958 resultados para workflow engine


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An understanding of interruptions in healthcare is important for the design, implementation, and evaluation of health information systems and for the management of clinical workflow and medical errors. The purpose of this study is to identify and classify the types of interruptions experienced by Emergency Department(ED) nurses working in a Level One Trauma Center. This was an observational field study of Registered Nurses (RNs) employed in a Level One Trauma Center using the shadowing method. Results of the study indicate that nurses were both recipients and initiators of interruptions. Telephones, pagers, and face-to-face conversations were the most common sources of interruptions. Unlike other industries, the healthcare community has not systematically studied interruptions in clinical settings to determine and weigh the necessity of the interruption against their sometimes negative results such as medical errors, decreased efficiency, and increased costs. Our study presented here is an initial step to understand the nature, causes, and effects of interruptions, thereby improving both the quality of healthcare and patient safety. We developed an ethnographic data collection technique and a data coding method for the capturing and analysis of interruptions. The interruption data we collected are systematic, comprehensive, and close to exhaustive. They confirmed the findings from earlier studies by other researchers that interruptions are frequent events in critical care and other healthcare settings. We are currently using these data to analyze the workflow dynamics of ED clinicians, to identify the bottlenecks of information flow, and to develop interventions to improve the efficiency of emergency care through the management of interruptions.

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OBJECTIVE: To identify and describe unintended adverse consequences related to clinical workflow when implementing or using computerized provider order entry (CPOE) systems. METHODS: We analyzed qualitative data from field observations and formal interviews gathered over a three-year period at five hospitals in three organizations. Five multidisciplinary researchers worked together to identify themes related to the impacts of CPOE systems on clinical workflow. RESULTS: CPOE systems can affect clinical work by 1) introducing or exposing human/computer interaction problems, 2) altering the pace, sequencing, and dynamics of clinical activities, 3) providing only partial support for the work activities of all types of clinical personnel, 4) reducing clinical situation awareness, and 5) poorly reflecting organizational policy and procedure. CONCLUSIONS: As CPOE systems evolve, those involved must take care to mitigate the many unintended adverse effects these systems have on clinical workflow. Workflow issues resulting from CPOE can be mitigated by iteratively altering both clinical workflow and the CPOE system until a satisfactory fit is achieved.

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An understanding of interruptions in healthcare is important for the design, implementation, and evaluation of health information systems and for the management of clinical workflow and medical errors. The purpose of this study is to identify and classify the types of interruptions experienced by ED nurses working in a Level One Trauma Center. This was an observational field study of Registered Nurses employed in a Level One Trauma Center using the shadowing method. Results of the study indicate that nurses were both recipients and initiators of interruptions. Telephone, pagers, and face-to-face conversations were the most common sources of interruptions. Unlike other industries, the outcomes caused by interruptions resulting in medical errors, decreased efficiency and increased cost have not been systematically studied in healthcare. Our study presented here is an initial step to understand the nature, causes, and effects of interruptions, and to develop interventions to manage interruptions to improve healthcare quality and patient safety. We developed an ethnographic data collection technique and a data coding method for the capturing and analysis of interruptions. The interruption data we collected are systematic, comprehensive, and close to exhaustive. They confirmed the findings from early studies by other researchers that interruptions are frequent events in critical care and other healthcare settings. We are currently using these data to analyze the workflow dynamics of ED clinicians, identify the bottlenecks of information flow, and develop interventions to improve the efficiency of emergency care through the management of interruptions.

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BACKGROUND AND PURPOSE We report on workflow and process-based performance measures and their effect on clinical outcome in Solitaire FR Thrombectomy for Acute Revascularization (STAR), a multicenter, prospective, single-arm study of Solitaire FR thrombectomy in large vessel anterior circulation stroke patients. METHODS Two hundred two patients were enrolled across 14 centers in Europe, Canada, and Australia. The following time intervals were measured: stroke onset to hospital arrival, hospital arrival to baseline imaging, baseline imaging to groin puncture, groin puncture to first stent deployment, and first stent deployment to reperfusion. Effects of time of day, general anesthesia use, and multimodal imaging on workflow were evaluated. Patient characteristics and workflow processes associated with prolonged interval times and good clinical outcome (90-day modified Rankin score, 0-2) were analyzed. RESULTS Median times were onset of stroke to hospital arrival, 123 minutes (interquartile range, 163 minutes); hospital arrival to thrombolysis in cerebral infarction (TICI) 2b/3 or final digital subtraction angiography, 133 minutes (interquartile range, 99 minutes); and baseline imaging to groin puncture, 86 minutes (interquartile range, 24 minutes). Time from baseline imaging to puncture was prolonged in patients receiving intravenous tissue-type plasminogen activator (32-minute mean delay) and when magnetic resonance-based imaging at baseline was used (18-minute mean delay). Extracranial carotid disease delayed puncture to first stent deployment time on average by 25 minutes. For each 1-hour increase in stroke onset to final digital subtraction angiography (or TICI 2b/3) time, odds of good clinical outcome decreased by 38%. CONCLUSIONS Interval times in the STAR study reflect current intra-arterial therapy for patients with acute ischemic stroke. Improving workflow metrics can further improve clinical outcome. CLINICAL TRIAL REGISTRATION: URL http://www.clinicaltrials.gov. Unique identifier: NCT01327989.

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OBJECTIVES The aim of this case series was to introduce a complete digital workflow for the production of monolithic implant crowns. MATERIAL AND METHODS Six patients were treated with implant-supported crowns made of resin nano ceramic (RNC). Starting with an intraoral optical scan (IOS), and following a CAD/CAM process, the monolithic crowns were bonded either to a novel prefabricated titanium abutment base (group A) or to a CAD/CAM-generated individualized titanium abutment (group B) in premolar or molar sites on a soft tissue level dental implant. Economic analyses included clinical and laboratory steps. An esthetic evaluation was performed to compare the two abutment-crown combinations. RESULTS None of the digitally constructed RNC crowns required any clinical adaptation. Overall mean work time calculations revealed obvious differences for group A (65.3 min) compared with group B (86.5 min). Esthetic analysis demonstrated a more favorable outcome for the prefabricated bonding bases. CONCLUSIONS Prefabricated or individualized abutments on monolithic RNC crowns using CAD/CAM technology in a model-free workflow seem to provide a feasible and streamlined treatment approach for single-edentulous space rehabilitation in the posterior region. However, RNC as full-contour material has to be considered experimental, and further large-scale clinical investigations with long-term follow-up observation are necessary.

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Background Workflow interruptions during surgery may cause a threat to patient's safety. Workflow interruptions were tested to predict failure in action regulation that in turn predicts near-accidents in surgery and related health care. Methods One-hundred-and-thirty-three theater nurses and physicians from eight Swiss hospitals participated in a cross-sectional questionnaire survey. The study participation rate was 43%. Results Structural equation modeling confirmed an indirect path from workflow interruptions through cognitive failure in action regulation on near-accidents (p < 0.05). The indirect path was stronger for workflow interruptions by malfunctions and task organizational blockages compared with workflow interruptions that were caused by persons. The indirect path remained meaningful when individual differences in conscientiousness and compliance with safety regulations were controlled. Conclusion Task interruptions caused by malfunction and organizational constraints are likely to trigger errors in surgery. Work redesign is recommended to reduce workflow interruptions by malfunction and regulatory constraints.

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Land degradation as well as land conservation maps at a (sub-) national scale are critical for pro-ject planning for sustainable land management. It has long been recognized that online accessible and low-cost raster data sets (e.g. Landsat imagery, SRTM-DEM’s) provide a readily available basis for land resource assessments for developing countries. However, choice of spatial, tempo-ral and spectral resolution of such data is often limited. Furthermore, while local expert knowl-edge on land degradation processes is abundant, difficulties are often encountered when linking existing knowledge with modern approaches including GIS and RS. The aim of this study was to develop an easily applicable, standardized workflow for preliminary spatial assessments of land degradation and conservation, which also allows the integration of existing expert knowledge. The core of the developed method consists of a workflow for rule-based land resource assess-ment. In a systematic way, this workflow leads from predefined land degradation and conserva-tion classes to field indicators, to suitable spatial proxy data, and finally to a set of rules for clas-sification of spatial datasets. Pre-conditions are used to narrow the area of interest. Decision tree models are used for integrating the different rules. It can be concluded that the workflow presented assists experts from different disciplines in col-laboration GIS/RS specialists in establishing a preliminary model for assessing land degradation and conservation in a spatially explicit manner. The workflow provides support when linking field indicators and spatial datasets, and when determining field indicators for groundtruthing.

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This paper presents the development history and specification of a 3D game engine titled "Spark Engine". The term "engine" is used to describe a complex graphics software suite that streamlines application development and provides efficient rendering functionality. A game engine specifically provides tools to simplify game development. Spark Engine is fully shader driven and is built on top of Microsoft's XNA Framework. It is a reusable and flexible platform that can be used to build any type of graphics application ranging from gaming to simulation. The engine was released as open source software under the New BSD License with an interest in furthering its development.

