{"title":"在基于计算机的医院感染监测中使用Arden语法的挑战","authors":"R. Jenders, Anuj P. Shah","doi":"10.1197/JAMIA.M1237","DOIUrl":null,"url":null,"abstract":"CONTEXT\nDetection 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.\n\n\nOBJECTIVE\nTo design and implement a computer-based system for detection of concerning patterns of infection or antibiotic resistance.\n\n\nSETTING\nComputer-based event monitor and central patient data repository at the Columbia-Presbyterian Medical Center (CPMC).\n\n\nRESULTS\nWe 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.\n\n\nCONCLUSIONS\nFiltering 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.","PeriodicalId":79712,"journal":{"name":"Proceedings. AMIA Symposium","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1197/JAMIA.M1237","citationCount":"8","resultStr":"{\"title\":\"Challenges in Using the Arden Syntax for Computer-Based Nosocomial Infection Surveillance\",\"authors\":\"R. Jenders, Anuj P. Shah\",\"doi\":\"10.1197/JAMIA.M1237\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"CONTEXT\\nDetection 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.\\n\\n\\nOBJECTIVE\\nTo design and implement a computer-based system for detection of concerning patterns of infection or antibiotic resistance.\\n\\n\\nSETTING\\nComputer-based event monitor and central patient data repository at the Columbia-Presbyterian Medical Center (CPMC).\\n\\n\\nRESULTS\\nWe 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.\\n\\n\\nCONCLUSIONS\\nFiltering 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.\",\"PeriodicalId\":79712,\"journal\":{\"name\":\"Proceedings. AMIA Symposium\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1197/JAMIA.M1237\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. AMIA Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1197/JAMIA.M1237\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. AMIA Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1197/JAMIA.M1237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 Arden Syntax, provides a vehicle for implementing algorithms for detecting such infections.
OBJECTIVE
To design and implement a computer-based system for detection of concerning patterns of infection or antibiotic resistance.
SETTING
Computer-based event monitor and central patient data repository at the Columbia-Presbyterian Medical Center (CPMC).
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.
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.