DW4TR: A Data Warehouse for Translational Research

Abstract

The linkage between the clinical and laboratory research domains is a key issue in translational research. Integration of clinicopathologic data alone is a major task given the number of data elements involved. For a translational research environment, it is critical to make these data usable at the point-of-need. Individual systems have been developed to meet the needs of particular projects though the need for a generalizable system has been recognized. Increased use of Electronic Medical Record data in translational research will demand generalizing the system for integrating clinical data to support the study of a broad range of human diseases. To ultimately satisfy these needs, we have developed a system to support multiple translational research projects. This system, the Data Warehouse for Translational Research (DW4TR), is based on a light-weight, patient-centric modularly-structured clinical data model and a specimen-centric molecular data model. The temporal relationships of the data are also part of the model. The data are accessed through an interface composed of an Aggregated Biomedical-Information Browser (ABB) and an Individual Subject Information Viewer (ISIV) which target general users. The system was developed to support a breast cancer translational research program and has been extended to support a gynecological disease program. Further extensions of the DW4TR are underway. We believe that the DW4TR will play an important role in translational research across multiple disease types.

How can clinical biobanks and patient information be adapted for research – Establishing a hospital based data warehouse solution

“…The data warehouse model as such shares many similarities with other models (4)(5)(6)(7)(8). As noted by Lyman and colleagues, the design of an integrated data warehouse is a resource-intensive process requiring a multidisciplinary approach and substantial investments of time and energy (7).…”

“…In order to extract existing electronic data for secondary quality and research purposes in a timely, efficient and secure way, several organizations propose the establishment of a data warehouse (4)(5)(6)(7)(8). A data warehouse can be defined as "a copy of transaction data specifically structured for query and analysis" (see ref.…”

Modelling of Cancer Patient Records: A Structured Approach to Data Mining and Visual Analytics

“…Case studies include one from Stolba and Tjoa [23], who used a clinical evidence-based process model for the generation of treatment rules. Another example, the Data Warehouse for Translational Research (DW4TR), has been developed to support breast cancer translational research in the USA and this has been extended to support a gynaecological disease programme [7].…”

Archetype-based data warehouse environment to enable the reuse of electronic health record data

“…Recently, DW infrastructures for reuse of information have been proposed [56][57][58]. However, to the best of the authors' knowledge, these systems were to be used inside one organization and not based in clinical information architecture standards.…”

“…However, to the best of the authors' knowledge, these systems were to be used inside one organization and not based in clinical information architecture standards. For example, Hu et al [56] relied on ontologies and clinical terminologies as SNOMED-CT to model clinical concepts. This is useful when the structure of the concept is known inside one organization but might be inaccurate for data reuse across several organizations or levels of the health care system, since the structure of information is unknown.…”