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A workflow flowchart on the verification steps involved in preparation to uploading assets to the University of Connecticut's institutional repository (http://digitalcommons.uconn.edu). This flowchart is geared towards assisting subject liaisons who also serve as series administrators for UConn@DigitalCommons.

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The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this proposa

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Knowledge management is critical for the success of virtual communities, especially in the case of distributed working groups. A representative example of this scenario is the distributed software development, where it is necessary an optimal coordination to avoid common problems such as duplicated work. In this paper the feasibility of using the workflow technology as a knowledge management system is discussed, and a practical use case is presented. This use case is an information system that has been deployed within a banking environment. It combines common workflow technology with a new conception of the interaction among participants through the extension of existing definition languages.

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This paper describes an infrastructure for the automated evaluation of semantic technologies and, in particular, semantic search technologies. For this purpose, we present an evaluation framework which follows a service-oriented approach for evaluating semantic technologies and uses the Business Process Execution Language (BPEL) to define evaluation workflows that can be executed by process engines. This framework supports a variety of evaluations, from different semantic areas, including search, and is extendible to new evaluations. We show how BPEL addresses this diversity as well as how it is used to solve specific challenges such as heterogeneity, error handling and reuse

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In recent years, applications in domains such as telecommunications, network security or large scale sensor networks showed the limits of the traditional store-then-process paradigm. In this context, Stream Processing Engines emerged as a candidate solution for all these applications demanding for high processing capacity with low processing latency guarantees. With Stream Processing Engines, data streams are not persisted but rather processed on the fly, producing results continuously. Current Stream Processing Engines, either centralized or distributed, do not scale with the input load due to single-node bottlenecks. Moreover, they are based on static configurations that lead to either under or over-provisioning. This Ph.D. thesis discusses StreamCloud, an elastic paralleldistributed stream processing engine that enables for processing of large data stream volumes. Stream- Cloud minimizes the distribution and parallelization overhead introducing novel techniques that split queries into parallel subqueries and allocate them to independent sets of nodes. Moreover, Stream- Cloud elastic and dynamic load balancing protocols enable for effective adjustment of resources depending on the incoming load. Together with the parallelization and elasticity techniques, Stream- Cloud defines a novel fault tolerance protocol that introduces minimal overhead while providing fast recovery. StreamCloud has been fully implemented and evaluated using several real word applications such as fraud detection applications or network analysis applications. The evaluation, conducted using a cluster with more than 300 cores, demonstrates the large scalability, the elasticity and fault tolerance effectiveness of StreamCloud. Resumen En los útimos años, aplicaciones en dominios tales como telecomunicaciones, seguridad de redes y redes de sensores de gran escala se han encontrado con múltiples limitaciones en el paradigma tradicional de bases de datos. En este contexto, los sistemas de procesamiento de flujos de datos han emergido como solución a estas aplicaciones que demandan una alta capacidad de procesamiento con una baja latencia. En los sistemas de procesamiento de flujos de datos, los datos no se persisten y luego se procesan, en su lugar los datos son procesados al vuelo en memoria produciendo resultados de forma continua. Los actuales sistemas de procesamiento de flujos de datos, tanto los centralizados, como los distribuidos, no escalan respecto a la carga de entrada del sistema debido a un cuello de botella producido por la concentración de flujos de datos completos en nodos individuales. Por otra parte, éstos están basados en configuraciones estáticas lo que conducen a un sobre o bajo aprovisionamiento. Esta tesis doctoral presenta StreamCloud, un sistema elástico paralelo-distribuido para el procesamiento de flujos de datos que es capaz de procesar grandes volúmenes de datos. StreamCloud minimiza el coste de distribución y paralelización por medio de una técnica novedosa la cual particiona las queries en subqueries paralelas repartiéndolas en subconjuntos de nodos independientes. Ademas, Stream- Cloud posee protocolos de elasticidad y equilibrado de carga que permiten una optimización de los recursos dependiendo de la carga del sistema. Unidos a los protocolos de paralelización y elasticidad, StreamCloud define un protocolo de tolerancia a fallos que introduce un coste mínimo mientras que proporciona una rápida recuperación. StreamCloud ha sido implementado y evaluado mediante varias aplicaciones del mundo real tales como aplicaciones de detección de fraude o aplicaciones de análisis del tráfico de red. La evaluación ha sido realizada en un cluster con más de 300 núcleos, demostrando la alta escalabilidad y la efectividad tanto de la elasticidad, como de la tolerancia a fallos de StreamCloud.