There's been no shortage of chatter in Pharma and Life Science circles surrounding generative AI and data privacy, with many organizations seeking guidance on where to begin when it comes to tackling this emerging opportunity.
Recently, Pat McGloin, MERGE Chief Client Officer and Life Science Practice Lead, sat down with Joo Lee, MERGE EVP and Chief Architect, for a focused Q&A to discuss the state of AI and data in healthcare, and the need for organizations to better understand it to ensure patient privacy.
Pat McGloin: Joo, thanks for sitting with me today to discuss this exciting topic. From your perspective, given the growing focus on AI and its potential intersection with regard to data privacy and ethics, how should organizations think about where to begin leveraging an AI driven patient adherence program?
Joo Lee: So first, I think if we zoom out, AI absolutely has transformative potential that we have not seen since the mobile phone. But with that and a lot of the technology waves that we've seen over the course of the past 10 years, there's a land grab that occurs with an awful lot of people who want to participate in this market wave. And although we like competition, in the end, it introduces a lot of confusion, especially for people who are not particularly technical.
When we look at AI, the key here is it's not necessarily about the logos like
ChatGPT, fundamentally, where everything starts in AI is with the source data. AI can ingest huge amounts of data and is capable of gleaning a lot of insights from that data. But if that data is of poor quality, or if it is inaccurate, then basically all you're going to end up with is a poor quality AI that is generating confidently wrong output.
For our purposes, what we really focus on is making sure that the fundamental data foundation is in place before we even start to think about some of the insights that we can glean from it courtesy of AI.
Pat: That’s a great point, Joo. With that said, how do you envision using AI and the corresponding data as a means to, for example, enhance engagement between HCPs and patients, and perhaps even a patient's overall adherence to a particular therapy?
Joo: I think the important thing to note is that AI will never be a surrogate for real human interaction. And when we're talking about things that are as sensitive as human health, the need to speak to human beings is particularly prevalent. If you're going through a health event, you really want to be able to speak to a fellow human being that can empathize with you. So it’s important to keep front and center the idea that AI can be an enhancer of the overall patient and provider relationship but not a replacement for it.
Enhancing patient relationships hinges on understanding treatment side effects, adherence barriers, effective engagement channels and then using that understanding to enhance adherence by leveraging AI driven omnichannel connections and their corresponding data points. This untapped opportunity allows us to meet patients where they are, activate engagement endpoints and to promote noble goals like adherence, which is truly exciting.
Pat: With the use of all of this information to drive improved adherence, the importance of data privacy becomes paramount. In your opinion, what should be prioritized when trying to implement a program like an AI-driven omnichannel experience?
Joo: I think when we look at all the technologies that have been unleashed on the world over the past three decades, what it's really introduced is this cat and mouse game between cyber criminals, and people who understand that this is an elevation of the human condition. This excitement has to be tempered with a lot of sensitivity to personal information and privacy to make sure that we're not exposing people to unnecessary risk.
At present, this is being tackled on a multilevel basis. Starting with regulation and governments, we talk about HIPAA and PHI and all of the regulatory and compliance requirements at that macro level that really put a lot of focus and attention on ensuring that people who are working with this type of information are being diligent in protecting it. Then, within sectors like healthcare, you have certification organizations, like HITRUST, who do a great job of inspecting and auditing participating organizations. An agency partner that has been HITRUST certified, for example, is demonstrating their commitment to data privacy by holding themselves to a higher privacy standard. This helps ensure people are abiding by all of these regulations and that organizations are really staying true to the guidance by being vigilant about truly protecting this level of personal health information.
At the organization level, there are a lot of technology tools that have been released into the market that also help with the protection of data. These tools cover everything from techniques such as data masking, to tokenization, to all kinds of ways by which we can protect people's information down to the ones and zeros level. Through all of these layers, we're able to do a much better job of protecting people's information – certainly much better than 10 years ago, but it will remain a cat and mouse game, unfortunately. So you must always be vigilant and seek to improve your protective systems and processes.
The Wrap
The transformative potential of AI in Pharma and Life Science is plain to see, but its proper application is far more complicated than what meets the eye. The conversation around AI's role as an enhancer – not a replacement – for human interaction, and how it can facilitate dialogue between healthcare providers and patients to ultimately drive improved adherence and patient outcomes is one clear upshot for the industry at large.
Yet, with the implementation of generative AI comes the need to address the paramount importance of both the source data that trains the AI as well as to consider the data privacy procedures in these AI-driven programs. The approaches organizations take towards safeguarding sensitive information and navigating the complex landscape of healthcare ethics and technology will determine the extent to which we will see AI establish a foothold in the fields of Pharma.
For organizations seeking to stay on the cutting edge of technology in patient care and data privacy,
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