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Aim\ud \ud We have limited understanding of which risk factors contribute to increased readmission rates amongst people discharged from hospital with diabetes. We aim to complete the first review of its kind, to identify, in a systematic way, known risk factors for hospital readmission amongst people with diabetes, in order to better understand this costly complication.\ud \ud Method\ud \ud The review was prospectively registered in the PROSPERO database. Risk factors were identified through systematic review of literature in PubMed, EMBASE & SCOPUS databases, performed independently by two authors prior to data extraction, with quality assessment and semi-quantitative synthesis according to PRISMA guidelines.\ud \ud Results\ud \ud Eighty-three studies were selected for inclusion, predominantly from the United States, and utilising retrospective analysis of local or regional data sets. 76 distinct statistically significant risk factors were identified across 48 studies. The most commonly identified risk factors were; co-morbidity burden, age, race and insurance type. Few studies conducted power calculations; unstandardized effect sizes were calculated for the majority of statistically significant risk factors.\ud \ud Conclusion\ud \ud This review is important in assessing the current state of the literature and in supporting development of interventions to reduce readmission risk. Furthermore, it provides an important foundation for development of rigorous, pre-specified risk prediction models.

Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans. We also report the results of usability studies carried out in four pilot sites by patients and clinicians., Graphical abstract Unlabelled Image

Enabling successful active ageing is an international priority to meet the challenges of increasing life expectancy. Digital strategies, such as telemedicine and e-health, offer the potential to deliver active ageing in a cost-effective manner at scale. This article aims to establish the extent to which the research literature considers e-health-based and telemedicine-based active ageing interventions. A systematic review was conducted according to PRISMA standards. Independently, two authors searched the Cochrane, EMBASE & CINAHL databases, with subsequent independent extraction and semi-quantitative analysis. We report a considerable breadth in digital active ageing research, which is truly international in its scope. There is a diverse range of both interventions and technologies, including a reassuring focus on community-based interventions. Whilst there are a number of quantitative studies, sample sizes are small, with a limited amount of statistical testing of the results. There is significant variation in the outcome measures reported and little consensus as to the most effective intervention strategies. Overall, whilst there is considerable breadth to the research published in the literature, there is a clear restriction in the depth of this research. There is little overall consensus. This lack of depth and consensus may be due to the need to recognize the important role of technical research elements alongside more traditional research methodologies, such as randomized controlled trials. Enabling both technical and clinical research methods to be recognized, in tandem, has enormous potential to support individuals, communities, clinicians and policy makers to make more informed decisions in relation to active ageing.

Objective\ud \ud The Learning Health System (LHS) requires integration of research into routine practice. ‘eSource’ or embedding clinical trial functionalities into routine electronic health record (EHR) systems has long been put forward as a solution to the rising costs of research. We aimed to create and validate an eSource solution that would be readily extensible as part of a LHS.\ud \ud Materials and Methods\ud \ud The EU FP7 TRANSFoRm project’s approach is based on dual modeling, using the Clinical Research Information Model (CRIM) and the Clinical Data Integration Model of meaning (CDIM) to bridge the gap between clinical and research data structures, using the CDISC Operational Data Model (ODM) standard. Validation against GCP requirements was conducted in a clinical site, and a cluster randomised evaluation by site nested into a live clinical trial.\ud \ud Results\ud \ud Using the form definition element of ODM, we linked precisely modelled data queries to data elements, constrained against CDIM concepts, to enable automated patient identification for specific protocols and pre-population of electronic case report forms (e-CRF). Both control and eSource sites recruited better than expected with no significant difference. Completeness of clinical forms was significantly improved by eSource, but Patient Related Outcome Measures (PROMs) were less well completed on smartphones than paper in this population.\ud \ud Discussion\ud \ud The TRANSFoRm approach provides an ontologically-based approach to eSource in a low-resource, heterogeneous, highly distributed environment, that allows precise prospective mapping of data elements in the EHR.\ud \ud Conclusion\ud \ud Further studies using this approach to CDISC should optimise the delivery of PROMS, whilst building a sustainable infrastructure for eSource with research networks, trials units and EHR vendors.

