This podcast will focus on how generative artificial intelligence (AI) impacts outpatient pharmacy practice. The speakers discuss how AI can help augment patient-centric and administrative functions to help pharmacists improve their outpatient practice, both presently and in the future.
The information presented during the podcast reflects solely the opinions of the presenter. The information and materials are not, and are not intended as, a comprehensive source of drug information on this topic. The contents of the podcast have not been reviewed by ASHP, and should neither be interpreted as the official policies of ASHP, nor an endorsement of any product(s), nor should they be considered as a substitute for the professional judgment of the pharmacist or physician.
[MUSIC] >> Welcome to the ASHP official podcast, your guide to issues related to medication use, public health, and the profession of pharmacy. >> Hello and welcome to the ASHP continuing education podcast series. This podcast episode is tiled, generative AI and its impact on outpatient pharmacy. My name is Kelvin Tran and our guests today are David Perez, a current PGY2 pharmacy informatics resident at Boyter Fred Dirt and the Medical College of Wisconsin, and Pooja Oja, a medication management informaticist at Mayo Clinic. In this episode, we will be discussing how generative AI impacts outpatient pharmacy, including retail pharmacy and ambulatory care spaces. We will also dive into some of the detail about what technologies have been developed and what might be on the horizon. If you are an ASHP member, you can earn continuing education for listening to this episode. Stay tuned to the end of the episode for more information. Let's jump right in. For the first question, Pooja and David, could you please provide a short definition of generative AI? >> Sure. Generative AI refers to deep learning models that can create content such as images, texts or even videos based on the data they are trained on. The data that they're trained on is called the reference data. In general, AI can help with streamlining the pharmacy workflow by simplifying some repetitive or mundane tasks, thus reducing the administrative burden and freeing up the pharmacy personnel to focus on other aspects of patient care. >> To add to what Pooja said, we find that AI can be integrated in various areas of the pharmacy practice, such as in the electronic health record or EHR, or in automated dispensing systems or ADS cabinets. Generative AI can be used to improve various types of workflows from patient documentation all the way to predictive analytics. Ultimately, the goal of integrating artificial intelligence in any pharmacy space would be to improve patient safety and outcomes, or find ways to help the pharmacy staff in achieving those goals. >> Thank you. It sounds like generative AI is a vast concept with potential benefit for outpatient pharmacy. What specific areas of outpatient pharmacy such as community pharmacy or ambulatory care, could generative AI help in? >> Sure. It's very important to consider the outpatient pharmacy workflows when talking about where generative AI might be useful for the practice. In this podcast, when referring to outpatient or community pharmacy, we are talking about the retail side and the ambulatory care side of pharmacy. In retail pharmacy, the pharmacy personnel are reviewing and filling prescription medication orders for patients and are often performing medication therapy management services. In the ambulatory care space, there is a greater focus on one-on-one medication therapy management services for patients. However, pharmacy personnel in these spaces are often managing other activities, such as inventory management or offering immunizations. The current gap with regards to artificial intelligence in this space is that pharmacy personnel are asked to perform many repetitive tasks that have the potential to be automated. Implementing generative AI in these specific places could potentially decrease stress and allow the pharmacy team to focus on patient care. Currently, we are finding opportunities for artificial intelligence in areas such as inventory management solutions. For example, generative AI can help in analyzing data to predict how inventory could fluctuate. We can also predict that generative AI might improve automated dispensing systems as it has the potential to employ machine learning algorithms for optimization to system maintenance and medication organization within the dispensing system. Additionally, generative AI can assist pharmacy staff with identifying and managing public health situations, which could streamline the process of maintaining adequate inventory for life-saving medications. generative AI has the potential to counsel patients for telehealth appointments and offer medication therapy management services itself. When thinking about AI in the ambulatory care or outpatient space, I also think of things that are not directly related to pharmacy personnel's role that inadvertently fall on the pharmacist or pharmacy staff and are often a contributor of patient satisfaction. For example, I think of scheduling assistance that could manage immunization schedules, medication delivery schedules, or staff schedules. I also think of a wait time display that could automatically be updated depending on patient volumes at the pharmacy at that time. In an ambulatory care setting where pharmacists are performing one-on-one MTM services, there is potential to incorporate medication knowledge solutions such as AI that could plan a patient's course of therapy and easy to read language. These advancements could assist in the transitions of care for the patient and their family. These are some great suggestions for what we think users might want to see in the outpatient space. I am sure that incorporating some of these ideas could help the pharmacy workflow tremendously. How about what is currently available on the market? Are any of the AI tools mentioned before available already? That's a really good question, Kelvin. On an almost daily basis, we are seeing new applications of generative AI in various spaces including in healthcare. Specifically for retail and ambulatory care, I found that the use of AI is not yet widespread, but we are feeling a push in that direction with regards to what we are seeing in the news or through other media sources. Most of the peer-reviewed literature that I found so far has focused on the potential uses for AI without actual implementation. However, some retailers are describing how they have started incorporating AI into pharmacy workflows. In the current state, we are seeing structured language standardization, where generative AI creates structure