This podcast will focus on how generative artificial intelligence (AI) impacts administrative aspects of pharmacy practice. We will focus on current technologies and future applications of generative AI in this space.
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.
(upbeat 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. My name is Diana Schreier, and our guest today are Puja Oja, medication management information assist at Mayo Clinic, and Charity Lobut, manager provider product team at HCA Healthcare. In this episode, we will be discussing leveraging artificial intelligence within the administrative pharmacy setting. If you are an ASHP member, you will also have the opportunity to earn continuing education for listening to this episode. Stay tuned to the end of the episode for more information. Now let's jump right in. For our first question, Puja and Charity, could you provide a short definition of generative AI? - Sure, generative AI or artificial intelligence refers to a type of artificial intelligence that can create or generate new content such as text, music, or videos based on patterns that it's learned from an existing dataset called reference data. Many models that are in use today can produce results that resemble human created content. Generative AI is just one of many potential artificial intelligence applications that are being used in healthcare today. Other artificial intelligence modalities can include machine learning, natural language processing, and computer vision. These can be incorporated into generative AI applications as well. - To add to what Puja said, generative AI can be used in the administrative pharmacy setting, particularly to assist with managerial responsibilities such as monitoring data for changes in clinical practice, timekeeping, data analytics, and other functions that can augment the pharmacy leader's ability to manage the clinical and operational impact of their team. - Those are great summaries for what generative AI is and how can be applied in the administrative pharmacy setting. What are some gaps in the administrative pharmacy setting today and how could AI applications assist with those gaps? - Today's pharmacy manager faces several challenges in gaps in their practice. Limited insight into their team's capacity, view readily available tools to measure the department's efficiency, and a never-ending list of new responsibilities to keep up with changes in practice. Effectively staffing and managing teams, identifying adverse drug events, delivering on department metrics, and identifying new ways to improve productivity, continue to challenge the pharmacy staff and administrative roles. Thankfully, some new tools are being developed that will support managers in the pharmacy setting. For example, machine learning or ML can be used to analyze unstructured data, including the electronic health record, to help identify patients with risk factors for adverse drug events and address them earlier in the patient's stay. What if your pharmacy staff spent more time on activities that targeted those reasons for adverse drug events? It would improve care delivery, demonstrate the importance of the pharmacy team's role in these interventions, and ultimately provide better patient outcomes. When it comes to workforce management, the activities related to scheduling and staffing care teams are time-consuming, manual tasks. Over-staffed teams are inefficient and can result in significant financial consequences, and under-staffed teams can risk team burnout, compliance issues, and even create threats to patient safety within your organization. There are numerous technology companies that offer workforce management solutions bolstered by artificial intelligence. These can include algorithms that forecast staffing needs based on patient volume and acuity, tools that facilitate job matching, and products that can assist with creating accurate job description to target potential candidates. These applications will help reduce the administrative burden on the pharmacy manager so they can spend more time growing and developing their team. In addition to identifying adverse drug events and providing staffing solutions, there are documented examples of healthcare organizations leveraging artificial intelligence applications for improved clinical decision-making. Currently, healthcare professionals are overwhelmed by the volume and frequency of clinical practice changes in medicine, and are spending the majority of their time on administrative tasks. This often includes ensuring accurate electronic health record documentation for clinical care, billing, and regulatory purposes. There are several healthcare technology organizations that are leveraging the immense data available in the electronic health record to provide concise, practical summaries of the patient's care so that caregivers can spend more time connecting with their patients. There is also a significant amount of information that pharmacy administrators receive daily in the form of performance metrics. It can be overwhelming to try to synthesize all this data and implement targeted solutions to improve performance measures while not sacrificing the quality of care delivered within these care teams. Pharmacy administrators are often asked to justify their budgets, continue to improve efficiency and reduce waste. Because of these challenges, it is increasingly important for organizations to adopt a solution that will provide accurate, reliable, and easy to understand performance data. - These are all great points as far as practice gaps are concerned, Pooja. From your perspective, what exists from a technology's perspective right now to assist with administrative pharmacy functions? - In addition to the solutions that we've already discussed, there are also companies offering healthcare compliance technology. These services leverage the organization's data to determine opportunities to improve compliance with regulatory standards. As we mentioned before, there are commercially available products that can help optimize workflow scheduling to allow leaders to make more informed decisions for scheduling for their teams. Managers are expected to be able to forecast the labor for planned and unplanned changes. For example, they might be adding a new service line. There could be local surges or there could be many other interruptions to the hospital's daily workflows. And a scheduling solution that actually considers these factors would be immensely valuable. Leaders are expected to make decisions informed by data and a generative AI solution that consumes their facilities metrics would support administrators in making more effective decisions for their teams. There are dashboard summarization tools that can also help with the interpretation of trends and information. Dashboard tools have existed for many years, but with a recent integration of generative AI, high level summaries can be created to help synthesize this information into something managers can reference. And the limitation of these types of tools, unfortunately, is that they can present the information, but they are not sophisticated enough to understand the unique pharmacy workflows. Thus, managing teams still need to determine the cause of the trends and the course of action. - These are great developments in the realm of generative AI. I agree with the limitation of the dashboard tools. One of the key values of these summaries is that you can have general dashboards and practice specific users can get general summaries. This reduces the need for resources to maintain the dashboards. Now that we've discussed some of the applications being leveraged by health system organizations