20 research outputs found
Cost-effectiveness in extracorporeal life support in critically ill adults in the Netherlands
Background: Extracorporeal life support (ECLS) is used to support the cardiorespiratory function in case of severe cardiac and/or respiratory failure in critically ill patients. According to the ELSO guidelines ECLS should be considered when estimated mortality risk approximates 80%. ECLS seems an efficient therapy in terms of survival benefit, but no undisputed evidence is delivered yet. The aim of the study is to assess the health-related quality of life after ECLS treatment and its cost effectiveness.
Methods: We will perform a prospective observational cohort study. All adult patients who receive ECLS in the participating centers will be included. Exclusion criteria are patients in whom the ECLS is only used to bridge a procedure (like a high risk percutaneous coronary intervention or surgery) or the absence of informed consent. Data collection includes patient characteristics and data specific for ECLS treatment. Severity of illness and mortality risk is measured as precisely as possible using measurements for the appropriate age group and organ failure. For analyses on survival patients will act as their own control as we compare the actual survival with the estimated mortality on initiation of ECLS if conservative treatment would have been continued. Survivors are asked to complete validated questionnaires on health related quality of life (EQ5D-5 L) and on medical consumption and productivity losses (iMTA/iPCQ) at 6 and 12 months. Also the health related quality of life 1 month prior to ECLS initiation will be obtained by a questionnaire, if needed provided by relatives. With an estimated overall survival of 62% 210 patients need to be recruited to make a statement on cost effectiveness for all ECLS indications.
Discussion: If our hypothesis that ECLS treatment is cost-effective is confirmed by this prospective study this could lead to an even broader use of ECLS treatment
Hysterectomy Does Not Cause Constipation
PURPOSE: This study was designed to evaluate the risk on development and persistence of constipation after hysterectomy. METHODS: We conducted a prospective, observational, multicenter study with three-year follow-up in 13 teaching and nonteaching hospitals in the Netherlands. A total of 413 females who underwent hysterectomy for benign disease other than symptomatic uterine prolapse were included. All patients underwent vaginal hysterectomy, subtotal abdominal hysterectomy, or total abdominal hysterectomy. A validated disease-specific quality-of-life questionnaire was completed before and three years after surgery to assess the presence of constipation. RESULTS: Of the 413 included patients, 344 (83 percent) responded at three-year follow-up. Constipation had developed in 7 of 309 patients (2 percent) without constipation before surgery and persisted in 16 of 35 patients (46 percent) with constipation before surgery. Preservation of the cervix seemed to be associated with an increased risk of the development of constipation (relative risk, 6.6; 95 percent confidence interval, 1.3-33.3; P=0.02). Statistically significant risk factors for the persistence of constipation could not be identified. CONCLUSIONS: Hysterectomy does not seem to cause constipation. In nearly half of the patients reporting constipation before hysterectomy, this symptom will disappear
Exploring, exploiting and evolving diversity of aquatic ecosystem models: A community perspective
Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5–10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary
Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective
A growth model of the cockle (Cerastoderma edule L.) tested in the Oosterschelde estuary (The Netherlands)
We present an ecophysiological model of the bivalve Cerastoderma edule that simulates individual growth and reproduction under ambient conditions in temperature and food availability in the Oosterschelde estuary, SW Netherlands. The model contains feedback loops in the uptake and metabolism of food and in the partitioning of carbon to the internal state variables: somatic tissue, storage, organic shell matrix and gametes. The model was calibrated for 24 parameters, based on random distributions of parameter values. This procedure includes an estimate of confidence intervals of the output variables. The simulated growth of shell length and animal wet and dry weight reflected the observed values of growth in the field for the period 1993 – 1997. The model is a tool for the integration of ecophysiological knowledge of this species and also for carrying-capacity studies of shellfish culture and for environmental management of populations in estuarine and coastal areas. D 2005 Elsevier B.V. All rights reserved
Output-Classes for Faculty-Based Design-Oriented Research on Digital Learning Resources in Higher Education
Abstract Digital learning resources are essentially knowledge-intensive information systems. In higher education, advance of interactive digital learning resources will primarily require design-oriented efforts by faculty. Growth of knowledge on digital learning resources and learning objects in higher education implies design, realization, use, implementation and evaluation of digital learning resources as well as sharing knowledge in scientific publications. Over the last fifteen years a range of projects involving such design-oriented activities in natural, engineering, management, decision and information sciences has been carried out. There is a growing body of literature on various design-related research approaches in educational research and in information systems research. However, for faculty-based design-oriented research the question what knowledge should be shared in scientific publications is not yet clearly answered. This article relates this question to the transdisciplinary nature of faculty-based design-oriented research. The article proposes an answer to this question in terms of a set of result types or output-classes. For each output-class it is explained why a contribution in that class can provide a valuable addition to the body of knowledge on digital learning resources in higher education
