Role of ruler or intruder? Patient’s right to autonomy in the age of innovation and technologies

Žaliauskaitė, Milda

doi:10.1007/s00146-020-01034-7

Cited by 4 publications

(2 citation statements)

References 48 publications

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“…Ethical considerations also warrant attention in the quest for specialized roles in gerontogeriatric nursing. As we move towards a more individualized, transition-focused care model, privacy, consent, and autonomy become increasingly pertinent [36].…”

Section: Discussionmentioning

confidence: 99%

Meleis’s Transition Theory in Gerontogeriatric Nursing and the Future Need for Specialized Care

Coelho,

Lobão,

Parola

et al. 2024

JAL

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With an ageing global population, healthcare systems confront challenges unique to the elderly. Current care models primarily manage health–illness shifts but frequently miss developmental transitions, particularly for older adults. Meleis’s transition theory offers an underutilized framework to rejuvenate our gerontogeriatric nursing approach. This article aims to articulate and advocate the value of Meleis’s transition theory as a framework for gerontogeriatric nursing, focusing on developmental transitions, thereby seeking a transformative change in the quality of elderly care. The article delves into Meleis’s transition theory’s vital components—transition types, conditions, and nursing therapeutics. It explores how these can be a multifaceted guide for gauging and overseeing ageing’s developmental shifts; adopting this theoretical perspective deepens our comprehension and bears tangible implications. Nurses versed in this theory could appreciate the benefits of a nuanced approach to the elderly, distinguishing it from the conventional biomedical stance. As the demands of an ageing populace grow, the integration of Meleis’s transition theory into nursing practices is not merely beneficial but imperative, setting a new standard for comprehensive and specialized elderly care.

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Section: Discussionmentioning

confidence: 99%

Meleis’s Transition Theory in Gerontogeriatric Nursing and the Future Need for Specialized Care

Coelho,

Lobão,

Parola

et al. 2024

JAL

View full text Add to dashboard Cite

show abstract

“…AI holds promise in enhancing patient autonomy, presenting the prospect of a more balanced clinician-patient relationship with a more equitable decision-making process ( 73 ). For example, an AI-driven self-monitoring device has been developed to anticipate exacerbation risks (severe worsening of lung symptoms) in patients with chronic obstructive pulmonary disorder (COPD) ( 74 ).…”

Section: Enhancing Ebp Through Ai Supportmentioning

confidence: 99%

Towards evidence-based practice 2.0: leveraging artificial intelligence in healthcare

Nilsen,

Sundemo,

Heintz

et al. 2024

Front. Health Serv.

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BackgroundEvidence-based practice (EBP) involves making clinical decisions based on three sources of information: evidence, clinical experience and patient preferences. Despite popularization of EBP, research has shown that there are many barriers to achieving the goals of the EBP model. The use of artificial intelligence (AI) in healthcare has been proposed as a means to improve clinical decision-making. The aim of this paper was to pinpoint key challenges pertaining to the three pillars of EBP and to investigate the potential of AI in surmounting these challenges and contributing to a more evidence-based healthcare practice. We conducted a selective review of the literature on EBP and the integration of AI in healthcare to achieve this.Challenges with the three components of EBPClinical decision-making in line with the EBP model presents several challenges. The availability and existence of robust evidence sometimes pose limitations due to slow generation and dissemination processes, as well as the scarcity of high-quality evidence. Direct application of evidence is not always viable because studies often involve patient groups distinct from those encountered in routine healthcare. Clinicians need to rely on their clinical experience to interpret the relevance of evidence and contextualize it within the unique needs of their patients. Moreover, clinical decision-making might be influenced by cognitive and implicit biases. Achieving patient involvement and shared decision-making between clinicians and patients remains challenging in routine healthcare practice due to factors such as low levels of health literacy among patients and their reluctance to actively participate, barriers rooted in clinicians' attitudes, scepticism towards patient knowledge and ineffective communication strategies, busy healthcare environments and limited resources.AI assistance for the three components of EBPAI presents a promising solution to address several challenges inherent in the research process, from conducting studies, generating evidence, synthesizing findings, and disseminating crucial information to clinicians to implementing these findings into routine practice. AI systems have a distinct advantage over human clinicians in processing specific types of data and information. The use of AI has shown great promise in areas such as image analysis. AI presents promising avenues to enhance patient engagement by saving time for clinicians and has the potential to increase patient autonomy although there is a lack of research on this issue.ConclusionThis review underscores AI's potential to augment evidence-based healthcare practices, potentially marking the emergence of EBP 2.0. However, there are also uncertainties regarding how AI will contribute to a more evidence-based healthcare. Hence, empirical research is essential to validate and substantiate various aspects of AI use in healthcare.

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The impact of artificial intelligence on the person-centred, doctor-patient relationship: some problems and solutions

Sauerbrei

Kerasidou

Lucivero

et al. 2023

BMC Med Inform Decis Mak

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Artificial intelligence (AI) is often cited as a possible solution to current issues faced by healthcare systems. This includes the freeing up of time for doctors and facilitating person-centred doctor-patient relationships. However, given the novelty of artificial intelligence tools, there is very little concrete evidence on their impact on the doctor-patient relationship or on how to ensure that they are implemented in a way which is beneficial for person-centred care.Given the importance of empathy and compassion in the practice of person-centred care, we conducted a literature review to explore how AI impacts these two values. Besides empathy and compassion, shared decision-making, and trust relationships emerged as key values in the reviewed papers. We identified two concrete ways which can help ensure that the use of AI tools have a positive impact on person-centred doctor-patient relationships. These are (1) using AI tools in an assistive role and (2) adapting medical education. The study suggests that we need to take intentional steps in order to ensure that the deployment of AI tools in healthcare has a positive impact on person-centred doctor-patient relationships. We argue that the proposed solutions are contingent upon clarifying the values underlying future healthcare systems.

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Role of ruler or intruder? Patient’s right to autonomy in the age of innovation and technologies

Cited by 4 publications

References 48 publications

Meleis’s Transition Theory in Gerontogeriatric Nursing and the Future Need for Specialized Care

Meleis’s Transition Theory in Gerontogeriatric Nursing and the Future Need for Specialized Care

Towards evidence-based practice 2.0: leveraging artificial intelligence in healthcare

The impact of artificial intelligence on the person-centred, doctor-patient relationship: some problems and solutions

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