Challenges in using the Arden Syntax for computer-based nosocomial infection surveillance

CONTEXT: Detection of outbreaks of infection in the hospital typically requires daily manual review of microbiology laboratory test results. This process is time-consuming, tedious, prone to error and may miss trends in infection. A standard formalism for procedural knowledge representation, the Ard...

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Veröffentlicht in:Proceedings. AMIA Symposium. - 1998. - (2001) vom: 11., Seite 289-93
1. Verfasser: Jenders, R A (VerfasserIn)
Weitere Verfasser: Shah, A
Format: Aufsatz
Sprache:English
Veröffentlicht: 2001
Zugriff auf das übergeordnete Werk:Proceedings. AMIA Symposium
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.
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100 1 |a Jenders, R A  |e verfasserin  |4 aut 
245 1 0 |a Challenges in using the Arden Syntax for computer-based nosocomial infection surveillance 
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500 |a Date Completed 24.05.2002 
500 |a Date Revised 13.11.2018 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a CONTEXT: Detection of outbreaks of infection in the hospital typically requires daily manual review of microbiology laboratory test results. This process is time-consuming, tedious, prone to error and may miss trends in infection. A standard formalism for procedural knowledge representation, the Arden Syntax, provides a vehicle for implementing algorithms for detecting such infections 
520 |a OBJECTIVE: To design and implement a computer-based system for detection of concerning patterns of infection or antibiotic resistance 
520 |a SETTING: Computer-based event monitor and central patient data repository at the Columbia-Presbyterian Medical Center (CPMC) 
520 |a RESULTS: We designed a two-phase system, including initial filtering of individual patient laboratory results by Arden Syntax Medical Logic Modules (MLMs) and subsequent aggregation and analysis across patients and locations using a statistical monitor. Preliminary data for the filtration phase demonstrate a 94.8% reduction in the volume of messages that must be considered in surveillance 
520 |a CONCLUSIONS: Filtering raw laboratory results using a standard formalism eases the process of aggregating data across patients and sites as well as detecting trends in infection. There is a need for augmenting such formalisms in order to enable population-based decision support 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Research Support, U.S. Gov't, P.H.S. 
700 1 |a Shah, A  |e verfasserin  |4 aut 
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