Healthcare organizations face the challenge of protecting sensitive patient information. From personal identities to medical histories, this data is a prime target for malicious actors seeking to exploit it for nefarious purposes. Fortunately, there are several data protection strategies available, each tailored to specific use cases and compliance requirements.
At the heart of healthcare data protection lies the distinction between two data categories: personally identifiable information (PII) and protected health information (PHI). PII refers to any data that could potentially identify a specific individual, such as names, contact details, or social security numbers. PHI, conversely, encompasses any information related to an individual's health status, healthcare provision, or payment for such services. Recognizing the unique characteristics and sensitivity of these data types is beneficial for implementing effective protection strategies.
The Health Insurance Portability and Accountability Act (HIPAA) privacy rule establishes national standards for protecting individuals' medical records and other personal health information. This regulation mandates that healthcare organizations, insurers, and certain service providers implement appropriate safeguards to preserve the privacy of PHI. The rule also grants patients specific rights over their health data, including the ability to access, review, and request corrections to their records.
One of the most advanced data protection methods is encryption, a process that scrambles sensitive information into an unreadable form. By applying different encryption keys to various data subsets, healthcare organizations can ensure that only authorized parties with the correct decryption keys can access the protected information. While encryption is a highly effective solution for safeguarding PHI, it does come with the challenge of managing a scalable key management system to support a diverse user community.
Tokenization is another powerful technique for protecting healthcare data. This method replaces sensitive information, such as patient names, social security numbers, or medical diagnoses, with non-sensitive placeholder tokens. These tokens are then stored in a secure database, while the original data is safely removed from operational systems. Tokenization offers the advantage of preserving data format and functionality while effectively obscuring the underlying sensitive information. However, the complexity of managing and tracking the various tokens issued for different audiences can present operational challenges.
Data masking, a complementary approach to encryption and tokenization, offers a unique solution for healthcare data protection. This technique scrambles individual data elements in a way that preserves the overall data format and statistical properties while rendering the original sensitive information unreadable. Masked data can be used for testing, development, or analytical purposes without compromising patient privacy. Data masking can be implemented either statically (in advance) or dynamically (in real-time), depending on the specific use case and compliance requirements.
Effective healthcare data protection strategies often combine encryption, tokenization, and data masking to address these challenges, each with its own strengths. Encryption is ideal for securing archived or file-based data, data masking supports safe sharing and analysis in production environments, and tokenization manages the complex network of personal, financial, and medical data associated with a patient’s healthcare journey. Healthcare providers can create a strong, layered defense against data breaches and unauthorized access by adapting these methods to their specific compliance needs.
Michalsons Legal Services states, “Data protection has a big impact on the healthcare industry. It treats information about the health, well-being, and sex lives of individuals as especially sensitive and lays down strict rules about how this information must be handled. At the same time, technology has made it much easier to lose, copy, steal, delete, or misuse large databases of sensitive information.”
Nicholas Kathmann, who has over 20 years of experience in IT, explains, “Healthcare’s ‘Golden Hour’ creates a unique opportunity for attackers. Healthcare organizations can modernize their approaches and adopt a ‘defense in depth’ strategy to avoid becoming easy targets.”
Nicholas uses a bank as a metaphor for network security, describing the need for segmentation. “Think of network segmentation like a bank. A burglar who manages to break in shouldn’t have the run of the place. Medical devices and patient intake systems need isolation to prevent attackers from moving laterally and reaching sensitive data.”
He also points out that healthcare’s high volume of connections requires more than standard security solutions. “Streamlining patient care processes while adding protections around data-oriented systems allows healthcare organizations to avoid disruptions without sacrificing security.”
Data protection refers to the practices and technologies used to safeguard sensitive information from unauthorized access, loss, or corruption. In healthcare, data protection involves securing protected health information (PHI) and electronic protected health information (ePHI) to ensure patient privacy and comply with HIPAA regulations.
Learn more: HIPAA Compliant Email: The Definitive Guide