The transition from wakefulness into sleep is accompanied by modified activity in the brain's thalamocortical network. Sleep-related decreases in thalamocortical functional connectivity (FC) have previously been reported, but the extent to which these changes differ between thalamocortical pathways, and patterns of intra-thalamic FC during sleep remain untested. To non-invasively investigate thalamocortical and intra-thalamic FC as a function of sleep stage we recorded simultaneous EEG-fMRI data in 13 healthy participants during their descent into light sleep. Visual scoring of EEG data permitted sleep staging. We derived a functional thalamic parcellation during wakefulness by computing seed-based FC, measured between thalamic voxels and a set of pre-defined cortical regions. Sleep differentially affected FC between these distinct thalamic subdivisions and their associated cortical projections, with significant increases in FC during sleep restricted to sensorimotor connections. In contrast, intra-thalamic FC, both within and between functional thalamic subdivisions, showed significant increases with advancement into sleep. This work demonstrates the complexity and state-specific nature of functional thalamic relationships--both with the cortex and internally--over the sleep/wake cycle, and further highlights the importance of a thalamocortical focus in the study of sleep mechanisms.

Information flow between the thalamus and cerebral cortex is a crucial component of adaptive brain function, but the details of thalamocortical interactions in human subjects remain unclear. The principal aim of this study was to evaluate the agreement between functional thalamic network patterns, derived using seed-based connectivity analysis and independent component analysis (ICA) applied separately to resting state functional MRI (fMRI) data from 21 healthy participants. For the seed-based analysis, functional thalamic parcellation was achieved by computing functional connectivity (FC) between thalamic voxels and a set of pre-defined cortical regions. Thalamus-constrained ICA provided an alternative parcellation. Both FC analyses demonstrated plausible and comparable group-level thalamic subdivisions, in agreement with previous work. Quantitative assessment of the spatial overlap between FC thalamic segmentations, and comparison of each to a histological "gold-standard" thalamic atlas and a structurally-defined thalamic atlas, highlighted variations between them and, most notably, differences with both histological and structural results. Whilst deeper understanding of thalamocortical connectivity rests upon identification of features common to multiple non-invasive neuroimaging techniques (e.g. FC, structural connectivity and anatomical localisation of individual-specific nuclei), this work sheds further light on the functional organisation of the thalamus and the varying sensitivities of complementary analyses to resolve it.

To develop a model describing core concepts and principles of data flow, data privacy and confidentiality, in a simple and flexible way, using concise process descriptions and a diagrammatic notation applied to research workflow processes. The model should help to generate robust data privacy frameworks for research done with patient data.Based on an exploration of EU legal requirements for data protection and privacy, data access policies, and existing privacy frameworks of research projects, basic concepts and common processes were extracted, described and incorporated into a model with a formal graphical representation and a standardised notation. The Unified Modelling Language (UML) notation was enriched by workflow and own symbols to enable the representation of extended data flow requirements, data privacy and data security requirements, privacy enhancing techniques (PET) and to allow privacy threat analysis for research scenarios.Our model is built upon the concept of three privacy zones (Care Zone, Non-care Zone and Research Zone) containing databases, data transformation operators, such as data linkers and privacy filters. Using these model components, a risk gradient for moving data from a zone of high risk for patient identification to a zone of low risk can be described. The model was applied to the analysis of data flows in several general clinical research use cases and two research scenarios from the TRANSFoRm project (e.g., finding patients for clinical research and linkage of databases). The model was validated by representing research done with the NIVEL Primary Care Database in the Netherlands.The model allows analysis of data privacy and confidentiality issues for research with patient data in a structured way and provides a framework to specify a privacy compliant data flow, to communicate privacy requirements and to identify weak points for an adequate implementation of data privacy.

Introduction: Low grade gliomas are the commonest brain tumours in children but present in a myriad of ways, each with its own treatment challenges. Conventional MRI scans play an important role in their management but have limited ability to identify likely clinical behaviour. The aim of this study is to investigate 1H magnetic resonance spectroscopy (MRS) as a method for detecting differences between the various low grade gliomas and related tumours in children. Patients and methods: Short echo time single voxel 1H MRS at 1.5 or 3.0 T was performed prior to treatment on children with low grade brain tumours at two centres and five MR scanners, 69 cases had data which passed quality control. MRS data was processed using LCModel to give mean spectra and metabolite concentrations which were compared using T-tests, ANOVA, Receiver Operator Characteristic curves and logistic regression in SPSS. Results: Significant differences were found in concentrations of key metabolites between glioneuronal and glial tumours (T-test p < 0.05) and between most of the individual histological subtypes of low grade gliomas. The discriminatory metabolites identified, such as choline and myoinositol, are known tumour biomarkers. In the set of pilocytic astrocytomas and unbiopsied optic pathway gliomas, significant differences (p < 0.05, ANOVA) were found in metabolite profiles of tumours depending on location and patient neurofibromatosis type 1 status. Logistic regression analyses yielded equations which could be used to assess the probability of a tumour being of a specific type. Conclusions: MRS can detect subtle differences between low grade brain tumours in children and should form part of the clinical assessment of these tumours.

