Database Management Systems

Large databases can be a rich source of clinical and administrative information on broad populations. These datasets are characterized by demographic and clinical data for over 1000 patients from multiple institutions. Since they are often collected and funded for other purposes, their use for secondary analysis increases their utility at relatively low costs. Advantages of large databases as a source include the very large numbers of available patients and their related medical information. Disadvantages include lack of detailed clinical information and absence of causal descriptions.

OBJECTIVE: Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS).

OBJECTIVE: Multi-site data collection is complex and requires an effective data management system. This article explores data management issues encountered in the design, conduct, and analysis of a research project involving 74 community-based sites and a central data management system. RESULTS: Once the data arrived at the central site, data integrity was maintained at a very high level. Issues encountered in our study on low back pain reflected the practice-based nature of the study and the limitations of finances, staff, and facilities.

BACKGROUND: Federally funded national surveys are routinely conducted to provide reliable, valid, and relevant data on health and health care, and these "public-use" survey data are typically made available for further study by the wider scientific community. The full potential for using such data to examine the delivery, utilization, organization, and costs of chiropractic or complementary/alternative (CAM) health care remains largely untapped.

OBJECTIVE: Multi-site data collection is complex and requires an effective data management system. This article explores data management issues encountered in the design, conduct, and analysis of a research project involving 74 community-based sites and a central data management system. RESULTS: Once the data arrived at the central site, data integrity was maintained at a very high level. Issues encountered in our study on low back pain reflected the practice-based nature of the study and the limitations of finances, staff, and facilities.

BACKGROUND: Federally funded national surveys are routinely conducted to provide reliable, valid, and relevant data on health and health care, and these "public-use" survey data are typically made available for further study by the wider scientific community. The full potential for using such data to examine the delivery, utilization, organization, and costs of chiropractic or complementary/alternative (CAM) health care remains largely untapped.

BACKGROUND: Recent advances in Web and information technologies with the increasing decentralization of organizational structures have resulted in massive amounts of information resources and domain-specific services in Traditional Chinese Medicine. The massive volume and diversity of information and services available have made it difficult to achieve seamless and interoperable e-Science for knowledge-intensive disciplines like TCM. Therefore, information integration and service coordination are two major challenges in e-Science for TCM.

As a form of important domain knowledge, large-scale ontologies play a critical role in building a large variety of knowledge-based systems. To overcome the problem of semantic heterogeneity and encode domain knowledge in reusable format, a large-scale and well-defined ontology is also required in the traditional Chinese medicine discipline. We argue that to meet the on-demand and scalability requirement ontology-based systems should go beyond the use of static ontology and be able to self-evolve and specialize for the domain knowledge they possess.

BACKGROUND: Traditional Chinese Medicine (TCM), a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature.