Accelerating the Front End of Medicine: Three Digital Use Cases and HCI Implications.

Digital applications in health care are a concurrent research and management question, where implementation experiences are a core field of information systems research. It also contributes to fighting pandemic crises like COVID-19 because contactless information flow and speed of diagnostics are improved. This paper presents three digital application case studies from emergency medicine, administration management, and cancer diagnosis with AI support from the University Medical Centers of Münster and Göttingen in Germany. All cases highlight the potential of digitalization to increase speed and efficiency within the front end of medicine as the crucial phase before patient treatment starts. General challenges for health care project implementations and human-computer interaction (HCI) concepts in health care are derived and discussed, including the importance of specific processes together with user analysis and adaption. A derived concept for HCI includes the criteria speed, accuracy, modularity, and individuality to achieve sustainable improvements within the front end of medicine.

Public opinion towards global distribution of COVID-19 vaccines - Data from Germany and the United States.

This study gathered evidence from Germany and the United States on public opinion towards fair distribution of COVID-19 vaccines across the world. Analytical Hierarchy Process and discrete choice experiments were used for this purpose. The sample is nationally representative of adults (aged 18 and above) for both countries using quotas on age, gender, education, state, and COVID-19 vaccination rates at the time of the fieldwork (25 May 2021 to 26 June 2021). Overall 1,003 responses in Germany and 1,000 in the United States were collected.

Dendritic axon origin enables information gating by perisomatic inhibition in pyramidal neurons.

Information processing in neuronal networks involves the recruitment of selected neurons into coordinated spatiotemporal activity patterns. This sparse activation results from widespread synaptic inhibition in conjunction with neuron-specific synaptic excitation. We report the selective recruitment of hippocampal pyramidal cells into patterned network activity. During ripple oscillations in awake mice, spiking is much more likely in cells in which the axon originates from a basal dendrite rather than from the soma. High-resolution recordings in vitro and computer modeling indicate that these spikes are elicited by synaptic input to the axon-carrying dendrite and thus escape perisomatic inhibition. Pyramidal cells with somatic axon origin can be activated during ripple oscillations by blocking their somatic inhibition. The recruitment of neurons into active ensembles is thus determined by axonal morphological features.

Public opinion on global distribution of COVID-19 vaccines: Evidence from two nationally representative surveys in Germany and the United States.

Despite ongoing calls for a more even global distribution of COVID-19 vaccines, there remains a great disparity between high- and low-income countries. We conducted representative surveys among the adult populations in the United States (N = 1,000) and Germany (N = 1,003) in June 2021 to assess public opinion in these countries on the distributive justice of COVID-19 vaccines. We conducted two instances of analytic hierarchy processes (AHP) to elicit how the public weighs different principles and criteria for vaccine allocation. In further discrete choice experiments, respondents were asked to split a limited supply of vaccine doses between a hypothetical high-income and a hypothetical low-income country. AHP weights in the United States and Germany were 37.4% (37.2-37.5) and 49.4% (49.2-49.5) for "medical urgency", 32.7% (32.6-32.8) and 25.4% (25.2-25.5) for "equal access for all", 13.7% (13.6-13.8) and 13.3% (13.2-13.4) for "production contribution", and 16.3% (16.2-16.4) and 12.0% (11.9-12.1) for "free market rules", respectively, with 95% CI shown in parentheses. In the discrete choice experiment, respondents in the United States and Germany split available vaccine doses such that the low-income country, which was three times more populous than the high-income country, on average received 53.9% (95% CI: 52.6-55.1) and 57.5% (95% CI: 56.3-58.7) of available doses, respectively. When faced with a dilemma where a vulnerable family member was waiting for a vaccine, 20.7% (95% CI: 18.2-23.3) of respondents in the United States and 18.2% (95% CI: 15.8-20.6) in Germany reduced the amount they allocated to the low-income country sufficiently to secure a vaccine for their family member. Our results indicate that the public in the United States and Germany favours utilitarian and egalitarian distribution principles of vaccines for COVID-19 over libertarian or meritocratic principles. This implies that political decisions favouring higher levels of redistribution would be supported by public opinion in these two countries.

Differential modulation of parietal cortex activity by respiration and θ oscillations.