Structuring Multidisciplinary Knowledge for Model
In the last decade a strong need for Quality Assurance has emerged among professionals in model based water management. The manifold of reasons for this can be summarised as follows. There is a lack of mutual understanding between modellers, model study clients, model auditors, stakeholders and concerned members of the public. Furthermore, malpractice (careless handling of input data, insufficient calibration/validation and model use outside of its scope) promotes a growing disbelief in the competence of models to support decision-making. This growing disbelief is fuelled by the tendency of modellers to oversell model capabilities. Several initiatives claim to support Quality Assurance in model based water management, but these focus on single domains and usually have chosen a textbook approach to provide guidelines and fillin forms to monitor modelling. The EC funded project HarmoniQuA aims at supporting the full modelling process by offering computer based guidance for all water management domains, different types of users, different types of modelling purposes (planning, design and operational management) and different levels of modelling complexity. In addition to the guidance, users are helped to record all what they do and to produce for a diverse audience dedicated reports. Finally, HarmoniQuA intends to facilitate co-operation between groups within and between modelling studies and let its users learn from other modelling studies. The HarmoniQuA system consists of a knowledge base and a toolbox. This paper will discuss scientific, technical and organisational considerations behind the HarmoniQuA approach for integrated modelling support. These considerations can be divided into two groups, one related to the expertise of modellers, the other to knowledge engin..
A Farm Information Model for Development and Configuration of Interoperable ICT Components to support Collaborative Business Processes – a case of late blight protection
Farm enterprises2
The objective of this paper is to describe a farm information model and a proof of concept that demonstrates how a collaborative Business Process for farming can be configured using this farm information model. Knowledge to develop this model and a proof of concept is obtained by case study research focusing on the collaborative Business Processes of spraying and crop protection of potatoes against late blight disease. need to collaborate with numerous actors that are part of Agri-Food Supply Chain Networks (AFSCNs) such as governments, advisory services, contractors, processors, input providers and certification bodies. This collaboration is required to produce food in a more sustainable, safe and transparent manner. To collaborate efficiently and effectively, information needs to be shared within collaborative Business Processes. The information sharing within such collaborative Business Processes should be supported by an ICT infrastructure consisting of interoperable ICT Components. Currently, most of the available ICT Components are not interoperable, hindering data exchange between ICT Components of various vendors. Consequently, this situation is hindering optimization of farm production processes and collaboration in AFSCNs. Therefore, a platform, called FIspace, is being established for multiple domains that support the development and configuration of interoperable ICT Components into a system that is able to support collaborative farm Business Processes. To develop interoperable ICT Components and configure these in an easy and flexible manner to support farm enterprises, a farm information model is, amongst other models, required.The presented farm information reference model is able to describe the relations between a farm enterprise and its collaborators, the Business Processes related to the supporting ICT Components and the data messages for data exchange between ICT Components
IoF2020 - the Internet of Meat : towards applications of Internet of Things in the meat supply chain
To enable all actors in the meat supply chain to monitor, manage and optimise their production process, Internet of Things applications create multiple opportunities. In the IoF2020 project (Internet of Food and Farm 2020), starting early 2017, 11 partners from five countries focus on large-scale implementations of IoT via three use cases in the meat supply chain: pig farm management, poultry chain monitoring and meat transparency and traceability. Farmer’s lack of accessibility to information to monitor their production on a continuous basis will be addressed by installing and integrating IoT sensors for environmental and animal monitoring. In addition, early warning systems will be developed, linking different data-streams to provide valuable feedback to the farmer, as well as information transfer to other stakeholders. Doing so, preventive or corrective actions for diseases, boar taint, bird mortality, feed waste, environment, etc. can be taken. Further, also EPCIS-based tracebility from farm to fork will be enabled, so that consumers receive reliable information on meat origin and quality. The current progress of these three use cases, as well as the planned developments will be presented. By addressing several technological and business challenges, as well as EU-wide dissemination, IoF2020 aims to contribute to the digital revolution in Smart Farming