Mapping challenges in the accessibility of treatment products for urea cycle disorders: A survey of European healthcare professionals.

Current management guidelines for urea cycle disorders (UCDs) offer clear strategies, incorporating both authorized and non-authorized medicinal products (including intravenous formulations and products regulated as food). These varying product categories are subject to specific accessibility challenges related to availability, reimbursement, and pricing. The aim of this study is to identify potential obstacles to optimal UCD treatment implementation in European clinical practice.

Making Co-Design More Responsible: Case Study on the Development of an AI-Based Decision Support System in Dementia Care.

Background: Emerging technologies such as artificial intelligence (AI) require an early-stage assessment of potential societal and ethical implications to increase their acceptability, desirability, and sustainability. This paper explores and compares 2 of these assessment approaches: the responsible innovation (RI) framework originating from technology studies and the co-design approach originating from design studies. While the RI framework has been introduced to guide early-stage technology assessment through anticipation, inclusion, reflexivity, and responsiveness, co-design is a commonly accepted approach in the development of technologies to support the care for older adults with frailty.

The evaluation of a decision support system integrating assistive technology for people with dementia at home.

Introduction: With a decreasing workforce of carers and a transition from care homes to home care, people with dementia (PwD) increasingly rely on informal caregivers (ICs) and assistive technologies (ATs). There is growing evidence that ATs in the home environment can reduce workload for formal carers (FCs) and ICs, reduce care costs, and can have a positive influence on quality of life (QoL) for PwD and their caregivers. In practice, using multiple ATs still often implies using different separate point solutions and applications.

AI-Assisted Decision-Making in Long-Term Care: Qualitative Study on Prerequisites for Responsible Innovation.

Background: Although the use of artificial intelligence (AI)-based technologies, such as AI-based decision support systems (AI-DSSs), can help sustain and improve the quality and efficiency of care, their deployment creates ethical and social challenges. In recent years, a growing prevalence of high-level guidelines and frameworks for responsible AI innovation has been observed. However, few studies have specified the responsible embedding of AI-based technologies, such as AI-DSSs, in specific contexts, such as the nursing process in long-term care (LTC) for older adults.