Journal: JMIR Formative Research
Article Title: What You Need to Know Before Implementing a Clinical Research Data Warehouse: Comparative Review of Integrated Data Repositories in Health Care Institutions
doi: 10.2196/17687
Figure Lengend Snippet: Common data types across IDRs. Columns show the main types of data collected in the selected IDRs. Gray-filled cells denote feature presence, with colors classifying the IDRs based on the examined architectures. Only 19 IDR articles contained enough information in their articles to be included in this figure. BRP: biorepository portal; BTRIS: biomedical translational research information system; CARPEM: cancer research for personalized medicine; CLB-IT: Léon Bérard Cancer Center Information Technology; DW4TR: Data Warehouse for Translational Research; EHR: electronic health record; HEGP: Hôpital Européen Georges Pompidou; HERON: health care enterprise repository for ontological narration; HSSC: Health Science, South Carolina; IDRs: integrated data repositories; Mayo Clinic-TRC: Mayo Clinic – Translational Research Center; METEOR: Methodist Environment for Translational Enhancement and Outcome Research; MIDH: Maternal and Infant Data Hub; MOSAIC: models and simulation techniques for discovering diabetes-related factors; Onco-i2b2; PHIS+: Pediatric Health Information System+; STARR: STAnford Research Repository; VUMC-BioVU: Vanderbilt University Medical Center–BioVU; VUMC-SD: Vanderbilt University Medical Center–Synthetic Derivative.
Article Snippet: On the basis of our analysis, we highlight the following guiding principles for small- to medium-sized institutions planning to implement an IDR: Commercial electronic medical record platforms such as Epic, Cerner, Meditech, and Allscripts are dominant in large institutions.
Techniques: Clinical Proteomics