2025 ILC Annual International Conference , 16th & 17 June, 2025, Genoa, Italy, Global Collaboration,Local Action for Fundamentals of Care Innovation. Zie bladzijde 81. An international group of experts has joined forces for the further development of Artificial Intelligence (AI) in relation to the Fundamentals of Care (FoC) framework. AI, or its categories like machine learning and deep learning, offers potential to identify patterns in healthcare data, develop clinical prediction models, and derive insights from large datasets. For example, algorithms can be created to detect the start of the palliative phase based on electronic health records, or to inform nursing decisions based on lifestyle monitoring data for older adults. These AI applications significantly influence nurses' roles, the nurse-client relationship and nurses’ professional identity. Consequently, nurses must take responsibility to ensure that AI applications align with person-centered fundamental care, professional ethics, equity, and social justice. Thus, nursing leadership is essential to lead the development and use of AI applications that support nursing care according to the FoC framework, and enhance patient outcomes. The aim of the current project is to explore nurses’ responsibility for how AI adds value to the FoC framework. Firstly, nurse leaders play a vital role in overseeing the quality and relevance of data collected in daily practice, as these data are foundational for AI algorithms. The elements as articulated in the FoC framework should be the building blocks for any algorithm. These building blocks can be linked to clinical and social conditions, and life stages, building from the basis of the individual's human needs. Secondly, it is crucial for nurses to participate in the interdisciplinary teams that develop AI algorithms. Their participation and expertise ensure that algorithms are co-created with an understanding of the needs of their clients, maximizing the potential for positive outcomes. In addition to education, policy, and regulation, a nurse-led, interdisciplinary research program is needed to investigate the relationship between AI applications, the FoC framework and it’s impact on nurse-client relationships, nurses’ professional identity, and patient outcomes.
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Through a qualitative examination, the moral evaluations of Dutch care professionals regarding healthcare robots for eldercare in terms of biomedical ethical principles and non-utility are researched. Results showed that care professionals primarily focused on maleficence (potential harm done by the robot), deriving from diminishing human contact. Worries about potential maleficence were more pronounced from intermediate compared to higher educated professionals. However, both groups deemed companion robots more beneficiary than devices that monitor and assist, which were deemed potentially harmful physically and psychologically. The perceived utility was not related to the professionals' moral stances, countering prevailing views. Increasing patient's autonomy by applying robot care was not part of the discussion and justice as a moral evaluation was rarely mentioned. Awareness of the care professionals' point of view is important for policymakers, educational institutes, and for developers of healthcare robots to tailor designs to the wants of older adults along with the needs of the much-undervalued eldercare professionals.
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BACKGROUND: Recent evidence suggests that an increase in baccalaureate-educated registered nurses (BRNs) leads to better quality of care in hospitals. For geriatric long-term care facilities such as nursing homes, this relationship is less clear. Most studies assessing the relationship between nurse staffing and quality of care in long-term care facilities are US-based, and only a few have focused on the unique contribution of registered nurses. In this study, we focus on BRNs, as they are expected to serve as role models and change agents, while little is known about their unique contribution to quality of care in long-term care facilities. METHODS: We conducted a cross-sectional study among 282 wards and 6,145 residents from 95 Dutch long-term care facilities. The relationship between the presence of BRNs in wards and quality of care was assessed, controlling for background characteristics, i.e. ward size, and residents' age, gender, length of stay, comorbidities, and care dependency status. Multilevel logistic regression analyses, using a generalized estimating equation approach, were performed. RESULTS: 57% of the wards employed BRNs. In these wards, the BRNs delivered on average 4.8 min of care per resident per day. Among residents living in somatic wards that employed BRNs, the probability of experiencing a fall (odds ratio 1.44; 95% CI 1.06-1.96) and receiving antipsychotic drugs (odds ratio 2.15; 95% CI 1.66-2.78) was higher, whereas the probability of having an indwelling urinary catheter was lower (odds ratio 0.70; 95% CI 0.53-0.91). Among residents living in psychogeriatric wards that employed BRNs, the probability of experiencing a medication incident was lower (odds ratio 0.68; 95% CI 0.49-0.95). For residents from both ward types, the probability of suffering from nosocomial pressure ulcers did not significantly differ for residents in wards employing BRNs. CONCLUSIONS: In wards that employed BRNs, their mean amount of time spent per resident was low, while quality of care on most wards was acceptable. No consistent evidence was found for a relationship between the presence of BRNs in wards and quality of care outcomes, controlling for background characteristics. Future studies should consider the mediating and moderating role of staffing-related work processes and ward environment characteristics on quality of care.
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