for text. The idea is to standardize the prescription instructions for patients. For example, there are various ways to state "take one tablet by mouth daily". The generative AI in this situation recognizes the variations and standardizes the frequency. This allows the clinician to provide clear and concise instructions for patients without much variability. This retailer also incorporates some supply chain integration where generative AI synthesizes data to experiment with different stocking scenarios. For example, generative AI can help the pharmacy determine the most appropriate dispensing canisters for medications, improving how medications are stored and potentially decreasing waste. To add on to what Pooja just said, that retailer has also described using generative AI for providing cost estimates for prescription medications with estimated insurance pricing. This allows the retailer to focus on customer satisfaction, where customers know what they are paying ahead of time and can plan for medication costs. Another tool utilizes a generative AI robot that sounds and interacts like a human to provide patient consultation. There is also a tool that can help users select the best over-the-counter product based on a given condition. Overall, it does look like there is a significant potential with these tools to be highly effective and helpful in the outpatient space. It's very interesting how you describe a push towards using generative AI in the future. Could you expand on that by describing what potential exists for generative AI for the outpatient pharmacy spaces? That's a great question, Kelvin. So generative AI has a lot in store for the outpatient pharmacy area. On the retail side, I can imagine significant impact of AI to manage medication inventory and costs. There is a lot of time that is spent by pharmacy personnel currently in managing medication inventory in both the inpatient and outpatient spaces. So saving time in both of these areas would be a great benefit. I believe that there is a large potential for utilizing generative AI in the outpatient arena. At this time, I would suggest that there is space for AI to grow in the medication therapy management areas, such as through the use of consultation bots. Additionally, a good target for AI would be in the over-the-counter meds area where there can be an AI assisted pharmacist that reviews a patient's symptoms and suggests good over-the-counter options for the patient. Thank you for that information. It does sound like the scope of generative AI is likely to grow in the future. Could you both discuss some of the current limitations with incorporating AI into the workflows? What challenges do we face today? Sure, I think the major risk for implementing AI in the outpatient space is the lack of research and validated tools used for AI in healthcare. Healthcare institutions are focused on reducing patient harm with the adoption of new technologies. There appears to be potential for that given the current tools might be trained on biased data. This is one of the major drawbacks to implementation at this time. However, we are seeing regulatory agencies begin to monitor the implementation of AI in healthcare. For example, the Office of the National Coordinator for Health Information Technology, or ONC Health IT, has recently published a draft of their Federal Health IT Strategic Plan for 2024-2030. Again, to add to what Pooja just said, I also believe that cost considerations and feasibility of implementing AI are some other considerations before we can even consider incorporating AI into our workflows. There are significant resources required to develop and integrate AI tools within health systems. So even if a tool is free, there are additional implementation considerations to work through as well. For example, staff training on how to use the AI tool would be required. Additionally, resources such as data scientists, machine learning engineers, application engineers, and project managers would be required to help in building these applications. Many healthcare organizations do not have the resources required to develop these generative AI tools themselves. Those are good points and really goes to show how important it is to consider the resource requirement and validate AI tools thoroughly before implementation. For our last question, how is AI going to affect pharmacists? What do we have to do to take advantage of this? Great question, Kelvin. Generative AI is going to significantly impact pharmacy personnel in the coming years. I think of an ongoing point will be continuing to educate pharmacy personnel about AI and how it would impact their workflows. This could be incorporated in continuing education materials such as this podcast or through onsite or virtual training for specific tools that are available. There is certainly some hesitation in the current state to begin the widespread implementation of AI. However, I do believe as more research is published, that hesitation will begin to subside. I have to agree with David. The landscape of AI is huge and it can be really intimidating to begin the process of implementation. I believe engaging in conversations surrounding AI is a good starting point for taking advantage of what is yet to come. I feel like we need to take a similar approach to an AI that we currently take in clinical pharmacy practice of identifying strong evidence-based research for patient care. It is very easy to become inundated with AI-related news and research when searching for AI information in a search engine. Thus, it's important to critically analyze research that is done about generative AI and ensure that it fits the needs of your organization before implementing it. Those are all very good points. As you both mentioned, it seems like we are still in a relatively early adoption phase with generative AI. At least in the pharmacy space, it will be interesting to see where pharmacists are implementing generative AI in the future. Well, that's all the time we have today. Thank you to our guests for a great topic and discussion. For ASHP members, you can find additional resources and earn free continuing education for listening to this episode by visiting elearning.ashp.org/podcast. Please note that continuing education credit expires two years after the date this episode is published. If you enjoyed today's episode, be sure to subscribe to ASHP official through your favorite podcast provider and see you next time. Thank you for listening to ASHP official, The Voice of Pharmacists Advancing Healthcare. Be sure to visit ashp.org/podcast to discover more great episodes, access show notes and download the episode transcript. 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