How AI Is Transforming Pharmacy Operations: Harry Travis, BS Pharm, MBA

As the pharmacy landscape evolves, artificial intelligence (AI) is poised to dramatically increase operational efficiency—potentially boosting team productivity by 50% in just a few years, explains Harry Travis, BS Pharm, MBA, president at The Travis Group, LLC. Yet with a flood of AI solutions vying for attention, pharmacy leaders must strategically prioritize, rigorously validate, and seamlessly integrate new technologies to realize these benefits. Achieving the right balance between automation and human oversight remains crucial for lasting success.

This transcript has been lightly edited; captions were auto-generated.

Transcript

How do you see generative AI changing the day-to-day workflow for pharmacists and care managers in the next few years?

I think that the potential exists for a lot of change. Many of the steps, if you just step back from the process of filling a prescription and look at the steps involved in filling a prescription, from intake benefit verification to the financial side of it, copay assistance, adjudication, patient engagement, drug utilization review, etc. Every one of those steps involves, at a kind of fundamental level, a set of questions being answered by either a technician or a pharmacist, and all of those answers, the answers to all those questions, exist somewhere, quote, unquote, out there. They're in a textbook, or they're on a form, or they're on a website. And we put a lot of money and a lot of people into navigating that kind of matrix of information. AI can help that task in general a lot, particularly when you're looking at AI agents that can open up websites and read documents and read structured data.

I believe that AI has the potential to make pharmacy teams. Could be teams in retail stores and community pharmacies. It could be teams in mail-order pharmacies. Could be teams and specialty pharmacies. I believe AI has the potential to make those teams significantly more productive, like 50% more productive over the 2- to 3-year period.

What are the biggest challenges you’ve encountered when integrating AI solutions into existing health care systems?

I think one of the biggest challenges right now is that there are a myriad of companies out there. We'll call them AI startups, AI tech platforms, that are approaching pharmacy operators with, 'I have a solution for,' and fill in the blank: prior auth[orizations], customer service, copay assistance, and revenue cycle management, and they're all point solutions. The challenge today is for pharmacy operators to pick which solution that they're going to kind of validate. You can only do so much. There's only so much time available.

Pharmacy operators are in a kind of comfortable or uncomfortable position of having all of these potential solution providers knocking on the door. They have to prioritize, 'Okay, which low-hanging piece of fruit [are] we going to go after first?' And then the challenge is, we've got to validate that tool to a very high degree of accuracy and reliability such that we can let it run without a lot of oversight. Okay, we always talk about we're going to keep a human in the loop. Well, we don't want to, I agree, but we don't want to keep the human so much in the loop that we don't get the productivity gains out of it and some of these tasks.

Step one, I believe, is validating each of these solutions against the pharmacy management system that's currently in place that you're relying on to dispense your medication, and then you have, kind of in programming language, an API [Application Programming Interface] that's connected to the XYZ company, and you're getting really comfortable and confident that that particular application is meeting its goals, and then you can move on to the next one, and the next one, and the next one.