Humberto Farias has been following the explosive growth of generative AI very closely.
Mr. Farias is co-founder and Chairman of Concepta Technologies, a technology company specializing in software development and programming in the areas of mobile, web, digital transformation and artificial intelligence.
For example, he noted that Apple has put generative AI at the center of the lives of hundreds of millions of iPhone-owning people, but he worries that recent data breaches, patient privacy concerns and other IT issues will make health IT teams more likely to view AI as a threat rather than a tool.
The question is, how can health systems reap the benefits while protecting valuable patient data? What are the benefits of generative AI?
Farias launched the Concepta Machine Advancement and General Intelligence Center (MAGIC), a collaborative research program, virtual incubator and service center for artificial intelligence and advanced technologies.
Healthcare IT News We recently spoke with Farias to learn more about MAGIC and understand the concerns he hears from healthcare CTOs about adopting artificial intelligence. Farias provided tips and examples for securely adopting AI and learning, and outlined key focuses for hospital and health system CIOs, CISOs, and other security leaders as AI and machine learning continue to transform healthcare.
Q. Tell us about your new organization, MAGIC. What are its goals?
A. Our mission is to push the boundaries of AI research and development while providing practical applications and services that address real-world problems. At MAGIC, we aim to foster cutting-edge research on both fundamental technologies and applied solutions, support and nurture early-stage AI ventures, educate and train experts in AI skills, provide consulting services, and build collaboration networks.
Our first partnerships include healthcare companies committed to improving healthcare for patients, hospitals and clinical teams. They combine assessment, analytics and education, and measure it all to improve healthcare for everyone. Through our partnerships, we Implementing AI can help your team run their programs more efficiently and cost-effectively.
We are actively collaborating with large health systems on some of the key issues they face when it comes to adopting AI. We work with health systems like Advent Health on other software technologies and are well-positioned to address the unique regulatory and patient security issues facing healthcare.
Q. What are some of the concerns you have heard directly from CTOs in the healthcare industry about implementing AI into their business structures?
A. When we hear from CTOs in the healthcare industry, their biggest concern regarding the implementation of AI in their business structure remains data privacy and security. Given the stringent restrictions imposed by HIPAA and other regulations, healthcare executives want to make privacy and security of sensitive patient data a top priority.
There is also hesitation about how AI solutions can be integrated with legacy systems, whether they are compatible, and how to navigate the complex regulatory environment to ensure that AI solutions comply with all relevant laws and guidelines.
It also costs money More companies are adopting AI, but many healthcare CTOs are unsure of the return on investment this technology will bring. I am always looking for ways to reduce costs by collaborating with my colleagues and working outside of silos – learning from our mistakes and building on the success of other leaders in our industry.
Additionally, there is a shortage of skilled talent to develop, implement, and manage AI systems. Healthcare systems are already under strain and facing cuts, so partnering with AI research programs can help fill this need and advance the use of AI across the institution.
We work to educate health systems on how to leverage AI for simple things like minimizing repetitive administrative tasks, as well as larger projects that can improve provider workflow and actual patient care.
Finally, there are always ethical concerns when it comes to AI, and healthcare CTOs want to ensure that AI is used ethically, especially in decisions that directly impact patient care. The biggest concerns in this area are informed consent and data bias.
Patients need to be aware that AI is part of their care and ensure that the data used to train AI algorithms does not lead to biased medical decisions that exacerbate disparities in health care outcomes among different demographic groups.
Q. Can you give us some tips or real-world examples on how to deploy AI safely and securely, especially with sensitive healthcare data in mind?
A. There are several ways healthcare leaders can deploy AI safely and securely, one of which is data encryption. It is important to always encrypt sensitive healthcare data, both across networks and when stored in systems of record, to protect against unauthorized access.
Another tip is to implement robust access control mechanisms to ensure that only authorized personnel have access to sensitive data. Large medical centers should have multi-factor authentication, role-based access control, and 24/7 monitoring systems in place. Conducting regular security audits is another way to ensure security and safety by continuously monitoring to quickly detect and respond to potential threats.
Regulating compliance is another tip to ensure trust. To do this, Align your AI adoption with regulatory frameworks like HIPAA and GDPR. Prioritize the development and adherence to ethical guidelines for the use of AI, with a focus on fairness, transparency, and accountability, is another tip.
For example, Stanford Health Care has an ethics committee that reviews AI projects for potential ethical issues.
Q. As AI continues to explode in healthcare, what do you think should be the primary focus for CIOs, CISOs and other security leaders at hospitals and health systems?
A. As the use of AI in healthcare is inevitable, a primary focus for CIOs, CISOs, and other security leaders will be to ensure ongoing data privacy and security and protect patient data from breaches. A top priority will be ensuring programs are compliant with regulations.
Healthcare leaders must also focus on developing a scalable, secure IT infrastructure that can support AI applications without compromising performance or security. Then, to support this system, provide ongoing training to all levels of staff, from staff to providers to executive leadership, on the latest AI technologies and security practices to mitigate the risks associated with human error.
To ensure a fail-safe plan is in place, healthcare leaders must develop and maintain a comprehensive risk management strategy that includes regular assessments, incident response plans, and continuous improvement.
Collaboration is key to creating the best teams capable of meeting the challenges of the world we live in, and we foster collaboration between IT, security, and clinical teams to ensure AI solutions meet the needs of all stakeholders while maintaining security and compliance standards.
The HIMSS AI in Healthcare Forum is scheduled to take place in Boston from September 5 to 6. Learn more and register.
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