The simultaneous, local integration of information from widespread brain regions is an essential feature of cortical computation and particularly relevant for multimodal association areas such as the posterior parietal cortex. Slow, rhythmic fluctuations in the local field potentials (LFPs) are assumed to constitute a global signal aiding interregional communication through the long-range synchronization of neuronal activity. Recent work demonstrated the brain-wide presence of a novel class of slow neuronal oscillations that are entrained by nasal respiration. However, whether there are differences in the influence of the respiration-entrained rhythm (RR) and the endogenous theta (θ) rhythm over local networks is unknown. In this work, we aimed at characterizing the impact of both classes of oscillations on neuronal activity in the posterior parietal cortex of mice. We focused our investigations on a θ-dominated state (rapid eye movement sleep) and an RR-dominated state (wake immobility). Using linear silicon probes implanted along the dorsoventral cortical axis, we found that the LFP-depth distributions of both rhythms show differences in amplitude and coherence but no phase shift. Using tetrode recordings, we demonstrate that a substantial fraction of parietal neurons is modulated by either RR or θ or even by both rhythms simultaneously. Interestingly, the phase and cortical depth dependence of spike-field coupling differ for these oscillations. We further show through intracellular recordings in urethane-anesthetized mice that synaptic inhibition is likely to play a role in generating respiration-entrainment at the membrane potential level. We conclude that θ and respiration differentially affect neuronal activity in the parietal cortex.NEW & NOTEWORTHY Nasal respiration generates a rhythmic signal that entrains large portions of the mammalian brain into respiration-coupled field potentials. Here, we report the simultaneous presence of respiratory rhythm (RR) and θ oscillations in the parietal association cortex of mice. Despite their overlapping frequencies, both rhythms differ in their state-dependent power and differentially entrain the discharge behavior of units. We conclude that network activity in the parietal cortex is synchronized by two different physiological oscillation patterns.

COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach.

The COVID-19 pandemic is a global challenge to humankind. To improve the knowledge regarding relevant, efficient and effective COVID-19 measures in health policy, this paper applies a multi-criteria evaluation approach with population, health care, and economic datasets from 19 countries within the OECD. The comparative investigation was based on a Data Envelopment Analysis approach as an efficiency measurement method. Results indicate that on the one hand, factors like population size, population density, and country development stage, did not play a major role in successful pandemic management. On the other hand, pre-pandemic healthcare system policies were decisive. Healthcare systems with a primary care orientation and a high proportion of primary care doctors compared to specialists were found to be more efficient than systems with a medium level of resources that were partly financed through public funding and characterized by a high level of access regulation. Roughly two weeks after the introduction of ad hoc measures, e.g., lockdowns and quarantine policies, we did not observe a direct impact on country-level healthcare efficiency, while delayed lockdowns led to significantly lower efficiency levels during the first COVID-19 wave in 2020. From an economic perspective, strategies without general lockdowns were identified as a more efficient strategy than the full lockdown strategy. Additionally, governmental support of short-term work is promising. Improving the efficiency of COVID-19 countermeasures is crucial in saving as many lives as possible with limited resources.

Artificial Intelligence for Hospital Health Care: Application Cases and Answers to Challenges in European Hospitals.

The development and implementation of artificial intelligence (AI) applications in health care contexts is a concurrent research and management question. Especially for hospitals, the expectations regarding improved efficiency and effectiveness by the introduction of novel AI applications are huge. However, experiences with real-life AI use cases are still scarce. As a first step towards structuring and comparing such experiences, this paper is presenting a comparative approach from nine European hospitals and eleven different use cases with possible application areas and benefits of hospital AI technologies. This is structured as a current review and opinion article from a diverse range of researchers and health care professionals. This contributes to important improvement options also for pandemic crises challenges, e.g., the current COVID-19 situation. The expected advantages as well as challenges regarding data protection, privacy, or human acceptance are reported. Altogether, the diversity of application cases is a core characteristic of AI applications in hospitals, and this requires a specific approach for successful implementation in the health care sector. This can include specialized solutions for hospitals regarding human-computer interaction, data management, and communication in AI implementation projects.

Long-Term Economic Sustainability of Humanitarian Logistics-A Multi-Level and Time-Series Data Envelopment Analysis.

Although resources are scarce and outputs incorporate the potential to save human lives, efficiency measurement endeavors with data envelopment analysis (DEA) methods are not yet commonplace in the research and practice of non-government organizations (NGO) and states involved in humanitarian logistics. We present a boot-strapped DEA window analysis and Malmquist index application as a methodological state of the art for a multi-input and multi-output efficiency analysis and discuss specific adaptions to typical core challenges in humanitarian logistics. A characteristic feature of humanitarian operations is the fact that a multitude of organizations are involved on at least two levels, national and supra-national, as well as in two sectors, private NGO and government agencies. This is modeled and implemented in an international empirical analysis: First, a comprehensive dataset from the 34 least developed countries in Africa from 2002 to 2015 is applied for the first time in such a DEA Malmquist index efficiency analysis setting regarding the national state actor level. Second, an analysis of different sections in a Rohingya refugee camp in Bangladesh is analyzed based on a bootstrapped DEA with window analysis application for 2017, 2018, and 2019 quarter data regarding the private NGO level of operations in humanitarian logistics.