Aim
To construct a competency evaluation index system for geriatric nursing positions in the context of new medical science.
Background
The new medical discipline is centered on the concept of population health, aiming to establish a comprehensive health service system that incorporates preventive measures, treatment and wellness strategies. It deeply integrates advanced technologies such as artificial intelligence and data science to achieve the digital and intelligent transformation of healthcare services. This places greater demands on the professional competence of nurses working in geriatric care positions. However, the precise competencies that nurses in China's geriatric care settings currently possess to meet the demands of high-quality elderly care remain unclear.
Design
A Delphi study.
Methods
Based on the onion model as a theoretical foundation, this study has preliminarily constructed a draft competency framework through evidence-based integration and behavioral event interviews. Two rounds of Delphi expert consultations were conducted with 19 specialists to revise and refine the indicator system.
Results
The evaluation indicator system comprises four primary indicators, 14 secondary indicators and 51 tertiary indicators, which include professionalism, theoretical knowledge, skills and personal characteristics. The response rates for the two rounds of expert questionnaires were 95 % and 89 %, respectively. The expert authority coefficients for the two rounds were 0.93 and 0.89, respectively.
Conclusion
The indicator system is scientifically sound and reliable, closely aligned with core characteristics such as digital intelligence and interdisciplinary integration. This provides a practical reference point for future development of geriatric care curricula and optimization of talent cultivation programs.
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