Medical Informatics

Information technology has been revolutionizing the everyday life of the common man, while medical science has been making rapid strides in understanding disease mechanisms, developing diagnostic techniques and effecting successful treatment regimen, even for those cases which would have been classified as a poor prognosis a decade earlier. The confluence of information technology and biomedicine has brought into its ambit additional dimensions of computerized databases for patient conditions, revolutionizing the way health care and patient information is recorded, processed, interpreted and utilized for improving the quality of life. This book consists of seven chapters dealing with the three primary issues of medical information acquisition from a patient's and health care professional's perspective, translational approaches from a researcher's point of view, and finally the application potential as required by the clinicians/physician. The book covers modern issues in Information Technology, Bioinformatics Methods and Clinical Applications. The chapters describe the basic process of acquisition of information in a health system, recent technological developments in biomedicine and the realistic evaluation of medical informatics

Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of Semantic Web

UNIVERSITY OF LIÈGE, BELGIUM Executive Summary Faculty of Medicine Département Universitaire de Médecine Générale. Unité de recherche Soins Primaires et Santé Doctor in biomedical sciences Towards a system of concepts for Family Medicine. Multilingual indexing in General Practice/ Family Medicine in the era of SemanticWeb by Dr. Marc JAMOULLE Introduction This thesis is about giving visibility to the often overlooked work of family physicians and consequently, is about grey literature in General Practice and Family Medicine (GP/FM). It often seems that conference organizers do not think of GP/FM as a knowledge-producing discipline that deserves active dissemination. A conference is organized, but not much is done with the knowledge shared at these meetings. In turn, the knowledge cannot be reused or reapplied. This these is also about indexing. To find knowledge back, indexing is mandatory. We must prepare tools that will automatically index the thousands of abstracts that family doctors produce each year in various languages. And finally this work is about semantics1. It is an introduction to health terminologies, ontologies, semantic data, and linked open data. All are expressions of the next step: Semantic Web for health care data. Concepts, units of thought expressed by terms, will be our target and must have the ability to be expressed in multiple languages. In turn, three areas of knowledge are at stake in this study: (i) Family Medicine as a pillar of primary health care, (ii) computational linguistics, and (iii) health information systems. Aim • To identify knowledge produced by General practitioners (GPs) by improving annotation of grey literature in Primary Health Care • To propose an experimental indexing system, acting as draft for a standardized table of content of GP/GM • To improve the searchability of repositories for grey literature in GP/GM. 1For specific terms, see the Glossary page 257 x Methods The first step aimed to design the taxonomy by identifying relevant concepts in a compiled corpus of GP/FM texts. We have studied the concepts identified in nearly two thousand communications of GPs during conferences. The relevant concepts belong to the fields that are focusing on GP/FM activities (e.g. teaching, ethics, management or environmental hazard issues). The second step was the development of an on-line, multilingual, terminological resource for each category of the resulting taxonomy, named Q-Codes. We have designed this terminology in the form of a lightweight ontology, accessible on-line for readers and ready for use by computers of the semantic web. It is also fit for the Linked Open Data universe. Results We propose 182 Q-Codes in an on-line multilingual database (10 languages) (www.hetop.eu/Q) acting each as a filter for Medline. Q-Codes are also available under the form of Unique Resource Identifiers (URIs) and are exportable in Web Ontology Language (OWL). The International Classification of Primary Care (ICPC) is linked to Q-Codes in order to form the Core Content Classification in General Practice/Family Medicine (3CGP). So far, 3CGP is in use by humans in pedagogy, in bibliographic studies, in indexing congresses, master theses and other forms of grey literature in GP/FM. Use by computers is experimented in automatic classifiers, annotators and natural language processing. Discussion To the best of our knowledge, this is the first attempt to expand the ICPC coding system with an extension for family physician contextual issues, thus covering non-clinical content of practice. It remains to be proven that our proposed terminology will help in dealing with more complex systems, such as MeSH, to support information storage and retrieval activities. However, this exercise is proposed as a first step in the creation of an ontology of GP/FM and as an opening to the complex world of Semantic Web technologies. Conclusion We expect that the creation of this terminological resource for indexing abstracts and for facilitating Medline searches for general practitioners, researchers and students in medicine will reduce loss of knowledge in the domain of GP/FM. In addition, through better indexing of the grey literature (congress abstracts, master’s and doctoral theses), we hope to enhance the accessibility of research results and give visibility to the invisible work of family physicians

