PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 16779230

Developing a relational XML schema for sharing HIV clinical data.

D R Drozd·W B Lober·M M Kitahata·K I Smith·S E Van Rompaey
View original source ↗Export metadata ↓

Abstract

Access to multi-site clinical data regarding treatment and outcomes of HIV-infected patients in routine care is required to support clinical research to improve the treatment of HIV. As part of the NIAID-funded CFAR Network of Integrated Clinical Systems (CNICS), we have developed a relational XML Schema to extend the existing observational research repository and to integrate real-time clinical information from electronic medical records (EMRs) at six Centers for AIDS Research (CFAR) into the repository. The schema will aid the expansion of the research repository beyond the initial sites, and the development process may facilitate the use of multi-site repositories to study other chronic diseases.

Explore related subjects

Databases as TopicHIV InfectionsHumansInformation SystemsMedical Record LinkageMedical Records Systems, ComputerizedProgramming LanguagesUnited StatesJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

D R Drozd, W B Lober, M M Kitahata, K I Smith, S E Van Rompaey. 2005. Developing a relational XML schema for sharing HIV clinical data.. https://pubmed.ncbi.nlm.nih.gov/16779230/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

GI Epidemiology: databases for epidemiological studies.

BACKGROUND: Large databases are being increasingly used for examining the epidemiology and outcomes of digestive and liver disorders. The complexity and rigor of the methods used to conduct these studies are often underestimated. AIMS: For the most commonly used databases, we provide a brief description of the contents, highlight strengths and weakness, and provide links for more detailed information. We also present a systematic approach to utilizing large databases for addressing research questions, highlighting commonly encountered study design issues, as well as strategies for resolving these issues. CONCLUSIONS: 1. Research using large databases requires the same essential skills needed to conduct research studies using other data sources. These include a rigorous study design, expertise in analytic methods, and relevant research questions. 2. The completeness and accuracy of information contained in the database must be assessed. Methods for improving the quality and completeness of this information should be considered. 3. Despite similarities among large databases, gaining insight and experience into the structure and content of each database is essential. Key points *Large databases can be a powerful source of information to examine the clinical epidemiology and outcomes of digestive and liver disorders. * Research using large databases requires the same essential skills needed to conduct research studies using other data sources. These include a rigorous study design, expertise in analytic methods, and relevant research questions. * The completeness and accuracy of information contained in the database must be assessed. Methods for improving the quality and completeness of this information should be considered. * Despite similarities among large databases, gaining insight and experience into the structure and content of each database is essential. * Examples of commonly used large databases are presented with a synopsis of information contained in the database, as well as strengths and limitations of using the database for research.

Databases as Topic↗
PubMed2007

Italian Rett database and biobank.

Rett syndrome is the second most common cause of severe mental retardation in females, with an incidence of approximately 1 out of 10,000 live female births. In addition to the classic form, a number of Rett variants have been described. MECP2 gene mutations are responsible for about 90% of classic cases and for a lower percentage of variant cases. Recently, CDKL5 mutations have been identified in the early onset seizures variant and other atypical Rett patients. While the high percentage of MECP2 mutations in classic patients supports the hypothesis of a single disease gene, the low frequency of mutated variant cases suggests genetic heterogeneity. Since 1998, we have performed clinical evaluation and molecular analysis of a large number of Italian Rett patients. The Italian Rett Syndrome (RTT) database has been developed to share data and samples of our RTT collection with the scientific community (http://www.biobank.unisi.it). This is the first RTT database that has been connected with a biobank. It allows the user to immediately visualize the list of available RTT samples and, using the "Search by" tool, to rapidly select those with specific clinical and molecular features. By contacting bank curators, users can request the samples of interest for their studies. This database encourages collaboration projects with clinicians and researchers from around the world and provides important resources that will help to better define the pathogenic mechanisms underlying Rett syndrome.

Databases as Topic↗
PubMed2007

A database on treating drug addiction with traditional Chinese medicine.

AIMS: Traditional Chinese medicine (TCM) has been used to treat drug addiction for more than 160 years and valuable experiences have been accumulated with regard to patients' detoxification and rehabilitation. The aims of this project were (1) to establish a computerized, bilingual (Chinese-English) database on TCM for drug addiction; (2) to analyse the literature published in this field; and (3) to identify those Chinese herbs commonly used for drug addiction treatment. DESIGN: (1) Paper collection: related papers were collected through electronic databases and hand-searched materials; (2) data computerization: the Microsoft Access program and Delphi language were used as the major data management systems; (3) paper analysis: annual publications from 1989 to 2003 were classified and calculated; and (4) herbal analysis: the frequency of herbs used and herbal function categories were analysed. FINDINGS: (1) A special bilingual database that contained 340 works of professional literature, including 85 patent files on TCM for drug addiction, was established, in which more than 90% of the publications originated from mainland China; (2) the literature classification showed a significant increase in the number of publications on clinical and laboratory researches in this field over the past decade; (3) five functional categorizations of Chinese herbs and the 10 most frequently used Chinese herbs as well as three toxic herbs were identified from more than 200 herbs reported in 150 original research articles and 85 patent files. CONCLUSIONS: For the first time, the published data on TCM in the treatment of drug addiction were analysed systematically by using a new database. The results are invaluable for further laboratory and clinical studies to obtain more direct evidence.

Databases as Topic↗