Summary

  • HIPAA mandates that covered entities enhance safeguards as needed to limit unnecessary or inappropriate access to and disclosure of protected health information.
  • This is proving difficult as most healthcare data is stored in either semi-structured or unstructured formats that traditional data redaction tools can’t read.  
  • NLP is able to mine through unstructured data with high degrees of precision.
  •  It can quickly and accurately discover evidence of PHI in vast amounts of data, and then redact this information to avoid HIPAA non-compliance.
  • Polymer DLP uses NLP technology to seamlessly and intelligently redact unstructured, in-motion PHI across collaboration apps.

The Health Insurance Portability and Accountability Act (HIPAA) consists of several rules that HIPAA-covered entities must follow to protect the confidentiality, integrity and availability of protected patient health information (PHI). 

One such rule, which we will focus on today, is the mandate to “enhance safeguards as needed to limit unnecessary or inappropriate access to and disclosure of protected health information.” 

In other words, covered entities must ensure that PHI is only accessed by, and shared with, healthcare professionals on a need-to-know basis. The rule makes sense in theory. After all, PHI is an extremely lucrative prospect to malicious actors, who can use this data as the basis for sophisticated scams and identity theft. 

However, protecting PHI from unlawful disclosure is proving difficult in practice. As research shows, more than 45.7 million patient records were affected by major healthcare data breaches in 2021. 

Not all of these incidents relate to data theft. In fact, more often than not, data exposure occurs internally, or between an organization and a third party. 

It’s easy to see why this happens. The rise of cloud apps like Slack and Teams have made it easier than ever for healthcare professionals to share resources with their peers. At the same time, research and development teams are harnessing the power of artificial intelligence and data analytics to supercharge their predictions. But PHI data fields are often, unlawfully, included.  

The innovation vs security deadlock in healthcare 

It is scary to think that many healthcare organizations are currently at odds with HIPAA compliance. However, this is undoubtedly the case. At the moment, most healthcare data is stored in either semi-structured or unstructured formats, containing several data fields that include PHI. 

Often, researchers and other healthcare professionals want to access non-confidential information within these documents. But their inherent format makes this data challenging to redact with traditional data loss prevention (DLP) tools. 

This leaves many healthcare providers in a tricky situation: do they forgo security so that their teams can access the information they need, or do they sacrifice innovation, and possibly even the quality of care they deliver, in order to uphold compliance? 

While it used to be a case of choosing one or the other, advances in natural language processing (NLP) mean that covered entities now have the opportunity to uncover vital clinical data while also maintaining HIPAA compliance. 

What is NLP?

Natural language processing is a fast-developing subset of artificial intelligence that gives computer systems the ability to understand and analyze the human language in both written and verbal formats. 

These amazing tools are made up of neural networks that analyze human language, syntax and grammar in real-time and at lightning speed. Best-in-breed solutions within this arena feature self-learning capabilities, which allow the NLP model to self-develop and improve based on new data, without further input from their creator. 

While NLP sounds extremely futuristic, you’ve probably already interacted with NLP tools without even knowing. If you’ve ever used an Alexa or Siri, or interacted with a customer service chatbot, you’ve used NLP. 

But this is just NLP within the consumer space. It also has extremely promising use cases within healthcare and compliance. 

NLP: The secret to compliant innovation in healthcare 

As we’ve mentioned, covered entities face a few obstacles to information sharing and R&D due to HIPAA, which mandates the protection of PHI from unlawful or unpermitted disclosure. The law also notes, however, that healthcare professionals can share resources should PHI be de-identified or obfuscated within a document. 

De-identification and obfuscation refer to the processes of redacting PHI from documents and data sets. De-identified data no longer falls under HIPAA as it is not thought of as PHI and there is no risk of exposure. 

So far, the problem for covered entities has been implementing de-identification at speed and scale—and reliably. Healthcare organizations are sitting on vast pools of valuable— but unstructured—medical data. Unstructured data is notoriously difficult to sort with traditional tools, and even more cumbersome to tackle manually. 

This is because unstructured data tends to be extensive, lengthy and complex. Plus, there are often variations in language, as people take notes and reference terms in different ways. All of these factors make obfuscating healthcare a near-impossible task. That is, unless you use an NLP tool.  

While older tools may find unstructured data challenging to read accurately, NLP is able to mine through unstructured data with high degrees of precision. It can quickly and accurately discover evidence of PHI in vast amounts of data, and then redact this information to avoid HIPAA non-compliance.

Polymer NLP For HIPAA

In today’s digital age, NLP is critical to achieving HIPAA compliance, and also offers fantastic cost-saving potential to covered entities. Analysis shows that AI applications in healthcare could create $150 billion in annual savings for the United States healthcare economy by 2026.

However, implementing it isn’t always easy. These tools become more accurate the more data they are fed. But many healthcare organizations don’t have the internal resources to decipher HIPAA texts in a way that NLP machines find useful. 

Polymer DLP has recognized this challenge. Now, we’re revolutionizing HIPAA compliance with our NLP-powered compliance tool. 

Polymer DLP is designed with HIPAA-specific templates that get to work the moment you install our software. Harnessing the power of NLP, our tool seamlessly and intelligently redacts unstructured, in-motion PHI with contextual awareness across dozens of collaboration apps, including Slack, Github, Dropbox and Teams.

With Polymer DLP, you’ll no longer have to choose between compliance or information sharing. You can achieve both in tandem, with a tool that works silently and efficiently to uphold data security and HIPAA rules in the background of your cloud apps.

Start your NLP journey today. Request a free demo.

Polymer is a no-code data loss prevention (DLP) platform that allows companies to monitor, auto-remediate, and apply behavioral techniques to reduce the risk of insider threats, sensitive data misuse, and leakage over third-party SaaS apps. Try Polymer for free.

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