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To explore the prescribing practices and behaviours of Advanced Practice Nurses (APN) and pharmacist prescribers in Singapore, assess their confidence in key prescribing competencies, examine their use of information sources, and understand their views on the consequences of prescribing errors.
Cross-sectional national survey.
A census survey of all registered APN and pharmacist prescribers in Singapore was conducted from February to May 2024 using a validated 96-item instrument. The survey assessed prescribing practices, confidence in prescribing competencies, use of information sources, and prescribing safety. Descriptive statistics were used for analysis.
Ninety-one prescribers (54 APNs, 37 pharmacists) responded (32% response rate), most of whom worked in public medical/surgical settings. Prescribing comprised a median of 75% of their practice. Most time was spent prescribing continued medications, with less on initiating new medicines. Participants reported high confidence in communication, therapeutic partnerships, and working within professional standards. Greatest confidence was seen in educating patients, legal prescribing, and monitoring treatment response. Lower confidence was noted in complementary medicine-related tasks. Professional literature and colleagues were the most valued information sources. Most participants acknowledged the serious consequences of prescribing errors, though many believed such errors would likely be intercepted.
APNs and pharmacists demonstrate strong competencies in safe, holistic prescribing. However, cultural factors may limit patient engagement, highlighting the need to strengthen shared decision-making and collaborative practice.
Refining governance structures, adopting tiered prescriber autonomy, and enhancing training in complex prescribing are essential. Standardising deprescribing, improving access to decision-support tools, and promoting interprofessional collaboration and patient involvement can strengthen care quality and team-based delivery.
This study offers the first national insight into Singapore's Collaborative Prescribing Framework and informs training, policy, and workforce development for non-physician prescribers locally and in similar international contexts.
STROBE checklist.
This study did not include patient or public involvement in its design, conduct, or reporting.
The use of technology to support nurses' decision-making is increasing in response to growing healthcare demands. AI, a global trend, holds great potential to enhance nurses' daily work if implemented systematically, paving the way for a promising future in healthcare.
To identify and describe AI technologies for nurses' clinical decision-making in healthcare settings.
A systematic literature review.
CINAHL, PubMed, Scopus, ProQuest, and Medic were searched for studies with experimental design published between 2005 and 2024.
JBI guidelines guided the review. At least two researchers independently assessed the eligibility of the studies based on title, abstract, and full text, as well as the methodological quality of the studies. Narrative analysis of the study findings was performed.
Eight studies showed AI tools improved decision-making, patient care, and staff performance. A discharge support system reduced 30-day readmissions from 22.2% to 9.4% (p = 0.015); a deterioration algorithm cut time to contact senior staff (p = 0.040) and order tests (p = 0.049). Neonatal resuscitation accuracy rose to 94%–95% versus 55%–80% (p < 0.001); seizure assessment confidence improved (p = 0.01); pressure ulcer prevention (p = 0.002) and visual differentiation (p < 0.001) improved. Documentation quality increased (p < 0.001).
AI integration in nursing has the potential to optimise decision-making, improve patient care quality, and enhance workflow efficiency. Ethical considerations must address transparency, bias mitigation, data privacy, and accountability in AI-driven decisions, ensuring patient safety and trust while supporting equitable, evidence-based care delivery.
The findings underline the transformative role of AI in addressing pressing nursing challenges such as staffing shortages, workload management, and error reduction. By supporting clinical decision-making and workflow efficiency, AI can enhance patient safety, care quality, and nurses' capacity to focus on direct patient care. A stronger emphasis on research and implementation will help bridge usability and scalability gaps, ensuring sustainable integration of AI across diverse healthcare settings.
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