AI and the evolving role of the pharmacist

Retail pharmacists not only dispense medications and educate patients but also administer vaccines and manage chronic diseases.¹

While their education and experience mean pharmacists are well-suited for their broader involvement on the patient care team, doing so effectively means they must reconfigure workflows to support additional patient care activities. At the same time, they must manage the rapid uptick in the number of prescriptions, complex drug regimens and administrative tasks driven by ongoing advances in healthcare and pharmaceuticals.

These changes have left pharmacists struggling to navigate an overwhelming influx of data from multiple channels — electronic health record (EHR) systems, laboratories, electronic prescribing, journals, clinical overviews, industry research, regulations, patient and provider communications, etc. — that they must translate into meaningful, actionable information.

Leveraging AI innovation to address modern challenges in the pharmacy industry

Although retail pharmacies have technology in place to improve operations and assist with patient care responsibilities, it falls short in alleviating pharmacists’ increasing workloads and reducing the time spent manually sorting through large volumes of data.

Furthermore, it does not focus on meeting pharmacists’ requirements for clinical decision support as they endeavor to deliver timely, safe and effective care.

Artificial intelligence steps up

For retail pharmacies and clinical pharmacists, the modern solution comes in the form of artificial intelligence (AI). Advancements in AI capabilities and its deeper integration into healthcare systems and processes means pharmacists have access to a wider array of tools that support workflows and enable provision of more accurate evidence-based clinical decisions.²

This is supported by a growing body of research demonstrating AI’s potential as a transformative technology in pharmacy practice.³ AI algorithms assist pharmacists in efficiently accessing essential information from the vast amount of clinical and drug data they encounter in their daily pharmacy operations. By using responsible AI in conjunction with a drug reference tool, pharmacists can significantly improve medication therapy management (MTM) by aiding identification of potential drug-drug interactions, assessing medication safety and efficacy and supporting better informed recommendations tailored to individual patient needs.

AI also assists clinical decision support (CDS) systems with medication-related decisions and can play a role in medication management by helping pharmacists make informed decisions about prescribed medications and treatment regimens.⁴ It can also assist with supporting the identification of potential drug interactions and adverse reactions and aid pharmacists in analyzing data around a patient’s medication usage and refill history to support med adherence and help mitigate complications.

AI also has the power to support pharmacists by:⁵

• Automating dispensing processes⁶

• Optimizing medication dosages⁷

• Supporting telemedicine initiatives⁸

• Enhancing security measures⁹

By incorporating responsible AI tools with trusted content into the pharmacy workflow, pharmacists can make care decisions based on the latest evidence, enhance clinical decision-making, boost confidence, alleviate burnout and enhance professional satisfaction.

AI is not without challenges

Despite its demonstrated benefits, AI presents several challenges for pharmacists. One is the cost and resources required for initial AI integration, which may be financially out of reach for some pharmacies. The training and education required to overcome reluctance to adopt AI tools can impede incorporation of AI into pharmacy operations. While there may be initial reluctance to adopt AI tools, comprehensive training can empower pharmacists to fully leverage AI, enhancing their daily operations.

Other notable challenges include:¹⁰

• Lack of empirical evidence supporting the efficacy of AI interventions. Because most AI research is retrospective and conducted in controlled environments, the results are hard to verify in real-world settings.

• Accountability concerns when AI is used for pharmaceutical purposes, which makes it difficult to determine who is responsible when problems arise.

Careful evaluation of potential AI tools and full consideration of their implications within a given pharmacy setting can bypass these issues and instill confidence in their use by pharmacists.

ClinicalKey AI and the principles of appropriate AI

The best AI solutions for pharmacists are those modeled upon the principles of responsible AI pulling from trusted content to support confident medication decisions. Adhering to these principles allows AI tools to support the expanded role of clinical pharmacists in today’s retail setting while bypassing many of the challenges that can compromise accuracy and damage confidence. One such solution is ClinicalKey AI from Elsevier, a company that upholds industry standards and privacy controls to ensure its solutions effectively align with and support user goals and objectives. ClinicalKey AI merges the power of AI with trusted content from more than 1,000 journals and books, as well as synoptic content to support point of care needs, and updates from the Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC) and National Library of Medicine (NLM), to bring pharmacists timely evidence-based information at the point of care.

Currently the only AI-powered drug information solution available for pharmacists, ClinicalKey AI features a unique architectural design called “retrieval augmented generation” (RAG) that:

• Allows users to type their questions in a conversational style

• Grounds responses in accurate, current information by retrieving facts from trusted content

• Generates responses with advanced result representation that includes summaries and follow-up questions

To adhere to the principles of responsible AI, the data was tested by more than 30,000 clinicians for two years on a clinical large language model (LLM) platform. Internal testing was also undertaken by more than 100 Elsevier clinicians who regularly evaluate the accuracy of ClinicalKey AI’s output, while clinicians with two health systems validated that the solution met pharmacists’ workflow needs.

ClinicalKey AI addresses three key challenges pharmacists face at the point of care: time constraints, complex medication regimens and unvetted AI.

Learn how ClinicalKey AI empowers pharmacists 在新的选项卡/窗口中打开 by bridging the gap between trusted medical content and advanced artificial intelligence. Designed specifically for clinicians, it revolutionizes decision-making at the point of care.