Remember when artificial intelligence seemed like something out of a movie? Like computer-generated imagery (CGI), it conjured up images or scenarios that certainly couldn’t occur in real life. 

These days, artificial intelligence, commonly referred to as AI, is prevalent in almost every industry. Healthcare might be a little late to the party, but it’s rapidly catching up. 

Roughly 94 percent of healthcare businesses utilize AI or machine learning in some capacity, and 83 percent of healthcare organizations have implemented an artificial intelligence strategy. It’s not simply for improving workflow processes, though. Almost 60 percent of United States healthcare executives believe that AI is effective at improving clinical outcomes. 

Not everyone is 100 percent on board with AI, though. Some physicians and patients have concerns about privacy and security of the technology. That apprehension is valid, which is why it is crucial for healthcare organizations using AI to put stringent measures in place to mitigate any risks of exposing protected health information (PHI) and other patient data. 

How are Advanced AI-driven Solutions Used in Healthcare? 

AI solutions are used to deliver scalable and less costly patient communication that can provide help at any time via phone or SMS. As we mentioned in a previous blog, AI is a broad term that encompasses different facets. LLMs, or large language models, communicate with patients through natural language user interfaces involving images, text and voice. Conversational AI automates more natural, human-like conversations between trained AI agents and patients. 

By combining advanced automation, artificial intelligence and natural language processing to enable comprehension of and response to human language, healthcare providers can use conversational AI to respond to common patient questions and streamline some administrative tasks. It achieves this by generating clear answers that mimic human interaction and asking follow-up questions if necessary.  

Some applications of conversational AI in healthcare consist of:

  • Appointment scheduling and reminders
  • Symptom assessment and triage
  • Performing patient navigation to schedule and complete recommended care 
  • Conducting post-discharge follow-up
  • Patient education
  • Medication reminders and adherence tracking
  • Communicating lab prep education
  • Providing guidance on self-care
  • Retrieving basic billing information
  • Answering common patient questions about symptoms
  • Telemedicine and remote consultations 
  • Multilingual support 

Key Privacy Concerns with AI in Healthcare 

To train and improve artificial intelligence applications and models, including conversational AI, large data sets are required. Often, that includes PHI, which is one of the most private and legally protected forms of data

It’s not surprising, then, that approximately 40 percent of physicians are concerned about AI’s impact on patient privacy. There is a risk of biases and flawed algorithms, both of which have the potential to create unsatisfying patient experiences. 

Healthcare organizations implementing a conversational AI solution must ensure that they follow industry best practices such as not storing patient data within the large language model (LLM) and developing a strategy that avoids these security and policy-associated problems: 

Unauthorized Access and Use of Sensitive Patient Data 

HIPAA requires that healthcare organizations and their business associates safely manage who has the privilege and/or right to access, change or distribute sensitive health data. Unauthorized access or improper handling of patient data can result in HIPAA fines and penalties — civil and criminal — along with costly breaches, a damaged reputation and lost patient trust. 

Access to PHI should be limited to only the amount of information necessary to perform a job. It is up to each covered entity to determine which access controls, software and systems they employ to manage authorized access to PHI used in conversational AI. 

Each employee with access to PHI should be adequately and regularly trained on security protocol. Some healthcare organizations utilizing AI maintain audit logs that record access to patient data, a process that verifies that only authorized entities are accessing PHI. 

By deploying stringent access control measures, only authorized personnel with specific roles can access sensitive data. Regular audits ensure these access rights are continually evaluated and updated as necessary.

Re-Identification and the Limitations of De-Identification Protections  

Before patient data is entered into third-party databases, certain information as required by the Safe Harbor provision of HIPAA must be removed to de-identify it. According to HHS, this is information “that identifies the individual or for which there is a reasonable basis to believe it can be used to identify the individual.” Aside from demographics, examples include clinical notes, test results and pathology reports. 

Deidentified patient data used for AI training may still be vulnerable to re-identification attacks. Although there is an extremely low risk of a data breach with this type of information, it can occur when it is shared without proper controls. 

AI-driven systems should be designed to ensure healthcare organizations utilizing conversational AI never store PHI unnecessarily. This “touch-and-go” method allows them to access necessary information without retaining sensitive data, further reducing potential risk points.

Lack Of Continuous Improvement

Threats to patient data and the security tools necessary to mitigate them change, and it’s essential for healthcare organizations to keep up with those trends. Even IT experts must proactively learn about emerging security risks to be better prepared for them in the future.

Along with regular security audits, healthcare organizations employing conversational AI should continually monitor system performance and user interactions and identify any discrepancies or potential vulnerabilities detected back into their system for remediation. Also, any systems used for accessing external systems without storing PHI should always be updated with the latest security patches.

Data Breaches and Cyberattacks 

Breaches are increasing throughout healthcare, with the most reported data breaches and the most breached records occurring in 2023. Last year, 725 data breaches were reported to the Office for Civil Rights (OCR), and more than 133 million records were exposed or impermissibly disclosed. 

Cyberattacks and the mishandling of PHI, whether intentional or not, can result in those hefty HIPAA violations, patient and provider dissatisfaction and even legal repercussions. The average cost of a healthcare data breach is the highest among all industries at $10.93 million. 

Every piece of data in transit or at rest should be encrypted using industry-leading methods. Healthcare organizations should only utilize data centers and storage facilities that are fortified with state-of-the-art security protocols. 

Also, regular backups ensure that healthcare data is never lost. These backups, encrypted and stored securely, ensure data recovery options are always available without compromising security.

Strategies for Mitigating AI Privacy and Security Risks 

Healthcare organizations utilizing conversational AI and other types of artificial intelligence in their operations must proactively develop, implement and maintain strict security measures. They must ensure robust data governance, employ stringent guidelines for sharing of PHI and continuously monitor the efficacy of such safeguards. 

As HITRUST notes, robust encryption methods secure patient information during data storage, transmission and processing to protect information from unauthorized access. Healthcare organizations need to embrace strategies that not only mitigate risks but also cultivate a culture of data responsibility and ethical data management. 

Other strategies for ensuring privacy and security through AI tools include:

  • Consistently assessing data practices and evaluating compliance with stringent regulations like HIPAA
  • Training healthcare staff on AI privacy and security best practices
  • Securing networks connecting patients with their care and any external access points
  • Involving third-party experts to conduct independent audits and assessments of your AI systems to identify vulnerabilities and provide unbiased feedback 

Implementing Providertech’s HIPAA Compliant Conversational AI Tool 

At Providertech, our conversational AI solution for patient engagement is designed to understand the way patients communicate and adapt accordingly. And, it promotes patient engagement by meeting healthcare consumers’ expectations for a seamless experience. 

We understand the importance of HIPAA compliance and security measures with advancing technology and are committed to maintaining the highest standards in healthcare data management. Call 540-516-3602 to start your interactive demo of this solution using test patient Sara Morales D.O.B. 7/20/81.