Design of a Controlled Language for Critical Infrastructures Protection

We describe a project for the construction of controlled language for critical infrastructures protection (CIP). This project originates from the need to coordinate and categorize the communications on CIP at the European level. These communications can be physically represented by official documents, reports on incidents, informal communications and plain e-mail. We explore the application of traditional library science tools for the construction of controlled languages in order to achieve our goal. Our starting point is an analogous work done during the sixties in the field of nuclear science known as the Euratom Thesaurus.JRC.G.6-Security technology assessmen

Impact of Terminology Mapping on Population Health Cohorts IMPaCt

Background and Objectives: The population health care delivery model uses phenotype algorithms in the electronic health record (EHR) system to identify patient cohorts targeted for clinical interventions such as laboratory tests, and procedures. The standard terminology used to identify disease cohorts may contribute to significant variation in error rates for patient inclusion or exclusion. The United States requires EHR systems to support two diagnosis terminologies, the International Classification of Disease (ICD) and the Systematized Nomenclature of Medicine (SNOMED). Terminology mapping enables the retrieval of diagnosis data using either terminology. There are no standards of practice by which to evaluate and report the operational characteristics of ICD and SNOMED value sets used to select patient groups for population health interventions. Establishing a best practice for terminology selection is a step forward in ensuring that the right patients receive the right intervention at the right time. The research question is, “How does the diagnosis retrieval terminology (ICD vs SNOMED) and terminology map maintenance impact population health cohorts?” Aim 1 and 2 explore this question, and Aim 3 informs practice and policy for population health programs. Methods Aim 1: Quantify impact of terminology choice (ICD vs SNOMED) ICD and SNOMED phenotype algorithms for diabetes, chronic kidney disease (CKD), and heart failure were developed using matched sets of codes from the Value Set Authority Center. The performance of the diagnosis-only phenotypes was compared to published reference standard that included diagnosis codes, laboratory results, procedures, and medications. Aim 2: Measure terminology maintenance impact on SNOMED cohorts For each disease state, the performance of a single SNOMED algorithm before and after terminology updates was evaluated in comparison to a reference standard to identify and quantify cohort changes introduced by terminology maintenance. Aim 3: Recommend methods for improving population health interventions The socio-technical model for studying health information technology was used to inform best practice for the use of population health interventions. Results Aim 1: ICD-10 value sets had better sensitivity than SNOMED for diabetes (.829, .662) and CKD (.242, .225) (N=201,713, p Aim 2: Following terminology maintenance the SNOMED algorithm for diabetes increased in sensitivity from (.662 to .683 (p Aim 3: Based on observed social and technical challenges to population health programs, including and in addition to the development and measurement of phenotypes, a practical method was proposed for population health intervention development and reporting

The Role of Tasks in the Internet Health Information Searching of Chinese Graduate Students

The purpose of the study was to examine the relationships between types of health information tasks and the Internet information search processes of Chinese graduate students at the University of North Texas. the participants' Internet information search processes were examined by looking at the source used to start the search, language selection, use of online translation tools, and time spent. in a computer classroom, 45 Chinese graduate students searched the Internet and completed three health information search tasks: factual task, interpretative task, and exploratory task. Data of the Chinese graduate students’ health information search processes were gathered from Web browser history files, answer sheets, and questionnaires. Parametric and non-parametric statistical analyses were conducted to test the relationships between the types of tasks and variables identified in the search process. Results showed that task types only had a statistically significant impact on the time spent. for the three tasks, the majority of Chinese graduate students used search engines as major sources for the search starting point, utilized English as the primary language, and did not use online translation tools. the participants also reported difficulties in locating relevant answers and recommended ways to be assisted in the future when searching the Internet for health information. the study provided an understanding of Chinese graduate students' health information seeking behavior with an aim to enrich health information user studies. the results of this study contribute to the areas of academic library services, multilingual health information system design, and task-based health information searching

MRC Population Data Archiving and Access Project

There are several important motivations for preserving research data: scientific, historical, economic, and legal. There is also significant demand for the re-use of population-based data in the medical research area, as usage of medical/health studies at the UK Data Archive (UKDA) show. This project investigated opportunities and barriers for the MRC in developing data archiving and access policy. Through case studies and interviews it sought to gain a better understanding of the range and variation of current MRC-funded data creation activities, the existing data management infrastructure and practice in MRC-funded contexts, and the views and opinions of those likely to be most affected by the establishment of such a policy

