RESUMO
OBJECTIVES: This paper addresses the design of a platform for the management of medical decision data in the ICU. Whenever new medical data from laboratories or monitors is available or at fixed times, the appropriate medical support services are activated and generate a medical alert or suggestion to the bedside terminal, the physician's PDA, smart phone or mailbox. Since future ICU systems will rely ever more on medical decision support, a generic and flexible subscription platform is of high importance. METHODS: Our platform is designed based on the principles of service-oriented architectures, and is fundamental for service deployment since the medical support services only need to implement their algorithm and can rely on the platform for general functionalities. A secure communication and execution environment are also provided. RESULTS: A prototype, where medical support services can be easily plugged in, has been implemented using Web service technology and is currently being evaluated by the Department of Intensive Care of the Ghent University Hospital. To illustrate the platform operation and performance, two prototype medical support services are used, showing that the extra response time introduced by the platform is less than 150 ms. CONCLUSIONS: The platform allows for easy integration with hospital information systems. The platform is generic and offers user-friendly patient/service subscription, transparent data and service resource management and priority-based filtering of messages. The performance has been evaluated and it was shown that the response time of platform components is negligible compared to the execution time of the medical support services.
Assuntos
Sistemas de Apoio a Decisões Clínicas/organização & administração , Unidades de Terapia Intensiva , Internet , Tomada de Decisões Assistida por Computador , Humanos , Linguagens de Programação , Interface Usuário-ComputadorRESUMO
.This paper describes the items, scale validity and scale reliability of a self-report questionnaire that measures bystander behavior in cyberbullying incidents among adolescents, and its behavioral determinants. Determinants included behavioral intention, behavioral attitudes, moral disengagement attitudes, outcome expectations, self-efficacy, subjective norm and social skills. Questions also assessed (cyber-)bullying involvement. Validity and reliability information is based on a sample of 238 adolescents (M age=13.52 years, SD=0.57). Construct validity was assessed using Confirmatory Factor Analysis (CFA) or Exploratory Factor Analysis (EFA) in Mplus7 software. Reliability (Cronbach Alpha, α) was assessed in SPSS, version 22. Data and questionnaire are included in this article. Further information can be found in DeSmet et al. (2018) [1].
RESUMO
This paper addresses the design of a generic and scalable platform for the execution of medical decision support agents in the intensive care unit (ICU). As will be motivated, medical decision support agents can impose high computational load and in practical setups a large amount of such agents are typically running in parallel. Future ICU systems will rely on extensive medical decision support. However, in current systems only one workstation is typically dedicated for the execution of medical decision support agents. Therefore, we propose an architecture based on middleware technology to allow for easy distribution of the agents along multiple workstations. The architecture allows for easy integration with a general ICU data flow management architecture.
Assuntos
Sistemas de Apoio a Decisões Clínicas , Técnicas de Apoio para a Decisão , Unidades de Terapia Intensiva , Segurança Computacional , Sistemas Computacionais , Humanos , Redes Locais , Interface Usuário-ComputadorRESUMO
BACKGROUND: E-homecare creates opportunities to provide care faster, at lower cost and higher levels of convenience for patients. As e-homecare services are time-critical, stringent requirements are imposed in terms of total response time and reliability, this way requiring a characterization of their network load and usage behavior. However, it is usually hard to build testbeds on a realistic scale in order to evaluate large-scale e-homecare applications. OBJECTIVE: This paper describes the design and evaluation of the Network Simulator for Web Services (WS-NS), an NS2-based simulator capable of accurately modeling service-oriented architectures that can be used to evaluate the performance of e-homecare architectures. METHODS: WS-NS is applied to the Coplintho e-homecare use case, based on the results of the field trial prototype which targeted diabetes and multiple sclerosis patients. Network-unaware and network-aware service selection algorithms are presented and their performance is tested. RESULTS: The results show that when selecting a service to execute the request, suboptimal decisions can be made when selection is solely based on the service's properties and status. Taking into account the network links interconnecting the services leads to better selection strategies. Based on the results, the e-homecare broker design is optimized from a centralized design to a hierarchical region-based design, resulting in an important decrease of average response times. CONCLUSIONS: The WS-NS simulator can be used to analyze the load and response times of large-scale e-homecare architectures. An optimization of the e-homecare architecture of the Coplintho project resulted in optimized network overhead and more than 45% lower response times.
Assuntos
Redes de Comunicação de Computadores/instrumentação , Simulação por Computador , Sistemas Computacionais , Serviços de Assistência Domiciliar , Informática Médica/instrumentação , Algoritmos , Diabetes Mellitus , Desenho de Equipamento , Humanos , Informática Médica/métodos , Esclerose MúltiplaRESUMO
Acute kidney injury (AKI) is very common among critically-ill patients and is correlated with significant morbidity and mortality. The RIFLE criteria (an acronym comprising Risk, Injury, Failure, Loss and End-stage kidney disease), were developed by a panel of experts aiming at standardizing the definition of AKI and to subdivide AKI into different categories of severity. However, although these criteria are clear and easy to understand, they are still complex and labour-intensive, and therefore mostly used in retrospective. The use of an electronic alert based on the RIFLE criteria, which warns the physician in real-time when kidney function is deteriorating can help to implement these criteria in daily clinical practice. In this paper we describe the successful implementation of such an alert system. Not only were there technological barriers to solve; also acceptance of the alert by the end user was of pivotal importance. Further research is currently performed to investigate whether the implementation of real-time electronic RIFLE alerts induce faster therapeutic intervention, and to evaluate the impact of a more timely intervention on improved preservation of kidney function and patients' outcome.