User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

London SynEx Demonstrator Site: Impact Assessment Report

The key ingredients of the SynEx-UCL software components are: 1. A comprehensive and federated electronic healthcare record that can be used to reference or to store all of the necessary healthcare information acquired from a diverse range of clinical databases and patient-held devices. 2. A directory service component to provide a core persons demographic database to search for and authenticate staff users of the system and to anchor patient identification and connection to their federated healthcare record. 3. A clinical record schema management tool (Object Dictionary Client) that enables clinicians or engineers to define and export the data sets mapping to individual feeder systems. 4. An expansible set of clinical management algorithms that provide prompts to the patient or clinician to assist in the management of patient care. CHIME has built up over a decade of experience within Europe on the requirements and information models that are needed to underpin comprehensive multiprofessional electronic healthcare records. The resulting architecture models have influenced new European standards in this area, and CHIME has designed and built prototype EHCR components based on these models. The demonstrator systems described here utilise a directory service and object-oriented engineering approach, and support the secure, mobile and distributed access to federated healthcare records via web-based services. The design and implementation of these software components has been founded on a thorough analysis of the clinical, technical and ethico-legal requirements for comprehensive EHCR systems, published through previous project deliverables and in future planned papers. The clinical demonstrator site described in this report has provided the solid basis from which to establish "proof of concept" verification of the design approach, and a valuable opportunity to install, test and evaluate the results of the component engineering undertaken during the EC funded project. Inevitably, a number of practical implementation and deployment obstacles have been overcome through this journey, each of those having contributed to the time taken to deliver the components but also to the richness of the end products. UCL is fortunate that the Whittington Hospital, and the department of cardiovascular medicine in particular, is committed to a long-term vision built around this work. That vision, outlined within this report, is shared by the Camden and Islington Health Authority and by many other purchaser and provider organisations in the area, and by a number of industrial parties. They are collectively determined to support the Demonstrator Site as an ongoing project well beyond the life of the EC SynEx Project. This report, although a final report as far as the EC project is concerned, is really a description of the first phase in establishing a centre of healthcare excellence. New EC Fifth Framework project funding has already been approved to enable new and innovative technology solutions to be added to the work already established in north London

On the Deployment of Healthcare Applications over Fog Computing Infrastructure

Fog computing is considered as the most promising enhancement of the traditional cloud computing paradigm in order to handle potential issues introduced by the emerging Interned of Things (IoT) framework at the network edge. The heterogeneous nature, the extensive distribution and the hefty number of deployed IoT nodes will disrupt existing functional models, creating confusion. However, IoT will facilitate the rise of new applications, with automated healthcare monitoring platforms being amongst them. This paper presents the pillars of design for such applications, along with the evaluation of a working prototype that collects ECG traces from a tailor-made device and utilizes the patient's smartphone as a Fog gateway for securely sharing them to other authorized entities. This prototype will allow patients to share information to their physicians, monitor their health status independently and notify the authorities rapidly in emergency situations. Historical data will also be available for further analysis, towards identifying patterns that may improve medical diagnoses in the foreseeable future

Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

A SOA-Based Platform to Support Clinical Data Sharing

The eSource Data Interchange Group, part of the Clinical Data Interchange Standards Consortium, proposed five scenarios to guide stakeholders in the development of solutions for the capture of eSource data. The fifth scenario was subdivided into four tiers to adapt the functionality of electronic health records to support clinical research. In order to develop a system belonging to the \u201cInteroperable\u201d Tier, the authors decided to adopt the service-oriented architecture paradigm to support technical interoperability, Health Level Seven Version 3 messages combined with LOINC (Logical Observation Identifiers Names and Codes) vocabulary to ensure semantic interoperability, and Healthcare Services Specification Project standards to provide process interoperability. The developed architecture enhances the integration between patient-care practice and medical research, allowing clinical data sharing between two hospital information systems and four clinical data management systems/clinical registries. The core is formed by a set of standardized cloud services connected through standardized interfaces, involving client applications. The system was approved by a medical staff, since it reduces the workload for the management of clinical trials. Although this architecture can realize the \u201cInteroperable\u201d Tier, the current solution actually covers the \u201cConnected\u201d Tier, due to local hospital policy restrictions

Business intelligence and nosocomial infection decision making

Nosocomial infection prevention in healthcare units it is very important to improve patient’s well-being and safety. This prevention can be done by manipulating and analysing real data to identify critical processes and areas inside the healthcare unit, and monitoring indicators generated from data. The main goal of this paper is to evaluate the applicability of the Business Intelligence tools and concepts to healthcare and their performance as a Clinical Decision Support System, analyzing the evolution of nosocomial infection in the Centro Hospitalar do Porto, by defining a set of indicators that can help the nosocomial infection management and inducing Data Mining models to predict the occurrence of nosocomial infections (sensitivity of 91%). A Business Intelligence system composed by the presentation of a set of indicators and a Data Mining part capable of predict the occurrence of infection can provide important information to support healthcare professionals in their decisions.(undefined