Healthcare institutions have been increasing their investments in both preventive and reactive cybersecurity solutions due to the ever-changing threat landscape. It is estimated that the healthcare industry will spend approximately $125 billion on security measures between 2020 and 2025.
Despite these efforts, the U.S. Department of Health and Human Services Office for Civil Rights (OCR) regularly investigates numerous reported breaches of unsecured protected health information, with a significant portion of compromised patient data originating from network file servers.
These breaches come with severe financial, operational, regulatory, and reputational consequences. According to a 2023 IBM report, the average cost of a healthcare data breach has surged to almost $11 million and continues to rise, largely due to hacking incidents, including ransomware attacks, as documented by the OCR.
Healthcare organizations are particularly vulnerable to cyberattacks because of the potential impact on critical life-saving operations. A 2022 report by the Ponemon Institute and Proofpoint, based on surveys of healthcare IT and security professionals, highlights negative patient outcomes as a major consequence of these cyber incidents.
It’s evident that the traditional approach to healthcare cybersecurity is insufficient in mitigating the impact of cyberattacks on this vital industry. One primary reason is that healthcare data, which requires protection, is not easily identifiable or locatable using existing technologies.
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How Hospitals Can Gain Visibility Into Their Data
Without a clear understanding of the location and characteristics of their data, organizations cannot effectively secure it. Locating patient information within an organization is a complex task that often necessitates programming skills.
Outdated technologies reliant on rules-based pattern matching for identifying protected health information are challenging to configure correctly and are no longer adequate for safeguarding healthcare organizations from their most significant risks.
Fortunately, advancements in artificial intelligence are driving solutions to identify and catalog electronic protected health information (ePHI). Deep learning empowers AI models to emulate the capabilities of trained humans in recognizing ePHI, eliminating the need for arduous programming and constant refinement of search patterns and detection rules. This outdated approach restricts organizations aiming to scale their security efforts.
How Hospitals Can Meet Better Standardization and Compliance
The National Institute of Standards and Technology (NIST) offers guidance and resources for implementing security measures in compliance with the HIPAA Security Rule. This rule aims to enhance patient data protection and reduce the impact of cyberattacks by securing ePHI held or managed by HIPAA-regulated entities.
According to NIST 800-66r2, “The ePHI that a regulated entity creates, receives, maintains, or transmits must be protected against reasonably anticipated threats, hazards, and impermissible uses and/or disclosures.”
The document provides updated and essential implementation guidance for HIPAA-regulated entities to proactively safeguard patient data and manage ePHI-related risks. As the industry standard for best practices, NIST 800-66r2 directs organizations to have an incident response plan for all areas where ePHI is used, stored, or shared.
The initial step toward achieving this is identifying all the locations and repositories of ePHI, including those obscure corners where it might be stored. Healthcare organizations can’t protect what they can’t see, so the first priority is to identify and catalog ePHI to shield it from cyberattacks. This is where a unified cloud-native application protection platform can prove invaluable.
Healthcare organizations looking to modernize their cybersecurity approach should consider adopting an AI-powered data security platform to assist in identifying and cataloging ePHI. Traditionally, this process has been cumbersome due to the unstructured nature of over 80 percent of healthcare data.
By leveraging AI-powered solutions, healthcare organizations can efficiently manage and identify ePHI, thereby reducing risks and cutting costs. Those who have embraced such solutions report decreased vulnerability to cyberattacks, reduced resource requirements for data management, and lower cyber insurance premiums.
