ELECTRONIC MEDICAL RECORD - SUCCESS OR FAILURE IN THE MEDICAL DECISION FROM THE ROMANIAN HEALTH SYSTEM ?

The investments in informational and communicational technologies in the health field represent a for of investing in human capital because health and medical services will exceed the physician – patient relationship and the improvement of the physical and emotional condition of the individuals of a society will become a prioritary problem of the community. In Romania is noticed a high degree of data fragmenting, with a negligible communication, often inexistent, within and outside the system, and the decision makers of the health system hold exclusivity on their own data, fact that makes them unavailable to the other participants to the system. The software-s, the formats and supports used differ both inside the system and outside it. And because a patient is given a diagnosis without complete and safe medical data, the medical error is one of the causes for the incorrect diagnosis of the patient. The decision makers from the health system must take on responsibilities for the efficient and safe management of these data, to represent a desired issue for all medical institutions. Only the interconnected and standardized electronic medical files will be able to improve the medical decision and the care given to patients. The care will be safer, more efficient, the medical information will be also useful to other clinic physicians in time and space by using the informational and communicational technologies. The complete electronic medical record must include all types of information connected to the patient`s health (medical, family history, health file, hereditary-collateral antecedents, treatments, prescriptions, allergies) and they must be protected, shared by physicians, patients and those interested in a safe and extended environment. It is necessary to computerize the medical information specific to patient and the clinical processes, and performance in the health system will depend on the transformation of the medical services system by bringing the benefits of the medical science and technology to all individuals.critical; inefficient medical service; electronic medical record; medical information computerization, interconnected electronic medical files, medical error, health electronic file, clinical decision, protected and shared medical information, interoperability, standard.

Online Fault Classification in HPC Systems through Machine Learning

As High-Performance Computing (HPC) systems strive towards the exascale goal, studies suggest that they will experience excessive failure rates. For this reason, detecting and classifying faults in HPC systems as they occur and initiating corrective actions before they can transform into failures will be essential for continued operation. In this paper, we propose a fault classification method for HPC systems based on machine learning that has been designed specifically to operate with live streamed data. We cast the problem and its solution within realistic operating constraints of online use. Our results show that almost perfect classification accuracy can be reached for different fault types with low computational overhead and minimal delay. We have based our study on a local dataset, which we make publicly available, that was acquired by injecting faults to an in-house experimental HPC system.Comment: Accepted for publication at the Euro-Par 2019 conferenc

UC Berkeley's Cory Hall: Evaluation of Challenges and Potential Applications of Building-to-Grid Implementation

From September 2009 through June 2010, a team of researchers developed, installed, and tested instrumentation on the energy flows in Cory Hall on the UC Berkeley campus to create a Building-to-Grid testbed. The UC Berkeley team was headed by Professor David Culler, and assisted by members from EnerNex, Lawrence Berkeley National Laboratory, California State University Sacramento, and the California Institute for Energy & Environment. While the Berkeley team mapped the load tree of the building, EnerNex researched types of meters, submeters, monitors, and sensors to be used (Task 1). Next the UC Berkeley team analyzed building needs and designed the network of metering components and data storage/visualization software (Task 2). After meeting with vendors in January, the UCB team procured and installed the components starting in late March (Task 3). Next, the UCB team tested and demonstrated the system (Task 4). Meanwhile, the CSUS team documented the methodology and steps necessary to implement a testbed (Task 5) and Harold Galicer developed a roadmap for the CSUS Smart Grid Center with results from the testbed (Task 5a) and evaluated the Cory Hall implementation process (Task 5b). The CSUS team also worked with local utilities to develop an approach to the energy information communication link between buildings and the utility (Task 6). The UC Berkeley team then prepared a roadmap to outline necessary technology development for Building-to-Grid, and presented the results of the project in early July (Task 7). Finally, CIEE evaluated the implementation, noting challenges and potential applications of Building-to-Grid (Task 8). These deliverables are available at the i4Energy site: http://i4energy.org/

Assessment benchmarking: accumulating and accelerating institutional know - how for best practice

