A 6-months assessment of the alcohol-related clinical burden at emergency rooms (ERs) in 11 acute care hospitals of an urban area in Germany

BACKGROUND: The purpose of the study was to identify and to profile alcohol-related attendances to emergency rooms (ERs) of 11 hospitals of various medical specialties covering a large urban population, to assess risk factors associated with short-stay cases, repeat attendances and higher degree of alcohol consumption and to estimate their impact on the alcohol-related burden at ERs. METHODS: A 6-months study was carried out to obtain clinical and administrative data on single and multiple attendances at ERs in 11 governmental acute hospitals in a large city in Germany. All alcohol-related attendances at ERs of study hospitals were eligible. A broad definition of alcohol-related attendances independently from alcohol diagnosis and various demographic, clinical and administrative measures were used. Odds ratios for the associations of these measures with duration of stay, repeat attendances and higher degrees of alcohol consumption were derived from multivariate binomial and multinomial logistic regression models. RESULTS: 1,748 patients with symptoms of alcohol consumption or withdrawal (inclusion rate 83.8%) yielded 2,372 attendances (3% of all medical admissions), and resulted in 12,629 inpatient-days. These patients accounted for 10.7 cases per 1,000 inhabitants. The average duration of inpatient stay was 10 days. 1,451 of all patients (83%) presented once, whereas the median of repeat attendances was three for the remaining 297 patients. Short-stay cases (<24 hours) were significantly linked with male gender, alcohol misuse, trauma (or suspicion of a trauma) and medical specialties. Increased levels of alcohol consumption at first attendance were significantly associated with repeat attendances in due course. In a multinomial logistic regression model higher degrees of alcohol consumption were significantly associated with male gender, trauma, short-stays, attendance outside regular working time, and with repeat attendances and self-discharge. CONCLUSION: Apart from demographic factors, the alcohol-related clinical burden is largely determined by short-stay cases, repeat attendances and cases with higher levels of alcohol consumption at first attendance varying across medical specialties. These findings could be relevant for the planning of anti-alcoholic interventions at ERs

An Ontology for OASIS TOSCA

To improve cloud portability and interoperability many standards have been proposed in order to facilitate the design, the development and deployment of cloud applications. One of the most used is TOSCA (Topology and Orchestration Specification for Cloud Applications). However since TOSCA helps modeling the structure of an application there are some information regarding the domain of the application that are missing on the standard. We propose to use an ontology representation of that standard to fill the gap between the structural aspect and the domain of the applications

FaaSten your decisions: A classification framework and technology review of function-as-a-Service platforms

Function-as-a-Service (FaaS) is a cloud service model enabling developers to offload event-driven executable snippets of code. The execution and management of such functions becomes a FaaS provider's responsibility, therein included their on-demand provisioning and automatic scaling. Key enablers for this cloud service model are FaaS platforms, e.g., AWS Lambda, Microsoft Azure Functions, or OpenFaaS. At the same time, the choice of the most appropriate FaaS platform for deploying and running a serverless application is not trivial, as various organizational and technical aspects have to be taken into account. In this work, we present (i) a FaaS platform classification framework derived using a multivocal review and (ii) a technology review of the ten most prominent FaaS platforms, based on the proposed classification framework. We also present a FaaS platform selection support system, called FAASTENER, which can help researchers and practitioners to choose the FaaS platform most suited for their requirements

Tailoring Technology-Agnostic Deployment Models to Production-Ready Deployment Technologies

Most of existing production-ready deployment automation technologies enable declaratively specifying the target deployment for a multi-service application, which can then be automatically enforced. Each technology however relies on a different deployment modelling language, hence hampering the portability of an application deployment from one technology to another. The Essential Deployment Metamodel (EDMM) was hence developed to enable specifying an application deployment in a technology-agnostic manner, in a way that specified deployments can be automatically transformed in the technology-specific deployment artifacts enabling to deploy them with one of the 13 most prominent production-ready deployment technologies. However, not every deployment specified as EDMM model can be executed by all of these deployment technologies, e.g., Kubernetes can actually deploy applications only if their services are containerized. For this reason, this paper introduces the EDMM Tailoring Support System (EDMM TSS), which enables determining whether an application deployment can be deployed with a target technology and if this is not the case, recommending and applying model adaptations to enable deploying the application on the desired target technology. We also present a prototype implementation of the EDMMTSS, which is plugged in the existing EDMM Modeling and Transformation Framework. Moreover, we present a case study showcasing the overall benefits of the resulting EDMM-based deployment support system