The healthcare industry is particularly vulnerable to cybersecurity threats due to the valuable data it processes; Protected Health Information (PHI) is among the most sensitive and valuable data in existence. As the past few years have shown, the consequences of a breach can be costly and, in the most severe cases, impact patient care, highlighting the critical need for standardized industry practices and regulations to uphold accountability.
Organizations often develop their cybersecurity measures internally since legislative direction has been limited and typically is written to be flexible and technology-agnostic. Seeing this gap, several groups are attempting to establish the most robust industry standards for healthcare organizations to improve security and privacy. For the first time since 2013, the U.S. Department of Health and Human Services (HHS) drafted a proposal to modify the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Security Rule with the goal of strengthening cybersecurity protections for electronic protected health information (ePHI). The most significant change proposed by HHS in their Notice of Proposed Rulemaking (NPRM) is the reclassification of certain security controls from being merely suggestions to now being absolutely mandatory. Included in this is multi-factor authentication (MFA), signaling a significant shift from the previous HIPAA verbiage, which was flexible and adaptable based on an organization’s size and focus.
It remains uncertain whether HHS’ proposal will be enacted. However, it has already prompted a wave of additional regulatory initiatives in the healthcare sector, including the Artificial Intelligence in Health Care Services Bill and the Health Care Cybersecurity and Resiliency Act of 2024.
Navigating the Current Landscape: Security of Artificial Intelligence
Healthcare’s extensive collection of sensitive data makes it especially vulnerable to cyberattacks. As the industry continues to embrace new digital technologies, specifically artificial intelligence (AI), data processing and sharing will increase in speed and volume. Therefore, incorporating standard security measures to control the hazards related to digital growth will be paramount.
A recent McKinsey & Company report revealed that despite a strong desire to increase AI investments and accelerate development, many leaders are wrestling with making AI safe in the workplace. Core challenges include data security, AI hallucinations, biased outputs, and potential misuse. Similarly, employees’ top concerns revolve around cybersecurity, privacy, and accuracy.
These security challenges and concerns make many businesses and employees hesitant to adopt AI. However, healthcare companies should not shy away from this advancement, as AI is rapidly becoming an effective way of delivering optimal patient care.
Leaders who are worried about AI should focus on allowing for incremental adoption in their businesses. A phased rollout of AI software can help healthcare organizations reduce hesitancy while still upholding security and privacy. A practical approach is to initially grant AI software licenses to a small group of employees for testing and evaluation. Once the software is deemed secure and free of critical vulnerabilities, a phased rollout to larger groups can be implemented.
Additionally, to balance progress with caution, organizations must establish clear guidelines for AI adoption, enabling innovation without compromising data integrity or patient trust.
Safeguarding Technology from the Start: Code Scanning
One of the most effective ways to secure technology and protect sensitive data is by implementing the proactive safety measure of code scanning. Before deploying software, organizations should thoroughly examine source code for potential vulnerabilities that could be exploited. Healthcare organizations should utilize reputable code-scanning tools to detect weaknesses during development and filter critical vulnerabilities to development teams for immediate remediation. Identifying and fixing vulnerabilities early in the development process allows for a more secure launch of applications to protect patient data, providing both security and data privacy for each individual utilizing healthcare software.
Staying Ahead of Emerging Threats
As healthcare organizations scale, adopting proactive cybersecurity measures will be essential to safeguarding patient data and maintaining trust. Emerging technologies like AI and the growing volume of sensitive data emphasize the need for prompt implementation of standardized security practices. To align with these standardized security practices, healthcare organizations should closely monitor emerging regulations to understand and implement the necessary enhancements to stay compliant.
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