The Ethical Implications of AI-Driven Patient Engagement

In this Pharmaceutical Executive video interview, Bill Grambley, CEO of AllazoHealth, delves into the potential of AI to revolutionize patient engagement and adherence. By utilizing patient-level data and predictive modeling, AI can identify individual needs and preferences, tailoring interventions to optimize treatment outcomes. This personalized approach addresses the common challenges of medication non-adherence and improves patient outcomes. The discussion highlights the importance of ethical considerations and data privacy when leveraging AI in healthcare. By focusing on patient well-being and using AI responsibly, healthcare providers can significantly enhance patient experiences and improve overall health outcomes.

What are the ethical implications of using AI to collect and analyze patient data? How are pharmaceutical companies ensuring patient data privacy and security while leveraging AI to improve outcomes?

So, I think it's really important to keep focused on what is the outcome you're supporting and what we've talked about and what a lot of health does, and what we see in the in the industry is using AI to collect and analyze patient data is appropriate where you have permission, and you're really focused on that medication journey. And occasionally you'll see headlines about things that aren't in that direction, right? They didn't have permission, or they're not really focused on that journey. In the programs we support, patients affirmatively opt in. So, they are saying to the companies that we support, I want you to outreach to me. I want you to use my data to make that experience better. I want you to support me with that kind of opt in.

Now, organizations like the pharma company or vendors like ourselves can use that data and use AI on that data to now understand how can we support them on their journey. Now, obviously we need to be highly precise about protecting that data, having security around that data, making sure that any kind of legal requirements, governance data use, all of that is highly precise. Within our environments we use. It's built within Microsoft Azure. We have fully HIPAA compliant, high trust certified; all of these things start to provide assurances that we're using that data appropriately. And I will go back to just focusing on the outcome.

So, there are lots of ways that you could use data inappropriately, but if you're focused on supporting the patient, you know, and again, in these programs. Sometimes a doctor has decided this is the right medicine, and we're trying to support that patient to get that medicine and stay on that medicine. So, in that vein, and with the right permissions, we can use this data, and we avoid some of the ethical concerns that you might hear about in the industry.