Metabolic pathway diagrams provide a wealth of information on how reactions combine to perform biological functions. While pathway diagrams are arranged in a way that allows a specific area of metabolism to be visualised, the inherent complexity of each pathway makes it difficult to identify the sets of reactions linking groups of compounds; a common task for researchers attempting to explain observed correlations or looking for further compounds of potential interest to use in validation work. Here we introduce Linked Metabolites, a tool that identifies sets of reactions linking groups of compounds in the context of the KEGG pathway diagrams.

Background Pilocytic astrocytomas (PA) are common childhood brain tumours whose management and prognosis vary widely depending on location. 1 H magnetic resonance spectroscopy (MRS) measures biochemistry in vivo and shows promise for characterising brain tumours and aiding management. Methods Single voxel MRS (1.5 Tesla, TE 30 ms, TR 1500 ms) was performed on 27 children with PAs. Cases were designated ‘progressors’ if tumour progression led to their clinical management plan being altered. Results Prior to treatment, supratentorial tumours had significantly higher myo-inositol ( p t -test) and glutamate plus glutamine ( p = 0.02, t -test) than cerebellar tumours. Optic pathway or thalamic tumours that progressed had a significantly ( p = 0.04, t -test) lower myo-inositol at initial MRS than those with stable disease. Myo-inositol levels decreased significantly in progressors between the initial and subsequent MRS ( p = 0.03, paired t -test). Changes in myo-inositol occurred before clinical and radiological progression. Conclusions MRS identifies differences with anatomical location in PAs and yields potential non-invasive biomarkers of prognosis.

Virtual Reality Modelling Language (VRML) is the start of a new era for medicine and the World Wide Web (WWW). Scientists can use VRML across the Internet to explore new three-dimensional (3D) worlds, share concepts and collaborate together in a virtual environment. VRML enables the generation of virtual environments through the use of geometric, spatial and colour data structures to represent 3D objects and scenes. In medicine, researchers often want to interact with scientific data, which in several instances may also be dynamic (e.g. MRI data). This data is often very large and is difficult to visualise. A 3D graphical representation can make the information contained in such large data sets more understandable and easier to interpret. Fast networks and satellites can reliably transfer large data sets from computer to computer. This has led to the adoption of remote tale-working in many applications including medical applications. Radiology experts, for example, can view and inspect in near real-time a 3D data set acquired from a patient who is in another part of the world. Such technology is destined to improve the quality of life for many people. This paper introduces VRML (including some technical details) and discusses the advantages of VRML in application developing.

A database system, incorporating smartcard technologies, was designed to hold the personal and pacing details of pacemaker patients, who attended a clinic at the Royal Sussex County Hospital (RSCH), Brighton, UK. Following an initial period of a 12 month clinical trial, with the database running on a standalone personal computer, the Pacemaker Patient Database has been redesigned and implemented as an intranet-based system. This paper describes the issues relating to the development of the new prototype system and identifies the design principles for intranet-based electronic health care (EHCR) record database systems.

