A LITERATURE REVIEW: CHATGPT, WHAT WILL THE FUTURE OF PHARMACY PRACTICE BRING—A THREAT OR A BENEFIT?
Main Article Content
Keywords
pharmacy, technology, ChatGPT, transformation
Abstract
ChatGPT (Chat Generative Pre-trained Transformer) is an artificial intelligence chatbot that uses a technology transformer to predict the following sentences or words in a chat or text. ChatGPT has begun to be widely used in pharmacy services to obtain information about disease, treatment, and patient therapy. However, it has not yet been discovered to what extent the safety and effectiveness of ChatGPT in helping pharmacists for the treatment process and patient care. This article review aims to summarize, evaluate and find the gaps in the research that has been done so that a better understanding of the role of ChatGPT is obtained to optimize its use in pharmaceutical services appropriately. Using English-language publications that were published and connected to ChatGPT and pharmacy services in 2023, the study used a multi-method qualitative approach, ProQuest, and ScienceDirect databases. ChatGPT shows excellent results in helping pharmacists give counselling and bringing immense potential in optimizing pharmacy services and in making clinical decision support. But ChatGPT can’t give accurate and safe information, can’t understand pharmacists’ instructions or explain adverse drug reactions and their causes. The ChatGPT answer shows no signs of reproducibility to low reproducibility. ChatGPT is a helpful technology, but not a professional medical advisor that can substitute such as a pharmacist. ChatGPT’s output must be validated before decision usage for the safety and efficacy of the treatment.
References
2. Biswas S. (2023). Prospective Role of ChatGPT in Pharmacy: According to ChatGPT. SSRN Electronic Journal,.
3. Ciancaglini A., Nunez J., Jaitt M., Otero P., & Goldfarb G. (2021). The Electronic Medical Record in Pediatrics: Functionalities and Best Use Practices. Archivos Argentinos de Pediatria, 119 (6).
4. Davis D. F., Golicic S. L., & Boerstler C. N. (2011). Benefits and Challenges of Conducting Multiple Methods Research in Marketing. Journal of the Academy of Marketing Science, 39 (3), 467 479.
5. Elliott R. A., Camacho E., Jankovic D., Sculpher M. J., & Faria R. (2021). Economic analysis of the prevalence and clinical and economic burden of medication error in England. BMJ Quality & Safety, 30 (2), 96 105.
6. Garg R. K., Urs V. L., Agrawal A. A., Chaudhary S. K., Paliwal V., & Kar S. K. (2023). Exploring the Role of Chat GPT in Patient Care (Diagnosis and Treatment) and Medical Research: A Systematic Review. MedRxiv,.
7. George S., & Elrashid S. (2023). Inventory Management and Pharmaceutical Supply Chain Performance of Hospital Pharmacies in Bahrain: A Structural Equation Modeling Approach. SAGE Open, 13 (1), 215824402211497.
8. Ghorbanzadeh M., Gholami S., Sarani A., Badeli F., & Nasimi F. (2019). The Prevalence, Barriers to Medication Error Reports, and Perceptions of Nurses toward the Causes of Medication Errors in the Hospitals Affiliated to North Khorasan University of Medical Sciences, Iran. Iran Journal of Nursing, 32 (117), 58 68.
9. Huang X., Estau D., Liu X., Yu Y., Qin J., & Li Z. (2023). Evaluating The Performance of ChatGPT in Clinical Pharmacy. .
10. Jairoun A. A., Al-Hemyari S. S., Shahwan M., Humaid Alnuaimi G. R., Zyoud S. H., & Jairoun M. (2023). ChatGPT: Threat or Boon to The Future of Pharmacy Practice? Research in Social and Administrative Pharmacy, 19 (7), 975 976.
11. Liu S., Wright A. P., Patterson B. L., Wanderer J. P., Turer R. W., Nelson S. D., McCoy A. B., Sittig D. F., & Wright A. (2023). Using AI-Generated Suggestions from ChatGPT to Optimize Clinical Decision Support. Journal of the American Medical Informatics Association, 30 (7), 1237 1245.
12. Mahendra A. D. (2021). The Natural and Prevalence of Medication Errors in A Tertiary Hospital in Indonesia. International Journal of Current Pharmaceutical Research, 55 58.
13. Morath B., Chiriac U., Jaszkowski E., Deiß C., Nürnberg H., Hörth K., Hoppe-Tichy T., & Green K. (2023). Performance and Risks of ChatGPT Used in Drug Information: an Exploratory Real-World Analysis. European Journal of Hospital Pharmacy, ejhpharm-2023-003750.
14. Susanti I. (2015). Identifikasi Medication Error pada Fase Prescribing, Transcribing, dan Dispensing di Depo Farmasi Rawat Inap Penyakit Dalam Gedung Teratai, Instalasi Farmasi RSUP Fatmawati Periode 2013. UIN Jakarta.
15. Yangfang L. (2012). Causes of Medication Error and Effective Preventive Strategies. Clinical Medicine & Engineering
16. Zhu Y., Han D., Chen S., Zeng F., & Wang C. (2023). How Can ChatGPT Benefit Pharmacy: A Case Report on Review writing.
Article Sidebar
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All articles published in JPTCP are licensed under Copyright Creative Commons Attribution-NonCommercial 4.0 International License.
Lusy Noviani
Department of Pharmacy, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
Putriana Rachmawati
Department of Pharmacy, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
Alvin Irawan
Department of Pharmacy, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia