Clinical foundations and information architecture for the implementation of a federated health record service

Clinical care increasingly requires healthcare professionals to access patient record information that may be distributed across multiple sites, held in a variety of paper and electronic formats, and represented as mixtures of narrative, structured, coded and multi-media entries. A longitudinal person-centred electronic health record (EHR) is a much-anticipated solution to this problem, but its realisation is proving to be a long and complex journey. This Thesis explores the history and evolution of clinical information systems, and establishes a set of clinical and ethico-legal requirements for a generic EHR server. A federation approach (FHR) to harmonising distributed heterogeneous electronic clinical databases is advocated as the basis for meeting these requirements. A set of information models and middleware services, needed to implement a Federated Health Record server, are then described, thereby supporting access by clinical applications to a distributed set of feeder systems holding patient record information. The overall information architecture thus defined provides a generic means of combining such feeder system data to create a virtual electronic health record. Active collaboration in a wide range of clinical contexts, across the whole of Europe, has been central to the evolution of the approach taken. A federated health record server based on this architecture has been implemented by the author and colleagues and deployed in a live clinical environment in the Department of Cardiovascular Medicine at the Whittington Hospital in North London. This implementation experience has fed back into the conceptual development of the approach and has provided "proof-of-concept" verification of its completeness and practical utility. This research has benefited from collaboration with a wide range of healthcare sites, informatics organisations and industry across Europe though several EU Health Telematics projects: GEHR, Synapses, EHCR-SupA, SynEx, Medicate and 6WINIT. The information models published here have been placed in the public domain and have substantially contributed to two generations of CEN health informatics standards, including CEN TC/251 ENV 13606

Consolidated List of Requirements

This document is a consolidated catalogue of requirements for the Electronic Health Care Record (EHCR) and Electronic Health Care Record Architecture (EHCRA), gleaned largely from work done in the EU Framework III and IV programmes and CEN, but also including input from other sources including world-wide standardisation initiatives. The document brings together the relevant work done into a classified inventory of requirements to inform the on-going standardisation process as well as act as a guide to future implementation of EHCRA-based systems. It is meant as a contribution both to understanding of the standard and to the work that is being considered to improve the standard. Major features include the classification into issues affecting the Health Care Record, the EHCR, EHCR processing, EHCR interchange and the sharing of health care information and EHCR systems. The principal information sources are described briefly. It is offered as documentation that is complementary to the four documents of the ENV 13606 Parts I-IV produced by CEN Pts 26,27,28,29. The requirements identified and classified in this deliverable are referenced in other deliverables

The online multi-agency support barometer

This report presents the findings of a small feasibility study which sought to investigate the use of an online risk management Barometer. The barometer was developed with a view to helping multiple agencies communicate about vulnerable and 'at risk' patients within mental health settings.The Barometer is an online tool which allows staff from multiple agencies to access and share information with other staff if a patient is at risk.The key aims and objectives of this small research project were i) to evaluating how professionals felt about their current risk assessment tools, ii) to assess the ease of use and the relevance of questions within the Barometer tool and iii) to discuss some potential modifications/problem areas of incorporating the Barometer tool within mental health services and across a multi-disciplinary perspective.The research was conducted in three mental services within the South Essex Partnership Trust (2 x CAMHS and 2 x Adult Services) using a mixed-methods approach

Special Libraries, May-June 1957

Volume 48, Issue 5https://scholarworks.sjsu.edu/sla_sl_1957/1004/thumbnail.jp

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.Siirretty Doriast

Clinical trial metadata:Defining and extracting metadata on the design, conduct, results and costs of 125 randomised clinical trials funded by the National Institute for Health Research Health Technology Assessment programme

Background:  By 2011, the Health Technology Assessment (HTA) programme had published the results of over 100 trials with another 220 in progress. The aim of the project was to develop and pilot ‘metadata’ on clinical trials funded by the HTA programme.   Objectives: The aim of the project was to develop and pilot questions describing clinical trials funded by the HTA programme in terms of it meeting the needs of the NHS with scientifically robust studies. The objectives were to develop relevant classification systems and definitions for use in answering relevant questions and to assess their utility.   Data sources: Published monographs and internal HTA documents.   Review methods: A database was developed, ‘populated’ using retrospective data and used to answer questions under six prespecified themes. Questions were screened for feasibility in terms of data availability and/or ease of extraction. Answers were assessed by the authors in terms of completeness, success of the classification system used and resources required. Each question was scored to be retained, amended or dropped.    Results: One hundred and twenty-five randomised trials were included in the database from 109 monographs. Neither the International Standard Randomised Controlled Trial Number nor the term ‘randomised trial’ in the title proved a reliable way of identifying randomised trials. Only limited data were available on how the trials aimed to meet the needs of the NHS. Most trials were shown to follow their protocols but updates were often necessary as hardly any trials recruited as planned. Details were often lacking on planned statistical analyses, but we did not have access to the relevant statistical plans. Almost all the trials reported on cost-effectiveness, often in terms of both the primary outcome and quality-adjusted life-years. The cost of trials was shown to depend on the number of centres and the duration of the trial. Of the 78 questions explored, 61 were well answered, 33 fully with 28 requiring amendment were the analysis updated. The other 17 could not be answered with readily available data.   Limitations: The study was limited by being confined to 125 randomised trials by one funder.   Conclusions: Metadata on randomised controlled trials can be expanded to include aspects of design, performance, results and costs. The HTA programme should continue and extend the work reported here