Digital Medical Libraries. DL1 Medical image libraries: a vision for the future (S. Morris). DL2 Digital libraries - a quality concept (F. Norman). DL3 MIDRIB - A comprehensive medical images database (J. Szuscikiewicz). DL4 Indexing the Web? A Comparative study of three medical Web servers on the Internet: CliniWeb, Diseases, Disorders and Related Topics, OMNI (S. J. Darmoni and B. Thirion). DL5 The role of the Internet in medical decision making (M. Anderson, H. Moazamipour, D. Hudson and M. Cohen). Electronic Publishing in Medicine. EP1 Non-indexed medical journals in the Web: new perspectives in the medical literature (A. E. Germenis, P. A. Kokkinides and C. Stavropoulos-Giokas). EP2 Networking the neurological charities (T. Kelly and A. Billington). EP3 EQUIP Magazine on the World Wide Web (M. North). EP4 Electronic publishing over the Internet: an extension of research workshops (J. M. Jenkins). EP5 Casting our Net: transforming a hospital house journal into an electronic version for simultaneous publication on the World Wide Web (H. Gaston, S-A. Morley, C. Baldock). Medical Education. ME1 Telemedicine and the Internet: their role in continuing medical education (S. Groves-Phillips). ME2 A systematic methodology for assessing WWW medical education materials (E. Berry, C. Parker-Jones, R. G. Jones, P. J. R. Harkin, H. O. Horsfall, J. A. Nicholls and N. J. A. Cook). ME3 A cognitive apprenticeship approach to teaching medicine on the World Wide Web (Z. Al-Rawahi and M. Sharples). ME4 The present and future role of the Internet in undergraduate and postgraduate medical education (A. Colman, R. Hollingsworth and B. Richards). ME5 Virtual Medical Laboratory (G. H. Alusi, A. C. Tan, A. Linney, and A. Wright). ME6 Interactive intranet tutoring for medical image processing (T. N. Arvanitis, N. Papadopoulos, C. Baldock, and D. Watson). 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TM2 Clinical evaluation of new teleradiology systems and concepts (M. Walz, K-J. Lehmann, R. Loose, R. Bolte, M. Schinkmann, G. Weisser, T. Hothorn, and M. Georgi). TM3 European Healthcare Telematics Observatory (G. De Moor, M. McCurry, M. Laires, and C. Thayer). Information Policies and Ethical Issues IP1 Official vs unofficial outbreak reporting through the Internet (J. Woodall). IP2 Lessons learned from the development of an Applications Tracking System in the pharmaceutical regulatory sector (A. Zenie, F. Argentesi, and K. de Neef). Internet Security IS1 Internet security: the myth of secure networking (S. Kingston). IS2 Security measures in open communication systems (R. Hanka, and I. E. Buchan). IS3 Security management in the medical environment (G. Butler, N. Jayaram and P. Morse). IS4 Models and issues in sharing health and social care data (P. A. Dearnley, and D. J. Smith). Access to Health and Medical Information AM1 Perspectives of a MEDINFONET (N. Jayaram and P. Morse). AM2 Evaluating the options for developing databases to support research-based medicine at the NHS Centre for Reviews and Dissemination (J. Glanville, and I. Smith). AM3 Health On the Net automated database of health and medical information (C. Boyer, O. Baujard, V. Baujard, S. Aurel, M. Selby, and R. D. Appel). AM4 BASCD surveys and computer communication (Z. J. Nugent). AM5 Experience of a local hospital with the Internet - Brighton Health Care NHS Trust World-Wide-Web pages (C. Baldock). AM6 HealthGate: Toward an access interface platform for health information networks (A. Alcolea, F. del Pozo, and E. J. Gomez). AM7 Orthopaedic Information on the Internet (J. F. M. Clough). AM8 WWW access to radiological database using ACR index, Java/JavaScript and mSQL (T. Hothorn, M. Walz, J. Stahl, A. Bode, K. J. Lehmann, T. Werny, M. Schinkmann, R. Loose, and M. Georgi). AM9 Virtual Workspaces in I2Cnet (C. Chronaki, M. Tsiknakis, and S. Orphanoudakis). AM10 Using the Internet to support Celiacs: a case study based on US and UK samples (D. J. Brunner). AM11 Exchanging clinical knowledge via Internet (I. E. Buchan, and R. Hanka). Clinical Applications on the World Wide Web CA1 Demonstrating minimal invasive therapy over the Internet (R. Bennett, and P. T. Kirstein). CA2 An intranet database for pacemaker patients (R. A. Smith, T. N. Arvanitis, M. English, and R. Vincent). CA3 A heart sound Internet resource (J. E. Hebden, J. N. Torry, A. Haghighi-Mood, B. Tovar Corona, and B. Altabsheh). CA4 The Anaesthesia crtical incident reporting system: an experience based database (S. Staender, J. Davies, B. Helmreich, B. Sexton, and M. Kaufmann). CA5 Exploring novel chemotherapy treatments using the WWW (J. Boyle, D. Henderson, J. McCall, H. McLeod, and J. Usher). CA6 The Internet: a new patient recruitment resource (K. A. Getz). CA7 DESIRE for medical research (B. Loughlin, and G. Kernohan). CA8 The BSPE Web page: a means of research co-ordination, disease notification and Society housekeeping (S. D. North, J. K. H. Wales, and X. M. Shou). CA9 World Wide Web interface for advanced SPECT reconstruction algorithms implemented on a remote massively parallel computer (A. R. Formiconi, A. Passeri, M. R. Guelfi, M. Masoni, A. Pupi, U. Meldolesi, P. Malfetti, L. Calori, and A. Guidazzoli). CA10 Computer assisted medical diagnosis using the Web (L-P. Seka, A. Fresnel, D. Delamare, C. Riou, B. Pouliquen, R. Duvauferrier, and P. Le Beux). CA11 The Internet and randomised controlled trials (M. A. Kelly, and J. Oldham). CA12 A WWW-accessible knowledge base for the interpretation of hepatitis serologic tests (C. Chizzali-Bonfadin, K-P. Adlassnig, M. Kreihsl, A. Hatvan, and W. Horak). CA13 An Internet service for manipulating 3D models of human organs reconstructed from computer tomography and magnetic resonance imaging (G. Clapworthy, M. Krokos, and N. Vasilonikolidakis).