The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
The DEDUCE Guided Query tool: Providing simplified access to clinical data for research and quality improvement
Open accessAbstract
In many healthcare organizations, comparative effectiveness research and quality improvement (QI) investigations are hampered by a lack of access to data created as a byproduct of patient care. Data collection often hinges upon either manual chart review or ad hoc requests to technical experts who support legacy clinical systems. In order to facilitate this needed capacity for data exploration at our institution (Duke University Health System), we have designed and deployed a robust Web application for cohort identification and data extraction—the Duke Enterprise Data Unified Content Explorer (DEDUCE). DEDUCE is envisioned as a simple, web-based environment that allows investigators access to administrative, financial, and clinical information generated during patient care. By using business intelligence tools to create a view into Duke Medicine's enterprise data warehouse, DEDUCE provides a guided query functionality using a wizard-like interface that lets users filter through millions of clinical records, explore aggregate reports, and, export extracts. Researchers and QI specialists can obtain detailed patient- and observation-level extracts without needing to understand structured query language or the underlying database model. Developers designing such tools must devote sufficient training and develop application safeguards to ensure that patient-centered clinical researchers understand when observation-level extracts should be used. This may mitigate the risk of data being misunderstood and consequently used in an improper fashion.
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Harris, P. A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., & Conde, J. G. (2009) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2008.08.010 · Cited by 51,384
Prokosch, H. (2009) · doi:10.3414/me9132 · Cited by 262
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Osho, A. A., Castleberry, A. W., Yerokun, B. A., Mulvihill, M. S., Rucker, J., Snyder, L. D., Davis, R. D., & Hartwig, M. G. (2017) · The Journal of Heart and Lung Transplantation · doi:10.1016/j.healun.2016.11.001 · Cited by 32
Osho, A. A., Castleberry, A. W., Snyder, L. D., Ganapathi, A. M., Hirji, S. A., Stafford-Smith, M., Lin, S. S., Davis, R. D., & Hartwig, M. G. (2014) · The Annals of Thoracic Surgery · doi:10.1016/j.athoracsur.2014.03.010 · Cited by 24
Osho, A. A., Castleberry, A. W., Snyder, L. D., Palmer, S. M., Stafford-Smith, M., Lin, S. S., Duane Davis, R., & Hartwig, M. G. (2014) · The Journal of Heart and Lung Transplantation · doi:10.1016/j.healun.2014.06.011 · Cited by 16
Metadata
- Authors
- Horvath, M. M., Winfield, S., Evans, S., Slopek, S., Shang, H., & Ferranti, J.
- Venue
- Journal of Biomedical Informatics
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 44
- Issue
- 2
- Pages
- 266-276
- ISSN
- 1532-0464 (ISSN-L)
- OpenAlex
- W2091372246
- Cited by
- 183
- References
- 2
- FWCI
- 16.09
- Type
- journal article
- Language
- en
- Open access
- bronze
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