IT-supported integrated care pathways for diabetes: A compilation and review of good practices

Introduction: Integrated Care Pathways (ICPs) are a method for the mutual decision-making and organization of care for a well-defined group of patients during a well-defined period. The aim of a care pathway is to enhance the quality of care by improving patient outcomes, promoting patient safety, increasing patient satisfaction, and optimizing the use of resources. To describe this concept, different names are used, e.g. care pathways and integrated care pathways. Modern information technologies (IT) can support ICPs by enabling patient empowerment, better management, and the monitoring of care provided by multidisciplinary teams. This study analyses ICPs across Europe, identifying commonalities and success factors to establish good practices for IT-supported ICPs in diabetes care. Methods: A mixed-method approach was applied, combining desk research on 24 projects from the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) with follow-up interviews of project participants, and a non-systematic literature review. We applied a Delphi technique to select process and outcome indicators, derived from different literature sources which were compiled and applied for the identification of successful good practices. Results: Desk research identified sixteen projects featuring IT-supported ICPs, mostly derived from the EIP on AHA, as good practices based on our criteria. Follow-up interviews were then conducted with representatives from 9 of the 16 projects to gather information not publicly available and understand how these projects were meeting the identified criteria. In parallel, the non-systematic literature review of 434 PubMed search results revealed a total of eight relevant projects. On the basis of the selected EIP on AHA project data and non-systematic literature review, no commonalities with regard to defined process or outcome indicators could be identified through our approach. Conversely, the research produced a heterogeneous picture in all aspects of the projects’ indicators. Data from desk research and follow-up interviews partly lacked information on outcome and performance, which limited the comparison between practices. Conclusion: Applying a comprehensive set of indicators in a multi-method approach to assess the projects included in this research study did not reveal any obvious commonalities which might serve as a blueprint for future IT-supported ICP projects. Instead, an unexpected high degree of heterogeneity was observed, that may reflect diverse local implementation requirements e.g. specificities of the local healthcare system, local regulations, or preexisting structures used for the project setup. Improving the definition of and reporting on project outcomes could help advance research on and implementation of effective integrated care solutions for chronic disease management across Europe

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

LeptonInjector and LeptonWeighter: A neutrino event generator and weighter for neutrino observatories

We present a high-energy neutrino event generator, called LeptonInjector, alongside an event weighter, called LeptonWeighter. Both are designed for large-volume Cherenkov neutrino telescopes such as IceCube. The neutrino event generator allows for quick and flexible simulation of neutrino events within and around the detector volume, and implements the leading Standard Model neutrino interaction processes relevant for neutrino observatories: neutrino-nucleon deep-inelastic scattering and neutrino-electron annihilation. In this paper, we discuss the event generation algorithm, the weighting algorithm, and the main functions of the publicly available code, with examples.Comment: 28 pages, 10 figures, 3 table

Searching for eV-scale sterile neutrinos with eight years of atmospheric neutrinos at the IceCube neutrino telescope

We report in detail on searches for eV-scale sterile neutrinos, in the context of a 3+1 model, using eight years of data from the IceCube neutrino telescope. By analyzing the reconstructed energies and zenith angles of 305,735 atmospheric $\nu_\mu$ and $\bar{\nu}_\mu$ events we construct confidence intervals in two analysis spaces: $\sin^2 (2\theta_{24})$ vs. $\Delta m^2_{41}$ under the conservative assumption $\theta_{34}=0$; and $\sin^2(2\theta_{24})$ vs. $\sin^2 (2\theta_{34})$ given sufficiently large $\Delta m^2_{41}$ that fast oscillation features are unresolvable. Detailed discussions of the event selection, systematic uncertainties, and fitting procedures are presented. No strong evidence for sterile neutrinos is found, and the best-fit likelihood is consistent with the no sterile neutrino hypothesis with a p-value of 8\% in the first analysis space and 19\% in the second.Comment: This long-form paper is a companion to the letter "An eV-scale sterile neutrino search using eight years of atmospheric muon neutrino data from the IceCube Neutrino Observatory". v2: update other experiments contours on results plo

Measurement of the high-energy all-flavor neutrino-nucleon cross section with IceCube

The flux of high-energy neutrinos passing through the Earth is attenuated due to their interactions with matter. The interaction rate is determined by the neutrino interaction cross section and affects the flux arriving at the IceCube Neutrino Observatory, a cubic-kilometer neutrino detector embedded in the Antarctic ice sheet. We present a measurement of the neutrino cross section between 60 TeV and 10 PeV using the high-energy starting event (HESE) sample from IceCube with 7.5 years of data. The result is binned in neutrino energy and obtained using both Bayesian and frequentist statistics. We find it compatible with predictions from the Standard Model. While the cross section is expected to be flavor independent above 1 TeV, additional constraints on the measurement are included through updated experimental particle identification (PID) classifiers, proxies for the three neutrino flavors. This is the first such measurement to use a ternary PID observable and the first to account for neutrinos from tau decay

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

A Many-analysts Approach to the Relation Between Religiosity and Well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N = 10, 535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β = 0.120). For the second research question, this was the case for 65% of the teams (median reported β = 0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates