securely without risking sensitive data exposure.
• Redacted data ensures compliance while retaining context for communication.

3. Email Systems (e.g., Office 365, Gmail)

Scenario:

A doctor emails a lab report containing PHI to a colleague or external partner.

Challenges:

• Email attachments and body content may expose PHI.
• Misaddressed emails or unauthorized access can lead to breaches.

Solution:

Strac integrates with email systems like Office 365 and Gmail to scan both email content and attachments. PHI is detected and redacted automatically before the email is sent. For example:

• A lab report PDF is scanned, and patient identifiers are masked.
• An email body stating:
• "Patient Jane Doe's appointment is on 12/12/2024"
• is transformed into:
• "Patient [REDACTED]'s appointment is on [REDACTED]."

Result:

• Emails are compliant with HIPAA and secure for sharing.
• Organizations avoid unintentional PHI disclosures.

4. Cloud Storage Platforms Like SharePoint and Google Drive

Scenario:

A healthcare organization stores thousands of files in SharePoint and Google Drive containing sensitive patient data, including scanned medical records, test results, and discharge summaries. These files are often shared externally for collaboration or internally for team access.

Challenges:

• PHI is scattered across folders and files, often unnoticed by administrators.
• Shared links might inadvertently grant access to unauthorized users.
• Manual review and redaction are impractical for the volume of data stored.

Solution:

Strac integrates with SharePoint and Google Drive to perform real-time and historical scanning of all files for PHI. Detected PHI is automatically redacted or flagged for admin review.

For example:

• A scanned PDF report in Google Drive containing patient details is processed by Strac’s OCR capabilities to detect text embedded in images, and PHI is masked before the file is shared.
• Shared links in SharePoint are monitored, and files with sensitive data are automatically marked as "Restricted Access."

Result:

• Secure collaboration within and outside the organization.
• Reduced risk of accidental data exposure through publicly accessible links.
• Compliance with HIPAA and other data privacy regulations.

5. Collaboration Tools Like Jira, Confluence, and Notion

Scenario:

Healthcare teams document projects, tasks, and patient-related workflows in Jira, Confluence, and Notion, where PHI such as patient names, medical histories, or diagnoses might be logged.

Challenges:

• Sensitive data can appear in tickets, project descriptions, or shared documents without users realizing the compliance risk.
• Collaboration across multiple teams increases the likelihood of data leaks.

Solution:

Strac integrates with Jira, Confluence, and Notion to scan tasks, tickets, and pages for PHI. Redaction occurs in real-time to ensure compliance without interrupting workflows.

For example:

• In Jira, a ticket containing a medical record number (e.g., “MRN: 123456”) is flagged and redacted before it is saved.
• In Confluence, sensitive text within meeting notes or project documentation is identified and replaced with placeholders.
• In Notion, free-form notes with PHI are scanned and modified during content creation, preventing the storage of unredacted sensitive information.

Result:

• Teams can collaborate effectively without risking compliance violations.
• Data in tickets, notes, and documents remains secure and compliant.
• Centralized monitoring ensures that no PHI slips through unnoticed.

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How PHI Redaction Works Across Platforms

Automated redaction tools like Strac work seamlessly across various platforms to detect and redact PHI. Here’s how:

1. Detection

Using machine learning (ML), natural language processing (NLP), and contextual analysis, Strac identifies PHI within text, images, and metadata.

2. Redaction

Sensitive information is automatically redacted from the platform’s content. This can include:

• Text replacement (e.g., masking SSNs).
• Image redaction (e.g., blurring sensitive areas).
• File redaction (e.g., removing PHI from PDF attachments).

PHI Redaction: Strac powered Document Redaction

3. De-Identify PHI Data in Databases

Strac will work with any database (Relational database or NoSQL Database) and can mask, tokenize or redact sensitive data in databases. Learn more about here: https://www.strac.io/integrations/postgres-data-masking

4. Strac API

Checkout our API Docs at https://docs.strac.io to learn how you can protect sensitive PHI data.

Benefits of Automated PHI Redaction with Strac

1. Comprehensive Detection: Strac’s ML/NLP models ensure accurate identification of PHI in structured and unstructured data.
2. Seamless Integration: Supports platforms like Zendesk, Slack, Office 365, Gmail, and more for real-time and bulk redaction.
3. Scalability: Processes large volumes of data across multiple platforms effortlessly.
4. Compliance: Ensures adherence to HIPAA and other regulations.
5. Enhanced Security: Prevents sensitive data from being exposed, reducing breach risks.

To learn more about Strac's tokenization, redaction, and masking solutions, book a demo.

Conclusion

PHI redaction is vital for securing sensitive health information in today’s multi-channel environment. Platforms like Zendesk, Slack, and email systems are integral to healthcare operations, but they require robust redaction tools to protect patient privacy and maintain compliance. With Strac, organizations can automate PHI redaction across platforms, enabling secure and efficient data handling while reducing the risk of compliance violations.