Today, artificial intelligence does something incredibly powerful but simple – the ability to connect data across the internet and synthesize it faster than a human can. We can type a simple prompt and get answers in near real-time.
And with all the progress in health data sharing, we find ourselves at an interesting juncture as AI grows more powerful. Many patients and providers rely on data systems to retrieve health information, so the natural use-case for health data sharing would be around health literacy helping patients understand their health status, or decision support, helping providers find the information they need quickly to make timely care decisions.
Rather than using AI to analyze data and expedite workflows, what if we used it to bolster the privacy and security of platforms that harbor sensitive health data?
Today, there are at least 200 healthcare organizations whose primary purpose is to mediate the electronic exchange of health information in the U.S. Ensuring the integrity and privacy of this information is not just a priority, but a fundamental human right. Networks that mediate data exchange must have best-in-class security programs.
Over the next few months, many healthcare organizations will be deploying AI-powered privacy features that were previously not feasible.
Anomaly detection: With AI, developers can build automated systems to monitor network activity and detect anomalies that might signify a cyberattack or a potential data breach. By learning what constitutes ‘normal’ activity, AI could identify unusual patterns or behaviors that deviate from the norm, triggering alerts for further investigation.
Predictive Analysis: Many AI models allow for predictive capabilities to anticipate potential security threats before they happen. Using machine learning algorithms, the AI can analyze historical data to identify patterns and trends associated with security incidents, enabling it to predict and prevent future attacks.
Automated Response: In the event of a cyberattack, AI can automate response actions, such as isolating affected systems or initiating backup protocols. This can significantly reduce response times, limiting the damage caused by the attack.
AI-Enhanced Encryption: To further safeguard data during exchange, AI can offer enhanced encryption techniques. This could involve dynamic encryption keys that change in real time, making it nearly impossible for unauthorized individuals to gain access.
AI-Powered Risk Assessment: Using AI, it becomes possible to assess the risk levels of different data requests or transactions based on various factors, such as the nature of the data, the recipient’s identity, and the security of the transmission channel. High-risk transactions could be autonomously flagged for additional security measures.
AI-Powered Security Training: AI-based chat functionality can integrate easily into internal security training programs to provide personalized guidance and assessments to personnel. By establishing rigor and AI-level intelligence into the training process, organizations can further reduce the risk of security incidents caused by human error.
With a technological revolution underway, now is the time to use AI advances to further protect patients. While most organizations can accommodate the security standards of today, the challenges of tomorrow must be anticipated. In today’s environment, staying still means falling behind. Especially in the health data community, to the industry has to be at the forefront of new technologies that offer outsized protections to consumers, and more importantly, build trust.