AI and pharmacy update
I help mid-career researchers develop sustainable and impactful research programs that are built for the next phase of their careers. Click here to find out more.
A while back, I mentioned that I was working with a few collaborators on an AI-driven update to an editorial we wrote more than 15 years ago. Well, today I wanted to share the first in what has turned into a series of editorials we’ve been writing entitled “AI in pharmacy practice: devolutionary or evolutionary”.
In this editorial, we asked Google Gemini to identify the key pharmacist characteristics from our original editorial and predict how AI-enabled solutions could impact those characteristics in the future. Please read the article for the specific details. But reflecting on what Gemini proposed for the future of pharmacy practice, some interesting patterns are beginning to emerge.
Three of the five proposed ways in which AI could spur an evolution in pharmacy practice focused on streamlining data synthesis, decision-making, and outcome tracking in patient care. Specifically, AI could be helpful in combing through patient charts and background (assuming they were electronically integrated) to provide a quick summary, saving pharmacists time and energy in a patient encounter. AI could also nudge providers and patients regarding best evidence-based practices (think treatment guidelines and self-care/management). Finally, AI could track patient outcomes so that pharmacists can actively manage patients and hopefully help patients be more successful in managing their conditions.
I think these functions would be helpful to pharmacists and patients in the future.
I think it is also worth reminding all of us that the proposals being made by the AI come from materials that WE are publishing, presenting, and posting online in the form of things like research literature, white papers, reports, news pieces, and commentaries. The AI looks for patterns to address the prompts we provide. Or put another way, these are the tasks where WE think AI will be helpful to us.
These proposals also got me thinking about “new” opportunities to apply our skills and knowledge in the future. So far, I’ve thought of 3:
1. Prepping patient material for integration into AI systems.
While most of us will not have the training to code the AI to read and integrate patient charts across clinics, hospitals, and systems, we do have the training and knowledge to know what parts of the charts, notes, and files need to go into creating a comprehensive view of patients.
2. Checking for the interoperability of materials.
Related to prepping patient materials for integration, we have the knowledge and skills needed to look at the existing clinical and research data used for making decisions about patient care to ensure that the integration is accurate and useful to the end user.
3. Tracking recommendations from AI for accuracy and improved patient outcomes.
Once we’re intentionally using AI in patient encounters, we have the clinical and research skills and knowledge to evaluate the AI recommendations being made and used by patients and providers to ensure they are improving patient outcomes.
What other areas or tasks do you think AI will be helpful for in your work? What other opportunities do you see coming from the integration of AI? What is worrying you about AI?
I want to hear your thoughts!
(Words: 521)
Not sure what you need? Complete this 3-minute survey to see if I can help.