Big science, big data, and a big role for biomedical informatics.
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001052
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2012-001052
Inadequate participant recruitment is a major problem facing clinical research. Recent studies have demonstrated that electronic health record (EHR)-based, point-of-care, clinical trial alerts (CTA) can improve participant recruitment to certain clinical research studies. Despite their promise, much remains to be learned about the use of CTAs. Our objective was to study whether repeated exposure to such alerts leads to declining user responsiveness and to characterize its extent if present to [...]
Author(s): Embi, Peter J, Leonard, Anthony C
DOI: 10.1136/amiajnl-2011-000743
The objective of this study is to develop an approach to evaluate the quality of terminological annotations on the value set (ie, enumerated value domain) components of the common data elements (CDEs) in the context of clinical research using both unified medical language system (UMLS) semantic types and groups.
Author(s): Jiang, Guoqian, Solbrig, Harold R, Chute, Christopher G
DOI: 10.1136/amiajnl-2011-000739
Profiling the allocation and trend of research activity is of interest to funding agencies, administrators, and researchers. However, the lack of a common classification system hinders the comprehensive and systematic profiling of research activities. This study introduces ontology-based annotation as a method to overcome this difficulty. Analyzing over a decade of funding data and publication data, the trends of disease research are profiled across topics, across institutions, and over time.
Author(s): Liu, Yi, Coulet, Adrien, LePendu, Paea, Shah, Nigam H
DOI: 10.1136/amiajnl-2011-000631
Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated data sources necessary to conduct retrospective analytic research and to identify and recruit prospective research subjects. The Clinical and Translational Science Award (CTSA) consortium's Informatics IDR Group conducted a survey of 2010 consortium members to evaluate recent trends in IDR implementation and use to support research between 2008 and [...]
Author(s): MacKenzie, Sandra L, Wyatt, Matt C, Schuff, Robert, Tenenbaum, Jessica D, Anderson, Nick
DOI: 10.1136/amiajnl-2011-000508
The Massachusetts Veterans Epidemiology Research and Information Center in collaboration with the Stanford Center for Innovative Study Design set out to test the feasibility of a new method of evidence generation. The first pilot of a point-of-care clinical trial (POCCT), adding randomization and other study processes to an electronic medical record (EMR) system, was launched to compare the effectiveness of two insulin regimens.
Author(s): D'Avolio, Leonard, Ferguson, Ryan, Goryachev, Sergey, Woods, Patricia, Sabin, Thomas, O'Neil, Joseph, Conrad, Chester, Gillon, Joseph, Escalera, Jasmine, Brophy, Mary, Lavori, Phillip, Fiore, Louis
DOI: 10.1136/amiajnl-2011-000623
To address the challenge of balancing privacy with the need to create cross-site research registry records on individual patients, while matching the data for a given patient as he or she moves between participating sites. To evaluate the strategy of generating anonymous identifiers based on real identifiers in such a way that the chances of a shared patient being accurately identified were maximized, and the chances of incorrectly joining two [...]
Author(s): Weber, Susan C, Lowe, Henry, Das, Amar, Ferris, Todd
DOI: 10.1136/amiajnl-2011-000329
National organizations historically focused on increasing use of effective services are now attempting to identify and discourage use of low-value services. Electronic health records (EHRs) could be used to measure use of low-value services, but few studies have examined this. The aim of the study was to: (1) determine if EHR data can be used to identify women eligible for an extended Pap testing interval; (2) determine the proportion of [...]
Author(s): Mathias, Jason S, Gossett, Dana, Baker, David W
DOI: 10.1136/amiajnl-2011-000536
To explore the feasibility of using statistical text classification to automatically detect extreme-risk events in clinical incident reports.
Author(s): Ong, Mei-Sing, Magrabi, Farah, Coiera, Enrico
DOI: 10.1136/amiajnl-2011-000562
Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance.
Author(s): Liu, Mei, Wu, Yonghui, Chen, Yukun, Sun, Jingchun, Zhao, Zhongming, Chen, Xue-wen, Matheny, Michael Edwin, Xu, Hua
DOI: 10.1136/amiajnl-2011-000699