Integrating Large Language Models Into UAE Community Pharmacies: Pharmacists' Perspectives on Benefits, Concerns, and Implementation Barriers
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View abstract on PubMed
Summary
This summary is machine-generated.Pharmacists in the UAE perceive significant risks with large language models (LLMs), including security and empathy concerns. Addressing these barriers through training and security measures is crucial for safe adoption in community pharmacies.
Area Of Science
- Health Informatics
- Artificial Intelligence in Healthcare
- Pharmacy Practice Research
Background
- The UAE's healthcare sector is rapidly advancing with new technologies.
- Understanding pharmacist perspectives on large language models (LLMs) is vital for digital health initiatives.
- Addressing implementation challenges for LLMs in pharmacy is a national priority.
Purpose Of The Study
- To explore UAE pharmacists' views on the benefits and drawbacks of LLM adoption.
- To identify barriers hindering LLM integration in community pharmacies.
- To determine factors associated with increased concerns regarding LLMs.
Main Methods
- A cross-sectional survey was conducted with 528 community pharmacists in the UAE.
- A validated questionnaire assessed socio-demographics, perceived benefits, concerns, and barriers.
- Binary logistic regression analyzed factors linked to LLM concerns.
Main Results
- Pharmacists reported low perceived benefits for 24/7 support (37.3%) and personalized care plans (74.4%).
- Major barriers included need for supervision (54.7%) and insufficient training (32.4%).
- Key concerns were technical failures (97.5%), hacking (97.2%), and lack of empathy (95.6%). Older pharmacists and those with higher degrees showed differing concern levels.
Conclusions
- LLM integration in pharmacies faces significant hurdles like security risks and empathy deficits.
- Enhanced training, robust security, and tailored LLM solutions are necessary.
- These interventions will support the safe and effective adoption of LLMs in pharmacy settings.
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