Benchmarking offers a comprehensive way of measuring current practice in an institution; whilst also gauging achievement against external sources. Although e-learning has been benchmarked with a number of universities in the UK and abroad no one to date has tackled the area of assessment; which is now becoming of more concern with the advent of e-assessment. This paper describes the construction of a set of benchmarking measures/indicators and the outcome of early pilots which combine data from a survey instrument of these measures with semi-structured interviews. The findings indicate that the benchmark measures this project has identified can form a solid foundation for benchmarking and that a mixed methods approach built around thisa comprehensive and robust core of benchmark measures can have value to institutions; not just in external benchmarking but also in internal reviews. It can also assist with setting baselines, exploring the student experience, providing staff with data meaningful to their role and professional development together with supporting a continuous improvement trajectory

Resilience markers for safer systems and organisations

If computer systems are to be designed to foster resilient performance it is important to be able to identify contributors to resilience. The emerging practice of Resilience Engineering has identified that people are still a primary source of resilience, and that the design of distributed systems should provide ways of helping people and organisations to cope with complexity. Although resilience has been identified as a desired property, researchers and practitioners do not have a clear understanding of what manifestations of resilience look like. This paper discusses some examples of strategies that people can adopt that improve the resilience of a system. Critically, analysis reveals that the generation of these strategies is only possible if the system facilitates them. As an example, this paper discusses practices, such as reflection, that are known to encourage resilient behavior in people. Reflection allows systems to better prepare for oncoming demands. We show that contributors to the practice of reflection manifest themselves at different levels of abstraction: from individual strategies to practices in, for example, control room environments. The analysis of interaction at these levels enables resilient properties of a system to be ‘seen’, so that systems can be designed to explicitly support them. We then present an analysis of resilience at an organisational level within the nuclear domain. This highlights some of the challenges facing the Resilience Engineering approach and the need for using a collective language to articulate knowledge of resilient practices across domains

Identifying and appraising promising sources of UK clinical, health and social care data for use by NICE

This report aimed to aid the National Institute of Health and Care Excellence (NICE) in identifying opportunities for greater use of real-world data within its work. NICE identified five key ways in which real-world data was currently informing its work, or could do so in the future through: (i) researching the effectiveness of interventions or practice in real-world (UK) settings (ii) auditing the implementation of guidance (iii) providing information on resource use and evaluating the potential impact of guidance (iv) providing epidemiological information (v) providing information on current practice to inform the development of NICE quality standards. This report took a broad definition of ‘real-world’ data and created a map of UK sources, informed by a number of experts in real-world data, as well as a literature search, to highlight where some of the opportunities may lie for NICE within its clinical, public health and social care remit. The report was commissioned by the NICE, although the findings are likely to be of wider interest to a range of stakeholders interested in the role of real-world data in informing clinical, social care and public health decision-making. Most of the issues raised surrounding the use and appraisal of real-world data are likely to be generic, although the choice of datasets that were profiled in-depth reflected the interests of NICE. We discovered 275 sources that were named as real-world data sources for clinical, social care or public health investigation, 233 of which were deemed as active. The real-world data landscape therefore is highly complex and heterogeneous and composed of sources with different purposes, structures and collection methods. Some real-world data sources are purposefully either set-up or re-developed to enhance their data linkages and to examine the presence/absence/effectiveness of integrated patient care; however, such sources are in the minority. Furthermore, the small number of real-world data sources that are designed to enable the monitoring of care across providers, or at least have the capability to do so at a national level, have been utilised infrequently for this purpose in the literature. Data that offer the capacity to monitor transitions between health and social care do not currently exist at a national level, despite the increasing recognition of the interdependency between these sectors. Among the data sources we included, it was clear that no one data source represented a panacea for NICE’s real world data needs. This does highlight the merits and importance of data linkage projects and is suggestive of a need to triangulate evidence across different data, particularly in order to understand the feasibility and impact of guidance. There exists no overall catalogue or repository of real-world data sources for health, public health and social care, and previous initiatives aimed at creating such a resource have not been maintained. As much as there is a need for enhanced usage of the data, there is also a need for taking stock, integration, standardisation, and quality assurance of different sources. This research highlights a need for a systematic approach to creating an inventory of sources with detailed metadata and the funding to maintain this resource. This would represent an essential first step to support future initiatives aimed at enhancing the use of real-world data