Mapping the rules: conceptual and logical relationships in a system for pediatric clinical decision support

The Child Health Improvement through Computer Automation (CHICA) system uses evidence-based guidelines and information collected in the clinic and stored in an electronic medical record (EMR) to inform physician and patient decision making. CHICA helps physicians to identify and select relevant screenings and also provides personalized, just-in-time information for patients. This system relies on a database of Medical Logic Modules (MLMS) written in the Arden Rules syntax. These MLMs store observations (StorObs) during the clinical encounter which trigger potential screenings and preventive health interventions for discussion with the patient or for follow up at the next visit. This poster shows how informationists worked with the CHICA team to describe the MLMs using standard vocabularies, including Medical Subject Headings (MeSH) and Logical Observation Identifiers Names and Codes (LOINC). After assigning keywords to the database of MLMs, the informationists used visualization tools to generate maps. These maps show how rules are related by logic (shared StorObs) and by concept (shared vocabulary). The CHICA team will use these maps to identify gaps in the clinical decision support database and (if needed) to develop rules which bridge related but currently isolated concepts.NIH 1R01LM010923-0

Surface-antigen expression profiling of B cell chronic lymphocytic leukemia: from the signature of specific disease subsets to the identification of markers with prognostic relevance

Studies of gene expression profiling have been successfully used for the identification of molecules to be employed as potential prognosticators. In analogy with gene expression profiling, we have recently proposed a novel method to identify the immunophenotypic signature of B-cell chronic lymphocytic leukemia subsets with different prognosis, named surface-antigen expression profiling. According to this approach, surface marker expression data can be analysed by data mining tools identical to those employed in gene expression profiling studies, including unsupervised and supervised algorithms, with the aim of identifying the immunophenotypic signature of B-cell chronic lymphocytic leukemia subsets with different prognosis. Here we provide an overview of the overall strategy employed for the development of such an "outcome class-predictor" based on surface-antigen expression signatures. In addition, we will also discuss how to transfer the obtained information into the routine clinical practice by providing a flow-chart indicating how to select the most relevant antigens and build-up a prognostic scoring system by weighing each antigen according to its predictive power. Although referred to B-cell chronic lymphocytic leukemia, the methodology discussed here can be also useful in the study of diseases other than B-cell chronic lymphocytic leukemia, when the purpose is to identify novel prognostic determinants

EN-BIRTH Data Collector Training - Handbook and Manual

The EN-BIRTH study aims to validate selected newborn and maternal indicators for routine facility-based tracking of coverage and quality of care for use at district, national and global levels. The item contains the EN-BIRTH_Trainer's Manual (14 June 2017) and EN-BIRTH_Training Handbook (23 May 2017)

TREatment of ATopic eczema (TREAT) Registry Taskforce: consensus on how and when to measure the core dataset for atopic eczema treatment research registries.

BackgroundComparative, real-life and long-term evidence on the effectiveness and safety of phototherapy and systemic therapy in moderate-to-severe atopic eczema (AE) is limited. Such data must come from well-designed prospective patient registries. Standardization of data collection is needed for direct comparisons and data pooling.ObjectivesTo reach a consensus on how and when to measure the previously defined domain items of the TREatment of ATopic eczema (TREAT) Registry Taskforce core dataset for research registries for paediatric and adult patients with AE.MethodsProposals for the measurement instruments were based on recommendations of the Harmonising Outcome Measures for Eczema (HOME) initiative, the existing AE database of TREATgermany, systematic reviews of the literature and expert opinions. The proposals were discussed at three face-to-face consensus meetings, one teleconference and via e-mail. The frequency of follow-up visits was determined by an expert survey.ResultsA total of 16 experts from seven countries participated in the 'how to measure' consensus process and 12 external experts were consulted. A consensus was reached for all domain items on how they should be measured by assigning measurement instruments. A minimum follow-up frequency of initially 4 weeks after commencing treatment, then every 3 months while on treatment and every 6 months while off treatment was defined.ConclusionsThis core dataset for national AE research registries will aid in the comparability and pooling of data across centres and country borders, and enables international collaboration to assess the long-term effectiveness and safety of phototherapy and systemic therapy used in patients with AE. What's already known about this topic? Comparable, real-life and long-term data on the effectiveness and safety of phototherapy and systemic therapy in patients with atopic eczema (AE) are needed. There is a high diversity of outcomes and instruments used in AE research, which require harmonization to enhance comparability and allow data pooling. What does this study add? Our taskforce has reached international consensus on how and when to measure core domain items for national AE research registries. This core dataset is now available for use by researchers worldwide and will aid in the collection of unified data. What are the clinical implications of this work? The data collected through this core dataset will help to gain better insights into the long-term effectiveness and safety of phototherapy and systemic therapy in AE and will provide important information for clinical practice. Standardization of such data collection at the national level will also allow direct data comparisons and pooling across country borders (e.g. in the analysis of treatment-related adverse events that require large patient numbers)

The Role Of Local Authorities In Health Issues: A Policy Document Analysis

Prior to the passing of the Health and Social Care Act 2012 the Communities and Local Government (CLG) Select Committee conducted an investigation into the proposed changes to the Public Health System in England. The Committee considered 40 written submissions and heard oral evidence from 26 expert witnesses. Their report, which included complete transcripts of both oral and written submissions, provided a rich and informed data on which to base an analysis of the proposed new public health system. This report analyses the main themes that emerged from the evidence submissions and forms part of our preliminary work for PRUComm’s PHOENIX project examining the development of the new public health system

Data privacy by design: digital infrastructures for clinical collaborations

The clinical sciences have arguably the most stringent security demands on the adoption and roll-out of collaborative e-Infrastructure solutions such as those based upon Grid-based middleware. Experiences from the Medical Research Council (MRC) funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project and numerous other real world security driven projects at the UK e-Science National e-Science Centre (NeSC – www.nesc.ac.uk) have shown that whilst advanced Grid security and middleware solutions now offer capabilities to address many of the distributed data and security challenges in the clinical domain, the real clinical world as typified by organizations such as the National Health Service (NHS) in the UK are extremely wary of adoption of such technologies: firewalls; ethics; information governance, software validation, and the actual realities of existing infrastructures need to be considered from the outset. Based on these experiences we present a novel data linkage and anonymisation infrastructure that has been developed with close co-operation of the various stakeholders in the clinical domain (including the NHS) that addresses their concerns and satisfies the needs of the academic clinical research community. We demonstrate the implementation of this infrastructure through a representative clinical study on chronic diseases in Scotland