Disability resources for the educator

This thesis identifies what disability resources are currently accessible and needed by the educator in order to service the disabled student in the classroom. It is a compilation of medical, academic, financial and equipment resources currently available to the educator

Theory and Applications for Advanced Text Mining

Due to the growth of computer technologies and web technologies, we can easily collect and store large amounts of text data. We can believe that the data include useful knowledge. Text mining techniques have been studied aggressively in order to extract the knowledge from the data since late 1990s. Even if many important techniques have been developed, the text mining research field continues to expand for the needs arising from various application fields. This book is composed of 9 chapters introducing advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language. I believe that this book will give new knowledge in the text mining field and help many readers open their new research fields

HealthCyberMap: Mapping the Health Cyberspace Using Hypermedia GIS and Clinical Codes

HealthCyberMap () is a Semantic Web service for healthcare professionals and librarians, patients and the public m general that aims at mappmg parts of medical/ health information resources in cyberspace in novel ways to improve their retrieval and navigation. The Semantic Web ( and ) aims to be the next-generation World Wide Web by giving machine-readable semantics and context to the currently presentation-based Web pages. HealthCyberMap features an unconventional use of GIS (Geographic Information Systems) to map conceptual spaces occupied by collections of medical/ health information resources. Besides mapping the semantic and non-geographical aspects of these resources using suitable spatial metaphors, HealthCyberMap also collects and maps the geographical provenance of these resources. Some of HealthCyberMap Web interfaces are visual (maps for browsing resources by clinical/ health topic, by provenance and by type), while others are textual (multilingual interfaces for browsing resources by language, and a directory of topical resource categories, besides HealthCyberMap Semantic Subject Search Engine that goes beyond conventional free-text and keyword-based search engines, and supports synonyms, disease variants, subtypes, as well as some semantic relationships between terms). HealthCyberMap adopts a clinical metadata framework built upon a clinical coding scheme (vocabulary or ontology—ICD-9-CM* clinical classification in the current pilot service). Clinical coding schemes serve as a reliable common backbone for topical resource indexing, automated topical classification, topical visualisation and navigation of coded resource pools (using suitable metaphors), and enhanced information retrieval and linking. A resource metadata base based on Dublin Core metadata set with HealthCyberMap’s own extensions holds information about selected high-quality resources. HealthCyberMap then uses GIS spatialisation methods to generate interactive navigational cybermaps from the metadata base. These visual cybermaps are based on familiar metaphors for image-word association to give users a broad overview and understanding of what is available in this complex conceptual space of medical/ health Internet resources and help them navigate it more efficiently and effectively. HealthCyberMap cybermaps can be considered as semantically-spatialised, ontology-based browsing views of the underlying resource metadata base. Using a clinical coding scheme as a metric for spatialisation (“semantic distance”) is unique to HealthCyberMap and is very much suited for the semantic categorisation and navigation of medical/ health Internet information resources. HealthCyberMap also introduces a useful form of cyberspatial analysis for the detection of topical coverage gaps in its resource pool using choropleth (shaded) maps of human body systems. The project features a cost-effective method for serving Web hypermaps with dynamic metadata base drill-down functionality. It also demonstrates the feasibility of Electronic Patient Record to Online Information Services (like HealthCyberMap) Problem to Knowledge Linking using clinical codes as crisp problem-knowledge linkers or knowledge hooks. The Semantic Subject Search Engine queries the same HealthCyberMap resource metadata base. Explicit concepts in resource metadata map onto a brokering domain ontology (ICD-9-CM) allowing the search engine to infer implicit meanings (synonyms and semantic relationships) not directly mentioned in either the resource or its metadata. Similarly, user queries would map to the same ontology allowing the search engine to infer the implicit semantics of user queries and use them to optimise retrieval. A formative evaluation study of HealthCyberMap pilot service using an online user evaluation questionnaire, in addition to analysis of HealthCyberMap server transaction log, has been conducted during the period from 18 April 2002 to 1 June 2002 with very encouraging results. This two-method evaluation approach was guided by methodologies described in NIH Web Site Evaluation and Performance Measures Toolkit among other resources. Many exciting future possibilities have been also investigated by the author, including the further development of HealthCyberMap as a customisable, location-based medical/ health information service