today, what about the future? What are some possibilities for how these technologies could be developed going forward? - Sure, that's a good question. In the future, artificial intelligence applications could monitor for a staff performance, using data from the electronic health record to identify opportunities to reinforce clinical practice in alignment with the hospital's policy, regulatory and accreditation needs. As a pharmacy manager, imagine if you could receive a report that identified the specific practice gaps for staff to improve their competency. In addition, tools that can identify operational inefficiencies could improve time to medication verification, medication interventions, and detection of adverse drug events or other negative patient outcomes. Instead of spending time reviewing endless cumbersome reports, pharmacy managers could identify specific approaches to improve their team's ability to deliver safe, effective healthcare to patients. In the area of clinical decision support, sophisticated, evidence-based alerts that are embedded within the electronic health record could help pharmacy staff make more informed decisions on their patients and let them spend more time working with the higher acuity medically complex patients. Clinical decision support tools that consider more than simple, one-dimensional patient characteristics would help care teams spend less time on the excessive, duplicative administrative documentation that is endemic in healthcare delivery today. In the future, pharmacy teams will spend less time combing through lengthy providers' notes and clinical documentation to find crucial pieces of patient information and more time as an integral member of the multidisciplinary care team. In addition to decision support, generative AI will help staff quickly create accurate succinct clinical documentation such as pharmacy notes. Overall, artificial intelligence applications will augment the pharmacy team's role in the delivery of patient care and help teams reduce the administrative burden of effective medication management. - So my next question is going to be for Charity. So Charity, we've talked a lot about the benefits of AI applications, but what are the risks and limitations of these tools? How will AI change how we do our jobs? - Thank you, Diana. One of the challenges healthcare teams are facing with these applications include the significant resources required to develop and integrate these tools into healthcare organizations. Today, developing a unique GNI program requires significant expertise from professionals that many healthcare systems do not already have in health. Depending on the type of application the organization is looking to create, the team needed can include data scientists or machine learning engineers, data architects, front-end application engineers, and project managers to keep teams organized and meeting necessary timelines. If an organization chooses to purchase a GNI service instead of developing one themselves, they will need to manage costs around user licenses, implementation, and infrastructure necessary to maintain the software. Managers must play an active role in keeping the reference data up-to-date with advancements and changes in practice. Organizations will need to define governance and change control process around these technologies to ensure they're utilized in an ethical, patient-centered manner. As with any new technology, there will be incidents and challenges that will require timely evaluation and responses to avoid patient and caregiver harm. As technology changes, pharmacy leaders need to actively participate in the continuous process of educating, monitoring, and reinforcing safe, evidence-based practices with their team. In addition to the significant time and resources required to develop and manage these tools, healthcare organizations must understand the regulatory implications of using these new technologies. Pharmacy leaders will have to ensure any new technology is rigorously vetted by the information technology team, quality, legal, and under-crucial stakeholders. Another challenge around the current use of GENAI is the potential to create inaccurate information called hallucination. An application that provides therapeutic recommendations that are not aligned with the most recently published guidelines has the potential to create confusion and frustration to clinical staff instead of effective decision-making. There is also limited guidance, training, and governance around how to safely and effectively implement these tools. ASHP has published the ASHP statement on the use of artificial intelligence and pharmacy that provides general guidance around the use of GENAI in the pharmacy setting, equipping organizations with a high-level overview of the role of the pharmacy team as it relates to incorporating artificial intelligence into their practice. Additionally, the Office of the National Coordinator or ONK Health IT has recently published a draft of the Federal IT Strategic Plan for 2024 to 2030 that incorporates elements of GENAI into their development roadmap. While these resources provide a foundation for healthcare organizations evaluating their own AI strategy, there's still opportunities to help guide professionals in successfully developing these tools for the clinical teams. So for our next question, we'd like to know, how is AI going to affect pharmacy teams? What do I have to do to take advantage of this? - The generative AI landscape is changing rapidly with advancements in this relatively new technology. It's important to stay vigilant of new data being published surrounding GENAI use, and pharmacy leaders must critically evaluate developing literature and emerging technologies. Healthcare organizations can expect to see new services offered by vendors that leverage generative AI, machine learning, natural language processing, among other AI modalities. Leaders will need to understand the benefits and challenges with these new technologies and determine what's best for their organization. Their teams can expect to start seeing these technologies develop within their office management software, billing applications, and in some cases, even within the EHR. Pharmacy teams that are interested in learning more about AI can engage with their IT teams and take courses that can provide foundational knowledge for implementing GENAI in their practice. Pharmacy schools are augmenting their curriculums to provide exposure to these topics, and ensure the next generation of pharmacy staff are aware of the implications around leveraging this emerging technology. Preceptors would also need to provide guidance around the appropriate use of GENAI to ensure students use these tools appropriately in their practice. Some healthcare organizations have developed their own strategic plan around the use of AI, and it's important to ensure any new initiative that are aligned with the org's policy, regulatory guidelines, and legal guidance. While there are many exciting possibilities at the advent of easily accessible GENAI applications, there's much work to be done to successfully integrate this new technology in the pharmacy team day-to-day operation. - Well, that's all the time we have for today. Thank you to our guests for a great topic discussion. For our 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 the continuing education credit experience 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. If you loved the episode and want to hear more, be sure to subscribe, rate or leave a review. Join us next time on ASHP official. - Join us next time on ASHP official. (upbeat music) (upbeat music) (upbeat music) (upbeat music) [BLANK_AUDIO]
