Purpose The effect of advanced age per se versus severity of chronic and acute diseases on the short- and long-term survival of older patients admitted to the intensive care unit (ICU) remains unclear. Methods Intensive care unit admissions to the surgical ICU and medical ICU of patients older than 65 years were analyzed. Patients were divided into three age groups: 65–74, 75–84, and 85 and above. The primary endpoints were 28-day and 1-year mortality. Results The analysis focused on 7,265 patients above the age of 65, representing 45.7 % of the total ICU population. From the first to third age group there was increased prevalence of heart failure (25.9–40.3 %), cardiac arrhythmia (24.6–43.5 %), and valvular heart disease (7.5–15.8 %). There was reduced prevalence of diabetes complications (7.5–2.4 %), alcohol abuse (4.1–0.6 %), chronic obstructive pulmonary disease (COPD) (24.4–17.4 %), and liver failure (5.0–1.0 %). Logistic regression analysis adjusted for gender, sequential organ failure assessment, do not resuscitate, and Elixhauser score found that patients from the second and third age group had odds ratios of 1.38 [95 % confidence interval (CI) 1.19–1.59] and 1.53 (95 % CI 1.29–1.81) for 28-day mortality as compared with the first age group. Cox regression analysis for 1-year mortality in all populations and in 28-day survivors showed the same trend. Conclusions The proportion of elderly patients from the total ICU population is high. With advancing age, the proportion of various preexisting comorbidities and the primary reason for ICU admission change. Advanced age should be regarded as a significant independent risk factor for mortality, especially for ICU patients older than 75.

The emergence of ethical concerns surrounding artificial intelligence (AI) has led to an explosion of high-level ethical principles being published by a wide range of public and private organizations. However, there is a need to consider how AI developers can be practically assisted to anticipate, identify and address ethical issues regarding AI technologies. This is particularly important in the development of AI intended for healthcare settings, where applications will often interact directly with patients in various states of vulnerability. In this paper, we propose that an ‘embedded ethics’ approach, in which ethicists and developers together address ethical issues via an iterative and continuous process from the outset of development, could be an effective means of integrating robust ethical considerations into the practical development of medical AI.

Background: The main German-speaking countries (Germany, Austria, and Switzerland) have implemented digital contact tracing apps to assist the authorities with COVID-19 containment strategies. Low user rates for these apps can affect contact tracing and, thus, its usefulness in controlling the spread of the novel coronavirus. Objective: This study aimed to assess the early perceptions of people living in the German-speaking countries and compare them with the frames portrayed in the newspapers during the first wave of the COVID-19 pandemic. Methods: We conducted qualitative interviews with 159 participants of the SolPan project. Of those, 110 participants discussed contact tracing apps and were included in this study. We analyzed articles regarding contact tracing apps from 12 newspapers in the German-speaking countries. Results: Study participants perceived and newspaper coverage in all German-speaking countries framed contact tracing apps as governmental surveillance tools and embedded them in a broader context of technological surveillance. Participants identified trust in authorities, respect of individual privacy, voluntariness, and temporary use of contact tracing apps as prerequisites for democratic compatibility. Newspapers commonly referenced the use of such apps in Asian countries, emphasizing the differences in privacy regulation among these countries. Conclusions: The uptake of digital contact tracing apps in German-speaking countries may be undermined due to privacy risks that are not compensated by potential benefits and are rooted in a deeper skepticism towards digital tools. When authorities plan to implement new digital tools and practices in the future, they should be very transparent and proactive in communicating their objectives and the role of the technology—and how it differs from other, possibly similar, tools. It is also important to publicly address ethical, legal, and social issues related to such technologies prior to their launch.

Artificial intelligence (AI) in healthcare promises to make healthcare safer, more accurate, and more cost-effective. Public and private actors have been investing significant amounts of resources into the field. However, to benefit from data-intensive medicine, particularly from AI technologies, one must first and foremost have access to data. It has been previously argued that the conventionally used “consent or anonymize approach” undermines data-intensive medicine, and worse, may ultimately harm patients. Yet, this is still a dominant approach in European countries and framed as an either-or choice. In this paper, we contrast the different data governance approaches in the EU and their advantages and disadvantages in the context of healthcare AI. We detail the ethical trade-offs inherent to data-intensive medicine, particularly the balancing of data privacy and data access, and the subsequent prioritization between AI and other effective health interventions. If countries wish to allocate resources to AI, they also need to make corresponding efforts to improve (secure) data access. We conclude that it is unethical to invest significant amounts of public funds into AI development whilst at the same time limiting data access through strict privacy measures, as this constitutes a waste of public resources. The “AI revolution” in healthcare can only realise its full potential if a fair, inclusive engagement process spells out the values underlying (trans) national data governance policies and their impact on AI development, and priorities are set accordingly.

To explore reasons of non-vaccinated nursing staff for declining seasonal influenza vaccination. The annual influenza vaccination of healthcare workers reduces morbidity and mortality among vulnerable patients. Still, vaccination rates remain very low, particularly in nursing staff. While several studies have explored barriers for healthcare workers to get vaccinated, most have used a quantitative approach. Data were collected by in-depth individual semi-structured interviews with 18 nurses from a range of fields, positions in organizational hierarchy, work experience and hospitals in two German-speaking cantons in Switzerland. Interviews were transcribed and analysed using conventional content analysis. Three interconnected themes explaining why nurses decline influenza vaccination were identified: Firstly, the idea of maintaining a strong and healthy body, which was a central motif for rejecting the vaccine. Secondly, the wish to maintain decisional autonomy - especially over one's body and health. Thirdly, nurses' perception of being surrounded by an untrustworthy environment, which restricts their autonomy and seemingly is in opposition to their goal of maintaining a strong and healthy body. Nurses tend to rely on conventional health beliefs rather than evidence based medicine when making their decision to decline influenza vaccination. Interventions to increase influenza vaccination should be tailored specifically for nurses. Empowering nurses by promoting decision-making skills and by strengthening their appraisal may be important factors to consider when planning future interventions to improve vaccination rates. The teaching of evidence-based decision-making should be integrated on different levels, including nurses' training curricula, their workspace and further education.