Adoption of ChatGPT as a Drug Information Resource: A Community-Based Study Among Pharmacists

Abstract

Access to accurate and timely drug information is essential for safe and effective pharmacy practice, yet conventional drug information resources are often limited by high costs, restricted accessibility, and time-intensive searches. Artificial intelligence based tools such as ChatGPT provide rapid, conversational access to drug-related information; however, evidence regarding their use in pharmacy practice is limited. This community-based cross-sectional study evaluated the extent, purpose, and perceived impact of ChatGPT utilization among pharmacists. A total of 300 pharmacists from community, hospital, and academic settings participated using a validated questionnaire assessing frequency of use, types of queries, perceived accuracy, and challenges. Overall, 72% of pharmacists reported using ChatGPT for drug information, with highest utilization in community practice. Common queries included dosage adjustments (41%), drug- drug interactions (28%), and adverse drug reaction management (22%). A majority of the participants felt that ChatGPT is a time-saving tool (68%) and has moderate to high levels of accuracy (61%), and 55% of the participants felt that it increased their confidence levels in patient counseling. However, 32% of the participants were concerned about the reliability and lack of citations in the sources used by ChatGPT.

Keywords

• ChatGPT
• Pharmacists
• Drug information
• Artificial Intelligence
• Community based study
• Patient counseling.

References

1. 1. Malone PM, Kier KL, Stanovich JE. Drug Information: A Guide for Pharmacists. 6th ed. New York: McGraw-Hill Education; 2018.
2. 2. Brown JN. Evaluation of drug information resources: A critical appraisal for pharmacy practice. American Journal of Health-System Pharmacy. 2019;76(3):134–140.
3. 3. Ventola CL. Mobile devices and medical applications for healthcare professionals: Uses and benefits. Pharmacy and Therapeutics. 2014;39(5):356–364.
4. 4. Biswas S. Role of ChatGPT in medical writing and healthcare communication. Radiology. 2023;307(2):e223312.
5. 5. Kung TH, Cheatham M, Medenilla A, et al. Performance of ChatGPT on USMLE-style medical examinations. PLoS Digital Health. 2023;2(2):e0000198.
6. 6. Cascella M, Montomoli J, Bellini V, Bignami E. Evaluating the reliability of ChatGPT in clinical decision-making. Healthcare. 2023;11(5):662.
7. 7. Lee P, Bubeck S, Petro J. Benefits, limits, and risks of large language models in medicine. New England Journal of Medicine. 2023;388(13):1233–1239.
8. 8. World Health Organization. Ethics and Governance of Artificial Intelligence for Health. Geneva: WHO; 2021.

9. 9. Hammad M, Iqbal J, Khan S. Artificial intelligence and drug information services: Opportunities and challenges. Journal of Clinical Pharmacy and Therapeutics. 2023;48(4):567–573.
10. 10. Topol EJ. High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine. 2019;25(1):44–56.
11. 11. Gilson A, Safranek CW, Huang T, et al. How medical learners are using artificial intelligence tools: Implications for education. Medical Education. 2023;57(8):734– 743.
12. 12. Johnston L, O’Reilly C, Scholz B. Questionnaire validation methods in pharmacy practice research. Research in Social and Administrative Pharmacy. 2020;16(8):1081– 1087.
13. 13. European Medicines Agency. Artificial Intelligence in Medicines Regulation. EMA; 2022.
14. 14. IBM Watson Health. Clinical decision support systems in pharmacy practice. Journal of Biomedical Informatics. 2021;118: 103784.
15. 15. National Academies of Sciences, Engineering, and Medicine. Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril. Washington, DC: National Academies Press; 2020