AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
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Errors in clinical research databases are common but relatively little is known about their characteristics and optimal detection and prevention strategies. We have analyzed data from several clinical research databases at a single academic medical center to assess frequency, distribution and features of data entry errors. Error rates detected by the double-entry method ranged from 2.3 to 26.9%. ⋯ Error detection based on data constraint failure significantly underestimated total error rates and constraint-based alarms integrated into the database appear to prevent only a small fraction of errors. Many errors were non-random, organized in special and cognitive clusters, and some could potentially affect the interpretation of the study results. Further investigation is needed into the methods for detection and prevention of data errors in research.
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AMIA Annu Symp Proc · Nov 2008
Interruptions in workflow prior to the implementation of a Critical Care Information System (CCIS) in two intensive care settings.
Interruptions in clinician workflow are believed to contribute to preventable medical errors, and ICUs have been noted as frequent sites of these errors. Emerging research suggests that a CCIS may assist in reducing or preventing interruptions. However, there is a paucity of research that has empirically investigated these assertions. As part of a longitudinal study, results of the frequency and nature of interruptions in workflow before the implementation of a CCIS will be reported.
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AMIA Annu Symp Proc · Nov 2008
Comparative StudyComparison of ontology-based semantic-similarity measures.
Semantic-similarity measures quantify concept similarities in a given ontology. Potential applications for these measures include search, data mining, and knowledge discovery in database or decision-support systems that utilize ontologies. To date, there have not been comparisons of the different semantic-similarity approaches on a single ontology. ⋯ We found that there was poor agreement among those metrics based on information content with the ontology only metric. The metric based only on the ontology structure correlated most with expert opinion. Our results suggest that metrics based on the ontology only may be preferable to information-content-based metrics, and point to the need for more research on validating the different approaches.
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AMIA Annu Symp Proc · Nov 2008
Clinical TrialImplementing a computerized pneumococcal vaccination reminder system in an emergency department: a prospective study.
The Emergency Department is a challenging environment to implement a sustainable pneumococcal vaccination program. To increase vaccination rates for patients > or = 65 years old, we prospectively evaluated a closed-loop informatics approach over a 1-year period. Among 3,455 screened patients 1,393 were up-to-date and 2,062 were eligible for the vaccination. 159 (7.7%) patients received the vaccine at the initial visit and an additional 59 (2.9%) at a subsequent visit, resulting in an overall rate increase of 10.6%.
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AMIA Annu Symp Proc · Nov 2008
Supporting the design of translational clinical studies through the generation and verification of conceptual knowledge-anchored hypotheses.
The ability to generate hypotheses based upon the contents of large-scale, heterogeneous data sets is critical to the design of translational clinical studies. In previous reports, we have described the application of a conceptual knowledge engineering technique, known as constructive induction (CI) in order to satisfy such needs. ⋯ Our report will be framed in the context of an ongoing project to generate hypotheses related to the contents of a translational research data repository maintained by the CLL Research Consortium. Such hypotheses will are intended to inform the design of prospective clinical studies that can elucidate the relationships that may exist between biomarkers and patient phenotypes.