%0 Journal Article %1 Horvath2011266 %A Horvath, Monica M. %A Winfield, Stephanie %A Evans, Steve %A Slopek, Steve %A Shang, Howard %A Ferranti, Jeffrey %D 2011 %J Journal of Biomedical Informatics %K dwh i2b2_alternative %N 2 %P 266 - 276 %R http://dx.doi.org/10.1016/j.jbi.2010.11.008 %T The \DEDUCE\ Guided Query tool: Providing simplified access to clinical data for research and quality improvement %U http://www.sciencedirect.com/science/article/pii/S1532046410001747 %V 44 %X 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.

@article{Horvath2011266, abstract = {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. }, added-at = {2016-09-15T13:43:43.000+0200}, author = {Horvath, Monica M. and Winfield, Stephanie and Evans, Steve and Slopek, Steve and Shang, Howard and Ferranti, Jeffrey}, biburl = {https://www.bibsonomy.org/bibtex/226790b80d3bbc0bd9ed474957601b190/dietrich}, doi = {http://dx.doi.org/10.1016/j.jbi.2010.11.008}, interhash = {9640eb3ad0ec747d9893d55cd843cd8d}, intrahash = {26790b80d3bbc0bd9ed474957601b190}, issn = {1532-0464}, journal = {Journal of Biomedical Informatics }, keywords = {dwh i2b2_alternative}, number = 2, pages = {266 - 276}, timestamp = {2016-09-15T13:43:43.000+0200}, title = {The \{DEDUCE\} Guided Query tool: Providing simplified access to clinical data for research and quality improvement }, url = {http://www.sciencedirect.com/science/article/pii/S1532046410001747}, volume = 44, year = 2011 }